2014-15 Annual Report

NCI, The Australian National University Annual Report 2014/15 143 Ward Road, World-class high-end computing services for Australian researchers Acton ACT 2601 www.nci.org.au National Computational Infrastructure The Australian National University 143 Ward Road Acton ACT 2601 T +61 2 6125 9800 E [email protected] W nci.org.au

National Computational Infrastructure Annual Report 2014/15

@NCInews World-class high-end computing services for Australian research and innovation NCINationalFacility

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Erica Seccombe, Grow, 2013, (detail), 4D Microcomputed Tomographic X-ray volumetric time-lapse of seeds germinating, single channel projection, formatted for stereoscopic viewing with circular polarized glasses, silver screen, duration: 6min. Visualised and animated using NCI’s Drishti software. 16 Annual Report 2014/15 iii Predicting sea level rise Predicting Shining new light on the body 38 37 Collaboration: Working together to build together Collaboration: Working Visualisation: Visualising butterfly Code enhancements achieved by Code enhancements achieved Data Collection The NCI National Research 19 competitive 2014 Merit Allocation Scheme NCI training courses cloud environment NCI’s activities Building tours and outreach by NCI staff presentations Conference Financial report 61 62 55 36 69 light in the Cloud computing: Splitting Highly parallel computing: Scaling data Big data: Revolutionising satellite for 2014/15 Compute allocation profile 33 massive models datasets massive Capability: 3 cloud Capability: national Capability: 5 analysis Capability: Deep-water ocean modelling for industry supported by NCI New agricultural precinct 6 user prize for NCI Top 4 wings in 3D AAS Fellowships awarded NCI researchers Our new partners: Our new partners: 18 9 4D earth modelling supported by industry solar cell efficiency Super-charging 35 Better materials for industry Solvents of the future What drives the deep 39 ‘Goldilocks problem’ Carbon capture’s stars neutron for super-dense Searching 31 crops to hit WA frosts More 7 40 New function for Nobel compound history the Sun’s Tracking drug design Computer-aided 44 41 45 42 47 43 46 49 48 Tables 1: Table profile 2: Table 3: Table 4: Table NCI in 2014/15 grant 5: Table 6: Table 34 7: Table 8: Table 9: Table highlights Research Capability: 12 GOVERNANCE AND FINANCE 65 OUR USERS OUR INFRASTRUCTURE 29 51 OUTREACH 59 PROJECT LIST 71 NCI’s capabilities capabilities NCI’s Collection Data NCI National Research Research National Environmental NCI’s Data Management Process NCI’s channel statistics Drishti YouTube Our users Compute allocation of NCMAS projects 16 2 23 Cloud statistics Filesystem configuration Data storage statistics Media and online engagement Organisational structure 57 60 30 57 55 66

Capabilities 2 Capabilities Innovation High-performance Computation 8 Innovation High-Performance Data Digital Laboratories Scientiﬁc Visualisation 13 22 24 The NCI Board Financial Report 66 68 Access Schemes User Services Highlights Research Raijin Cloud Data Storage 32 37 36 53 54 56

OUR RESEARCH ENGAGEMENT OUR RESEARCH ENGAGEMENT 1 SECTION 2: SECTION 5: APPENDIX: progress Figures 13 1: Figure 2: Figure ingest 3: Figure 4: Figure 5: Figure 6: Figure Platform Data Interoperability 7: Figure 8: Figure 9: Figure 10: Figure 14 ﬁeld by research on Raijin 11: Figure 12: Figure 35 Table of Contents Table IV Introduction ReportChair’s ReportDirector’s at a glance The year Snapshot: at a glance specs System Our partners and afﬁliates SECTION 1: VIII X VII VI XI SECTION 3: SECTION 4:

Annual Report 2014/15 V *

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commercialisation stage. and innovation NCI has been crucial the success of to Supporting industry “ INDUSTRY my research, which has now moved into the into moved has now which research, my *Feedback from the 2014 NCI User Survey Our values & quality: Innovation research of high-performance in the provision laboratories for services and digital computing is underpinned all of which research, data-intensive applications support and by our infrastructure quality and innovation of for the teams, recognised the services they provide. What we do we University, Australian National Based at The (HPC) and high-performance computing provide (HPD) services to a number high-performance data agencies, including CSIRO, of the national science of the Australian Bureau Geoscience Australia, 2,000+ researchers and a further Meteorology, of five ARC Centres at 31 Australian universities, Excellence, and industry. first petaflop home to the nation’s are We research its highest-performance supercomputer, cloud, its fastest filesystems and its largest renowned are Our staff data repository. research nationally and internationally for their expertise. and expertise This combination of infrastructure and innovation enables high-impact research that otherwise would be impossible to undertake, delivers outcomes that inform public policy and national benefits, both in the public sector and supports an internationally and in industry, that attracts and environment competitive research for Australia. world-class researchers retains *

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The national and strategic nature of NCI is nature The national and strategic funding model, reﬂecting demonstrated in our Australian of (a) the responsibilities the shared National Collaborative its Government—through Strategy (NCRIS), for the Infrastructure Research and (b) the of world-class infrastructure, provision sector—comprising science agencies, research universities, industry and the Australian Research of Council, which collectively contribute two-thirds costs. the recurrent NCI Australia is the nation’s most highly-integrated, most highly-integrated, is the nation’s NCI Australia environment. computing high-performance research on national to deliver NCI has been architected driven are excellence. We priorities and research of raising the ambition, by our primary objective of Australian research. impact, and outcomes Introduction are Who we

Annual Report 2014/15 VII optimise weather forecasting models of critical forecasting optimise weather management Our data national significance. international received teams have acclamation of the NCI environmental for the development stack, and have data services interoperability in the progress also made nation-leading Australian Government-funded of NCI’s creation 13). The operations (see page data repository a year of outstanding teams has delivered new cloud service, and has implemented a new high-performance services, established and further enhanced its persistent filesystem, in the international HPC community reputation contributions (bug fixes, patches) with numerous to Linux and Lustre. None of this could have been achieved without the expertise and commitment of our staff each and every member and I thank sincerely and of the team for their ongoing dedication for its insightful innovation. I thank also the Board and the expanding partnership that stewardship supports NCI. if it Of course, NCI would neither exist nor evolve community not for the Australian research were whose goals on our infrastructure, that relies of spur us to enhance the quality and innovation our services, and whose well successes reflect to on us. I look forward working with you all in the future. Professor Lindsay Botten NCI Director, Director’s Report Director’s progress strong has seen ongoing This past year high- mission of world-class, NCI’s in advancing research services for Australian end computing of our infrastructure, and innovation. All aspects and operations are services development, and priorities objectives driven by the research and our community of the national research Unique in Australia, we partner organisations. integrated research have evolved as a highly portfolio that with a service e-infrastructure computation and high- sees high-performance services as natural performance data-intensive vision of enabling research by a peers. Grounded is that would not otherwise be possible, NCI delivering solutions for high-impact research and delivers that matters, informs public policy, national benefits. national high- NCI is truly Australia’s Today, We facility. performance computing research the work of than 550 projects, service more Australia. Of throughout 2,000 researchers ARC-funded than 190 are more these projects, $43 million activities, which collectively receive the ARC. NCI was acknowledged p.a. from than 1,400 journalin more in the past articles equally between the university split roughly year, sector and the science agencies. These CSIRO of Meteorology, agencies, the Bureau using and Geoscience Australia, undertake R&D NCI facilities that deliver enormous benefits the to Australia including the development of model, and next-generation weather prediction the implementation of the Australian Geoscience Chair notes, as the Board Data Cube. Further, exploiting NCI the portfolio of industry projects national amplifies the importance of a strong innovation system. HPC capability for Australia’s of several new This year has seen the creation expert service teams at NCI, enhancing the and depth of the ways in which we can breadth support our users. Of particular note is the new who HPC Development and Innovations Team working closely with our major partners to are

This report demonstrates the diversity and the the diversity demonstrates This report and of the research impact ground-breaking I invite you tosupported by NCI, and innovation this throughout Highlights peruse the Research you will ﬁnd Dr Katya Pas from Report. On page 42 about her revolutionary Monash University talking as the industrial solvents of thework on ionic liquids unique capacity as Page 5 highlights NCI’s future. while the expertise of NCIa collaborative platform, the scaling of high- in optimising and enhancing staff showcased on page 12. performance codes is work the hard to recognise I take this opportunity theand dedication of everyone at NCI, including Lindsay Botten, Associate Professor Director, Allan WilliamsDirectors and Dr Ben Evans, Business Chairman Deputy Manager Amanda Walker, Robin Stanton, and the NCI Emeritus Professor Without Board. their outstanding commitment, milestones the impressive could not herein reported have been achieved. Emeritus Professor Mark Wainwright AM FTSE NCI Board Chair,

The importance of NCI, and its value to the nationalThe importance of NCI, and its value to the community is amply computational research by the unanimous decision of our recognised their commitment to partner organisations to renew from the NCI Collaboration for a further two years of the Collaboration the end of 2015. The renewal of NCI’s (which sustains two-thirds Agreement costs), particularly in financially straitened recurrent times for government agencies and universities, and on is a very significant milestone for this year, I thank all organisations for their behalf of the Board ongoing support. Chair’s Report Chair’s Report. In 2014–15 NCI Annual to the Welcome many examples pages you will find the following that has and innovation research of the excellent the support of Australia’s been taking place with over the past computing facility national research that over the past year report I am pleased to year. the Collaboration with in strength, NCI has grown Deakin University, new members, now having three Climate and the Antarctic RMIT University and the University of Ecosystems CRC (through its industry portfolio is growing Further, Tasmania). by NCI provided services through directly steadily, science agency through and indirectly to industry, partner organisations.

Annual Report 2014/15 IX ” 4 6 Dr Adam Lewis, Lewis, Dr Adam 6 & Marine Observations branch NCI has allowed us to revolutionise revolutionise us to NCI has allowed “ Head of Geoscience Australia’s National Earth Head of Geoscience Australia’s June 2015 than 7 PB of nationally significant So far more RDSI- datasets has been ingested into NCI’s and made available to the funded data repository community. research approaches to the analysis of satellite data. of satellite the analysis to approaches 5 5 4 June 2015 Drishti Prayog visualisation NCI’s is software presentation displayed at the Emerging in Conference Technology UK. Manchester, February 2015 February system for the data transfer A new high-speed international large datasets is ingest of very installed. April 2015 with Fujitsu to work with NCI signs a $2M deal install the 8 PB g/data3 NetApp to supply and be accessible on Raijin and filesystem, which will GB/sec. the cloud at up to 140 2015 May NCI is allocated $5.3M from the National Collaborative Research Strategy Infrastructure for 2015–16 Project. May 2015 NCI-supported CSIRO nanotechnologist, Dr Amanda Barnard, wins the Institute Feynman Foresight Prize (see page 31). 3 2 3 January 2015 The g/data2 site-wide persistent 2 December 2014 partner in the NCI is named as the infrastructure Sciences National Agricultural and Environmental funded by the Science and Industry Precinct, Minister Investment Fund, and announced by the for Industry and Science (see page 18). December 2014 Science The NCI-hosted Climate and Weather to the research Laboratory is released was community (see page 22). The laboratory built and developed by a partnership of the CSIRO, the ARC Centre of Meteorology, Bureau and of Excellence in Climate Systems Science NCI. November 2014 Geoscience Australia’s Water Observations from supported Space project, (see Australia Award by NCI, wins a Resilient page 6). filesystem enters full production service, filesystem enters full production 4.5 PB to 6.7 PB. expanding from 1 1

the year at a glance the year

September 2014 cloud, supercomputer-grade NCI’s Tenjin, becomes available to our partner organisations. September 2014 Visit to NCI by the then Minister for MP. Communications, the Hon. Malcolm Turnbull, August 2014 internet primary to connection is upgraded NCI’s from the latest generation AARNET4 link, moving a capped to a dedicated full bandwidth 10 Gigabit connection.

July 2014 July the functionality commences on optimising Work primary climate and weather of Australia’s jointly funded a project modelling suite through NCI, and undertaken in by Fujitsu Limited and and CSIRO collaboration with BoM (see page 10). Snap shot – shot Snap

VIII

Annual Report 2014/15 XI Supported by Supported Collaborating Organisations Australia’s highest-performing research cloud research highest-performing Australia’s 33.5 TFlop peak performance Bridge, 2.6 GHz) (Sandy 1,600 Intel Xeon cores in 100 nodes Inﬁniband full fat-tree Mellanox FDR 56 Gb/sec interconnect Fujitsu PRIMEHPC FX10 system 7+ PB of nationally and internationally signiﬁcant datasets • • • • • 25 TB main memory Disk • 160 TB Solid State repository • Access to 20 PB data • • 22 TFlop peak performance IXfx cores • 1,536 SPARC • 3 TB memory • • Tightly Tenjin integrated with Raijin and Tenjin: Fujin: data catalogue: largest research Australia’s

7 PB scratch storage on Raijin accessed 7 PB scratch storage on Raijin accessed at 150 GB/sec storage accessed 22 PB active project at up to 140 GB/sec data accessed 12 PB archived at up to 140 MB/sec 49 PB capacity Spectra Logic tape array Fujitsu Primergy clusterFujitsu Primergy 57,472 Intel Xeon cores (Sandy Bridge, 2.6 GHz) Inﬁniband full fat-tree Mellanox FDR 56 Gb/sec interconnect • • • • • • 1.2 PFlops peak performance • • • 160 TB main memory • 10 PB disk storage hours/annum • 503M core packages • 300+ software repository • Access to 20 PB data

Fastest ﬁlesystems in the Southern (Lustre): Hemisphere System specs at a glance at specs System Raijin:

A node of RDS Research Data Services

Commercial Partners

Afﬁliates

1 Our Research Engagement XII 1 Annual Report 2014/15 3 ” MVY*SPTH[L:`Z[LT:JPLUJL critical software problems. critical software The expertise of the NCI team has has of the NCI team The expertise ¸;OLJVSSHIVYH[VYZOH]L^VYRLK]LY`LɈLJ[P]LS` [VNL[OLY[VYLHSPZL[OLZLPTWYV]LTLU[Z;OLL_WLY[PZL aof the NCI team has been essential to solving U\TILYVMJYP[PJHSZVM[^HYLWYVISLTZ¹ZH`Z+Y Naughton. 5*0»ZL_WLY[ZOH]LHSZVILLUJVSSHIVYH[PUN^P[O[OL (9**LU[YLVM,_JLSSLUJLMVY*SPTH[L:`Z[LT:JPLUJL the scalability of the US Geophysical Fluid to improve +ÙHTPJZ3HIVYH[VY`»Z4VK\SHY6JLHU4VKLSÔPJO models. weather prediction is critical for BoM’s yielded a substantial The collaboration has already 2,000 the scalability of the model, from in increase of than a third allowing use of more to 20,000 cores, 9HPQPU»Z[V[HSJVYLZ^P[OPUHZPUNSLY\UBYLHKTVYLVU page 11]. ¸6\YZWLJ[HJ\SHY4VK\SHY6JLHU4VKLS^VYRSLKI` (5<OHZILULÄ[[LKMYVTMHU[HZ[PJZ\WWVY[MYVT[OL 5*0[LHT¹ZH`Z7YVMLZZVY(UKYL^7P[THU+PYLJ[VY (9**LU[YLVM,_JLSSLUJL “ been essential to solving a number of solving been essential to HIGHLY PARALLEL COMPUTING PARALLEL HIGHLY CAPABILITY HIGHLIGHT: CAPABILITY For the past two years, the Australian Bureau of For the past two years, the Australian Bureau (BoM) has been working closely with NCI Meteorology [V[LZ[HUKYLÄULP[ZUL_[NLULYH[PVUUH[PVUHS^LH[OLY models. prediction ¸>L»YL[YPHSSPUNV\YUL_[NLULYH[PVUTVKLSZVU9HPQPUPU for them becoming operational in a year or preparation [^V¹L_WSHPUZ+Y4PJOHLS5H\NO[VUMYVT)V4 “Every day at NCI we run Australian Community Climate and Earth System Simulator (ACCESS) suites, which support numerical weather prediction systems, with and evaluation of prototype research HZWLJPHSMVJ\ZVUZL]LYLHUKOPNOPTWHJ[^LH[OLY events in the Australian region.” (ZWHY[VMHJVSSHIVYH[PVU^P[O-\QP[Z\[OL5*0JVKL optimisation team have been working with BoM, -\QP[Z\*:096HUK[OL(9**LU[YLVM,_JLSSLUJLMVY *SPTH[L:`Z[LT:JPLUJL[VPUJYLHZL[OLLɉJPLUJ`VM they run,the ACCESS component models. The faster that can be supported, and the the model the larger the detail and accuracy provided. greater input/output collaboration on asynchronous Already a time saving of up to 20% has realised processing using 2,000 cores. Scaling massive models massive Scaling Data storage Collaboration NCI’s capabilities NCI’s Figure 1: Figure Our services are provided within a tightly integrated within a tightly provided Our services are supported by expert framework and infrastructure fields. world leaders in their who are staff HPC Visualisation

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We offer everything Australian researchers and everything Australian researchers offer We government need to analyse, access, agencies publish and visualise data. share, NCI is unique in the world, offering Australia’s Australia’s offering NCI is unique in the world, fastest Australia’s first petaflop supercomputer, largest research cloud and Australia’s research with the Southern tightly integrated data repository, filesystems. fastest Hemisphere’s Engagement Capabilities Our Research Research Our

2 1 Annual Report 2014/15 5 ” that’s through this work. gained ¸,]LUTVYLPTWVY[HU[S`;,95HUK046:HYLT\S[P institutional endeavours founded on cooperation. In contrast to many of our participating institutions, ÔPJOOH]LLU[LYWYPZLÄYL^HSSZ^P[OZLJ\YP[`WVSPJPLZ membership, NCI is set up as a tied to organisation collaborative environment.” leading The collaboration saves both time and money, [VTVYLLɉJPLU[HUKLɈLJ[P]LV\[JVTLZHKKZ+Y King. ¸;OLYL»ZHTHZZP]LUH[PVUHSLɉJPLUJ`[OH[»ZNHPULK work because we can have a single this through dataset, instead of one dataset for each agency. we can make that single dataset “Furthermore, meeting the needs of both terrestrial comprehensive, HUKTHYPUL\ZLYZÔLYLHZWYL]PV\ZS`KPɈLYLU[ subsetsinstitutions would likely have held overlapping of the whole. ¸;OLHIPSP[`[VZOHYLYLZV\YJLZIL[^LLUUV[Q\Z[ links within institutions, but also domains strengthens sector and enables more the Australian research integrative science, bringing together complementary L_WLY[PZL[VHKKYLZZTVYLJVTWSL_JOHSSLUNLZ¹ There’s a massive national efficiency national efficiency a massive There’s “ COLLABORATION Image courtesy of NASA CAPABILITY HIGHLIGHT: HIGHLIGHT: CAPABILITY NCI is the platform of collaboration between our fellowNCI is the platform of collaboration between 5*90:MHJPSP[PLZ[OL0U[LNYH[LK4HYPUL6IZLY]PUN :`Z[LT046:HUK[OL;LYYLZ[YPHS,JVZ`Z[LT 9LZLHYJO5L[^VYR;,95>VYRPUN[VNL[OLY^LHYL building national datasets housed at NCI. 046:9LTV[L:LUZPUN-HJPSP[`3LHKLY+Y,K^HYK 2PUNÔVPZIHZLKH[*:096PU;HZTHUPHZH`ZOH]PUN access to NCI allows his team to easily collaborate ^P[O;,95HUK\UKLY[HRL^VYR[OH[^V\SKU»[IL possible otherwise. ¸6ULVMT`YVSLZPZ[VVYNHUPZLSHYNLZH[LSSP[LPTHNL than ten years, thousands of datasets, spanning more images and tens of terabytes of data,” he says. datasets and these large “NCI lets us organise andcollaborate with other institutions, agencies easily do inside our in a way we can’t organisations own organisations.” the pastAcquisition of satellite data has boomed over KLJHKLHUKWYVQLJ[PVUZMVY[OLM\[\YLHYLYLHJOPUN [OL[LUZVMWL[HI`[LZZJHSLWYLZLU[PUNHJVTWSL_ computational challenge. our in satellite data was stretching “The growth JVTW\[LJHWHIPSP[PLZH[[OL[PTL;,95HUK046: ^LYLJVTPUNPU[VILPUN¹L_WSHPUZ+Y2PUN “The high capacity and performance of the NCI were than equal to the task and made it a natural more choice as a platform on which to build our national data collections. Working together to build together Working datasets national normally see in everyday life. normally see to grind out solutions of “This means you have 4H_^LSS»ZLX\H[PVUZVMLSLJ[YVTHNUL[PJ[OLVY`H[[OL computing you need large nanoscale, and for that power.” ;OL5*0JSV\KLU]PYVUTLU[PZ^LSSZ\P[LK[V4Y because it allows immediate research Sturmberg’s outputs. interaction with software simulations that only take a “I am now able to run change something away, minute, look at them straight them again,” he says. in the model, and run thing is that our collaborators at ANU “The other great at the University of Sydney and other students here that I who want to use the same simulation package without having have developed can access it directly to worry about operating systems.” )HJRLKI`[OL(9**LU[YLVM,_JLSSLUJLMVYOP[LHUK at ANU to bring his simulations Kylie Catchpole Prof to life in the lab. to do the modelling to try and use NCI “We understand what physics is going on in these and then ANU fabricates and tests nanostructures, [OLZ[Y\J[\YLZPU[OLSHI¹OLL_WSHPUZ CLOUD COMPUTING CLOUD

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4 1 Annual Report 2014/15 7 The team made the discovery by employing the powerThe team made the discovery by employing VM9HPQPU[VWPLJL[VNL[OLY[OV\ZHUKZVMTPJYVZJVWPJ PTHNLZVMI\[[LYÅ`^PUNSH`LYZ[VNLULYH[L[OLÄYZ[+ YLJVUZ[Y\J[PVUVMI\[[LYÅ`WOV[VUPJJY`Z[HSZ ;OLKPZJV]LYÒHZMHYYLHJOPUNWV[LU[PHSHWWSPJH[PVUZ using metallic iridescent already Car companies are WHPU[IHZLKVUI\[[LYÅ`WOV[VUPJJY`Z[HSZ =0+,6!O[[W!IP[S`Å`PUNJVS VISUALISATION ” supercomputers. Butterfly wings could harbour Butterfly “ the blueprint for next-generation next-generation the blueprint for CAPABILITY HIGHLIGHT: CAPABILITY 9LZLHYJOLYZMYVT(56M:ÔPJOTHWZZ\YMHJL^H[LYHJYVZZ Australia,” he says. ;OL>6M:WYVQLJ[YLJLP]LK[OLUH[PVUHSS` ZPNUPÄJHU[^VYRH^HYKPU[OL.V]LYUTLU[JH[LNVY`H[ [OL9LZPSPLU[(\Z[YHSPH(^HYKZ of Geoscience Australia’s NCI is an integral part JHWHIPSP[`ZH`Z+Y3L^PZ ¸;OL5*0PZILULÄ[[PUNHSSHYLHZVM.LVZJPLUJL says. Australia science,” he our partnership with NCI we have been “Through able to develop our quantitative science cost LɈLJ[P]LS`HUK[VPUJYLHZLV\YJVSSHIVYH[PVU^P[O V[OLYVYNHUPZH[PVUZZ\JOHZ[OL*:096[OL)\YLH\VM and ANU, to name a few. Meteorology ¸-VYL_HTWSL^L»]LKL]LSVWLKHJVOLYLU[PTHNL of the Australian of the deep geological structure future continent, which is an essential step toward because it helps us to ‘see’ minerals prospecting that covers much of Australia. beneath the regolith ¸>LZLLV\YWHY[ULYZOPWPU5*0HZHUL_LTWSHYVM collaboration in Australian government science, which also leverages other government investments, such HZ[OL9LZLHYJO+H[H:LY]PJLZ0UMYHZ[Y\J[\YL[V TH_PTPZL]HS\LHUKPTWHJ[MVY[OL[H_WH`LYHUK[OL government.” “ approaches to the analysis of data. the analysis to approaches BIG DATA BIG

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CAPABILITY HIGHLIGHT: CAPABILITY NCI is working with our Collaborating PartnerNCI is working with our than two unlock more Geoscience Australia to data of national policymakingpetabytes of geoscience ZPNUPÄJHUJL Government’s the Australian With support from 9LZLHYJO+H[H:[VYHNL0UMYHZ[Y\J[\YLWYVQLJ[L_WLY[Z have been tackling NCI and Geoscience Australia from migrating this dataset to NCI.the mammoth task of ;OLKH[HYLWYLZLU[ZKPZ[PUJ[WYVQLJ[ZPUJS\KPUN earth observation30 years’ worth of Australasian PTHNLZNLULYH[LKI`5(:(»Z3HUKZH[ZH[LSSP[LZHUK [OL(\Z[YHSPHU5H[\YHS/HaHYKZ+H[H(YJOP]L^OPJO hazard, includes observational and probabilistic tsunami,impact and risk data covering earthquakes, ÅVVKZHUK[YVWPJHSJ`JSVULZ -VSSV^PUNTPNYH[PVU5*0»Z+H[H4HUHNLTLU[ collaborates closely with data managers at Team data Geoscience Australia to develop comprehensive eachmanagement plans to outline how best to make KH[HZL[HJJLZZPISLZLHYJOHISLHUKZOHYLHISLBZLL page 15]. ;OLPU[LNYH[PVUVM5*0»ZÄSLZ`Z[LTZ^P[O9HPQPU to capacity has enhanced Geoscience Australia’s HUHS`ZL[OLPYKH[HZL[ZZH`Z+Y(KHT3L^PZ/LHK & Marine National Earth of Geoscience Australia’s 6IZLY]H[PVUZIYHUJO to approaches “NCI has allowed us to revolutionise the Australian the analysis of satellite data through .LVZJPLUJL+H[H*\ILWYVK\JPUN^VYSKÄYZ[ WYVK\J[ZZ\JOHZV\Y>H[LY6IZLY]H[PVUZMYVT:WHJL

data analysis analysis data Revolutionising satellite satellite Revolutionising

6 1 Annual Report 2014/15 9 ” unparalleled in Australia. unparalleled in thousands of storms and taking into account all theof storms and taking into thousands variables. cyclone simulation involved in each “The processes HYLZVJVTWSL_[OH[`V\ULLK[V\ZL]LY`ÄUL YLZVS\[PVU+TVKLSZZVS]PUN]LY`JVTWSL_ mathematical equations. feasibly do this is by using“The only way you can if not hundreds you can run a HPC facility where at the same time andthousands of storm simulations weeks in a matter of a few deliver results thereby instead of months.” the decision to move to NCIMr Brandi Mortensen says ^HZKYP]LUI`[OLULLK[VLUJVTWHZZNYV^[OPU+/0»Z research. to think ahead in terms of the magnitude needed “We toof our simulations – how many storms we needed run,” he says. all under one access to 57,000 cores “NCI provides which is unparalleled in Australia. an environment roof, very happy to be working with NCI and we are “We to working together to move our science look forward in a good direction.” NCI provides an environment which is which an environment NCI provides “ RESEARCH HIGHLIGHT RESEARCH Deep-water ocean modelling for industry ocean modelling Deep-water 5*0PZWYV]PKPUNOPNOWLYMVYTHUJLJVTW\[H[PVUHS ZLY]PJLZ[VNSVIHSUV[MVYWYVÄ[LUNPULLYPUN VYNHUPZH[PVU+/0>H[LYHUK,U]PYVUTLU[7[`3[K ¸>LZWLJPHSPZLPULUNPULLYPUNPU]VS]PUN^H[LY¹L_WSHPUZ +/0»Z/LHKVM4HYPUL:PTVU)YHUKP4VY[LUZLU like waves water, coastal and marine “Everything from HUKVJLHUJPYJ\SH[PVU[VWVY[ZHUKZOPWZHUKÅVVKPUN management.risk and industrial water ¸>LHYL\ZPUN9HPQPU[VJHSJ\SH[LPUNYLH[KL[HPSOV^ ^H]LZHUKJ\YYLU[ZHYV\UK[OLUVY[O^LZ[VM(\Z[YHSPH and in behaving, both in normal conditions are to cyclones.” response to oil and gas The work is of particular interest understanding a thorough companies, which require VMVJLHUJ\YYLU[Z[VPUMVYTKLZPNUVMKLLW^H[LY such as oil rigs, pipelines and moored infrastructure ships. ¸6PSHUKNHZJVTWHUPLZ^HU[[VRUV^^OH[ZVY[VM J\YYLU[Z[OL`JHUL_WLJ[PUKPɈLYLU[WHY[ZVM(\Z[YHSPHU can their infrastructure waters so they can ensure ^P[OZ[HUKHPU`LHYJOHUJLUH[\YHSKPZHZ[LY SPRLHTHQVYJ`JSVUL¹L_WSHPUZ4Y)YHUKP4VY[LUZLU ¸;OLJOHSSLUNLPZ[OH[PUVYKLY[VWYLKPJ[H`LHY cyclone event you need to describe the predicted simulating climate over 10,000 years. That requires and Industry Innovate. to Optimisation of the Australian Community Optimisation of the Australian Simulator model, Climate and Earth System and and Development into advanced Research computational scaling and tools. NCI: Enabling Government, Researchers Researchers NCI: Enabling Government, • • HPC Development and and HPC Development Innovations with national and has been working NCI This year, international of optimise a selection collaborators to most important computational models. the globe’s FUJITSU COLLABORATION Fujitsu signed a formalIn April 2014 NCI and by a supported Collaboration Agreement, NCI and the Australian subcontract between undertake: (BoM), to of Meteorology Bureau synergistic collaboration draws This three-year strategic goals of Fujitsu and NCI; on the shared expertise in high-performance computing Fujitsu’s expertise and computational science; and NCI’s and in the application of high-end computing and data-intensive services to the rich research development portfolios of our collaborators. ” ARC Centre of Excellence of Excellence ARC Centre for Climate System Science Climate System for Professor Andrew Pitman, Director, Pitman, Director, Andrew Professor The technical developments led developments The technical environments provided by NCI. by provided environments “ by the ARC Centre of Excellence for for ARC Centre of Excellence the by

high performance and data computing Climate System Science depend on the Science System Climate

NCI is addressing this challenge by providing by providing this challenge NCI is addressing that drive innovation: the expertise and services optimisation of software the development and for simulation and data-intensive computation, along with sophisticated data services, data management, and visualisation services. The challenges that confront the future use of the future The challenges that confront not so globally relate high-performance computing increasing vendors to provide much to the ability of but the ability of researchers computational power, effectively. to utilise these systems The strength of an e-infrastructure capability capability e-infrastructure of an The strength – skills, much on soft infrastructure depends as hardware. etc. – as it does on software, High-Performance Computation High-Performance Innovation

8 1 Annual ReportReport 2014/15 1111 ” The NCI team and BoM experts and BoM experts The NCI team “ have collaborated very effectively very collaborated effectively have Development Branch, Bureau of Meteorology of Bureau Branch, Development Earth System Modelling Program, Research and Research Earth Modelling Program, System Dr Michael Naughton, Senior Research Scientist, Scientist, Senior Research Naughton, Dr Michael together to realise these improvements. to together 20% Fujin, NCI’s Fujitsu FX10 cluster. NCI’s Fujin, Geophysical Fluid from 2,000 to from National Oceanic for the 0.25°-resolution for the 0.25°-resolution — allowing use of more than a third a third than — allowing use of more Furthermore, the project has yielded a the project Furthermore, 7.5-fold reduction in computation (wall clock) 7.5-fold reduction NOAA GFDL’s Modular Ocean Model for ocean Model Modular Ocean GFDL’s NOAA modelling Innovations Team Development and The NCI HPC of ARC Centre with the has been collaborating Science to implement for Climate System Excellence Ocean Model (MOM) on Raijin. Modular NOAA’s of MOM, the iteration to the previous Compared a resolution represents model 0.1°-resolution current than more fold and requires enhancement of 2.5 power per time computation 6 times greater the model’s improve to step. A substantial effort for its practical required scalability was therefore in upscaling utilisation, resulting 20,000 cores within a single run — as well as total cores of Raijin’s a time. in CPU hours reduction of land the introduction version of the model through masking. The maintainers of MOM, the and Atmospheric Administration have now veriﬁed the NCI Dynamics Laboratory, on changes and demonstrated similar improvements US computational systems. have also successfully ported MOM onto NCI staff which has a unique Fujin, our Fujitsu FX10 cluster, K with Japan’s shared architecture SPARC-based worldwide) Computer (the 4th fastest supercomputer Thisand is the only FX10 machine outside of Japan. resource work has opened up a new computational the globe. around to MOM researchers to link the to link the Coupled

in the overall OASIS coupler model OASIS coupler 40% improvement in overall UM performance for Numerical in overall UM performance for Numerical The Centre National de la Recherche la Recherche National de The Centre Scientifique’s together. other five models • This year, the NCI HPC Development and NCI HPC Development the This year, been working on optimising have Team Innovations models to and 4DVAR the individual UM, MOM performance enhancements bring about substantial expertise suite. The Team’s to the overall ACCESS of their fixes by adoption has been recognised the custodians of these by into the official releases major international models. Model (UM) for Unified The UK Met Office’s atmospheric modelling of the work so far has been One key achievement to the UM(v8.4) code, which a major improvement operational current has been adopted into BoM’s activities. a combination of better decomposition Through bottlenecks, and strategies, alleviating hardware BoM has MPI communication improvements, in an have resulted efforts that the team’s reported approximately for the performance of the ACCESS model used the Australian Parallel Suite daily weather forecast: Global (APSv2-G). latest The team have also been working on the for the next- (v10.2) in preparation UM release generation BoM operational model. The major outcome of this work has been an approximately 30% gain This was achieved through Prediction. Weather a major code change to the I/O design which a critical inefficiency in the UM design. This removes being reviewed design for I/O is currently improved by the UK Met Office for inclusion in the next of the UM (v10.4). release NCI is also assisting CSIRO to adopt the latest version of the UM so it can be used for the International Panel on Climate Change’s Phase 6 project Project Model Intercomparison (see page 15). (UM) for for data for sea-ice Modular Ocean (CABLE) for land– CICE model 4DVAR Model 4DVAR Unified Model Community Atmosphere Biosphere Biosphere Community Atmosphere (MOM) for ocean modelling The UK Met Office’s The UK Met Office’s assimilation The US Department of Energy Los Alamos National Laboratory’s modelling CSIRO’s Land Exchange model The UK Met Office’s Model surface modelling atmospheric modelling and Atmospheric The National Oceanic Geophysical Fluid Administration (NOAA) (GFDL)’s Dynamics Laboratory

• • • • •

The Australian Community Climate and Earth Community Climate The Australian is the (ACCESS) model System Simulator BoM uses daily to predict operational model that and climate conditions. This weather Australia’s essential information for vast model, which provides is a conglomeration of picnickers to policy-makers, six major international models: THE ACCESS OPTIMISATION PROJECT PROJECT OPTIMISATION ACCESS THE TOOLS AND SCALING ADVANCED THE AND PROJECT

10 1 Annual Report 2014/15 13 7348 ” 5792 Quarter 4391 3352 2014.q3 2014.q4 2015.q1 2015.q2 NCI National Research Data Collection NCI National Research ingest progress

NCI has driven our successful our successful NCI has driven Garvan Institute of Medical Research Institute Garvan 0 growth in our exploding ﬁeld. our exploding in growth “ 80 70 60 50 40 30 20 10

Professor Chris Goodnow, Deputy Director, Deputy Director, Chris Goodnow, Professor Making collections held by national agencies Making collections held by national agencies either accessible; these collections required high-performance computational or high- performance data services to unlock their potential Co-locating and integrating these collections with other nationally and internationally significant collections to enable research interdisciplinary Combining datasets held by research collections, and communities into coherent Integrating these collections within a rich of high-end computational and environment data-intensive services. (%,TB) rate Ingest Data allowed us to scale at the rate of data scale at the rate to us allowed providing access to high performanceaccess to providing data storage and computation that has and computation data storage Figure 2: Figure • • • • genome and exome informatics through informatics exome genome and DATA INGEST PROGRESS INGEST DATA collections were 10 PB of data Approximately at NCI as part of a formal selected for storage 2). This (see Table under the RDSI scheme process of lasting data holdings identified research process value and importance to the nation. The distinctive goals of the NCI Node were: Enable projects that are currently challenged by currently that are Enable projects layer and the the gap between the infrastructure outcomes ‘data science’ layer at which research realised are bridging the ‘human middleware’ Provide between compute and storage services operational support that remediates Provide existing service deficiencies, and which, can evolve to serve the requirements ultimately, high-impact collections. of future • • • High-Performance DataInnovation High-Performance and last 15 years, the requirements During the have investments of e-infrastructure expectations national supercomputing solely from expanded rich landscape the early years to the services in tightly integrated dataof today which includes of rapidly developing role services, driven by the in new research. data as a major player in the data collectionEnormous advances sequencers, telescopes andcapabilities of genome the requirement accelerated satellites have greatly strategies. Research for innovative data handling petascale data now facing communities are challenges. largest research As the home of Australia’s NCI is at the leading edge of data repository, developments of data ingest and management a truly high- techniques. Our aim is to provide performance data analysis capability. Data as a Service In 2011, the Australian Government initiated the $50 Data Storage Infrastructure million NCRIS Research to set up petascale data storage (RDSI) Project with storage located at six primary infrastructure, Australia. Of and two additional nodes throughout with 10 PB of has the largest capacity, these, NCI’s collections storage. Data Services As part of the follow-on Research established in 2014, NCI is (RDS) NCRIS Project into data as now focussing our RDSI infrastructure communities with a service, in support of research petascale data requirements. This data as a service delivery operation will: . reduced data reduced 40% improvement in overall in overall 40% improvement 30% performance (APSv2-G); in overall performance improvement (v10.2) 20,000 2,000 to Upscaling from in and 7.5-fold reduction cores computation time (0.1°-resolution in CPU hours version); 20% reduction version) (0.25°-resolution Reduced data assimilation time by in run up to 70%; 30% improvement time 30% improvement in performance 30% improvement

This last is of particular importance, as Fujitsu has exclusively chosen NCI to port this version for them. of the team will carry out porting Later this year, the new ﬂagship computer, Gaussian onto Fujitsu’s FX100. The team have also achieved a have also achieved The team

National Oceanic and National Oceanic and Atmospheric Administration Geophysical Fluid Dynamics Laboratory UK Met Ofﬁce Code enhancements achieved by NCI in 2014/15 Code enhancements

NCI’s work on the component parts of the ACCESS suite is already being work on the component parts of the NCI’s for activities from This has implications daily operations. implemented in BoM’s HPY[YHMÄJJVU[YVS[VUH[\YHSKPZHZ[LYWYLWHYH[PVU and implementing their next-generation Further work will assist BoM in designing which will be world-leading in simulation suites, climate higher-resolution complexity and resolution.

Unified Model UK Met Office Modular Ocean Model Model for data 4DVAR assimilation Model Maintainer NCI enhancements COMPUTATIONAL CHEMISTRY COMPUTATIONAL NCI have been working with BoM operators to address keenly sought improvements in the ACCESS in sought improvements keenly operators to address working with BoM NCI have been has the adoption of hyper-threading this end, To performance. data assimilation model’s The UK Met Office’s 4DVAR Model for data assimilation assimilation for data Model 4DVAR Met Office’s The UK assimilation time by up to 70%. assimilation These improvements have allowed BoM to exceed its operational goals in time-to-solution and hyper- and goals in time-to-solution BoM to exceed its operational have allowed These improvements to all NCI users. is now available threading Table 1: Table For more than 20 years, NCI (and its predecessors) than 20 years, NCI (and its predecessors) For more has been collaborating with Fujitsu to ensure programs key computational chemistry software FX10 and efficiently on Fujitsu’s operate effectively act as intermediaries between NCI staff hardware. computational developers and Fujitsu’s the software chemist market, testing, debugging and optimising Amber, including ADF, programs software industry standard and the current GAMESS, VASP, in computational chemistry – Gaussian.

12 1 Annual Report 2014/15 15 Standardise data formats Standardise (i.e., not Expose all data attributes for search just collection-level or dataset-level search functions) Make all metadata open and discoverable and NCI, ANDS, FIND, data.gov.au through partner data portals (e.g., TERN, IMOS, GA) Enable unique and persistent identifiers for and versioning provenance interfaces that link programmatic Provide to enable the data to compute resources and analyses. sophisticated searching Using NCI’s next generation, next generation, Using NCI’s site-wide high-performance WHYHSSLSÄSLZ`Z[LTZ[OL5H[PVUHS Data Research Environmental from both will be accessible Collection unprecedented at an Tenjin Raijin and 140 GB/sec. • • • • • Data Management of large datasetsThe generation and ingestion and organised in a structured must be undertaken can be easily accessed, the data manner to ensure and analysed. shared searched, of innovative data NCI is at the forefront many Historically, management processes. as disparate, national datasets have been provided not data collections that are heterogeneous formatted to a common grid or data format then often specification. The same data are science domains using an for different reformatted NCI aims to draw together approach. uncoordinated uses of the data, and harmonise and these different simplify their generation. the NCI Data Management Team Over the past year, to: have been working with collection custodians High-speed data transfer High-speed Performance new High NCI’s In early 2015 +H[H;LHTHUK[OL:[VYHNLHUK0UMYHZ[Y\J[\YL data to improve implemented a system Team datasets. for very large ingest speeds )HZLKVU[OL<:+LWHY[TLU[VM,ULYN`»Z :JPLUJL+4ATVKLS[OL;LHTZPUZ[HSSLK nodes that sit as dedicated data transfer connection router NCI’s close as possible to [V[OL(\Z[YHSPHU(JHKLTPJHUK9LZLHYJO 5L[^VYR((95L[ ;OPZZL[\WLSPTPUH[LZJ\TILYZVTLÄYL^HSSZ in has led to increases and checkpoints and KH[H[YHUZMLYZWLLKZVM\W[V has also participated in the The Team International Climate Network Working deploy and tune the University to Group VM*OPJHNV»Z.SVI\Z6USPULZLY]PJL[V reducing automate the transfer process, system human involvement and increasing robustness. NCI Since the new system was implemented, has ingested 1.5 PB of the Coupled Model 0U[LYJVTWHYPZVU7YVQLJ[*407KH[HZL[ MYVT[OL3H^YLUJL3P]LYTVYL5H[PVUHS 3HIVYH[VY`PU[OL<:(H[ZWLLKZÔPJO capacity can consume almost the entire network Transport of the Southern Cross JVUULJ[PVUHJYVZZ[OL7HJPÄJ ;OPZJHWHIPSP[`WH]LZ[OL^H`MVY[OLUL_[ generation of CMIP data, which is anticipated [VILPUL_JLZZVM7)HUK^PSS\UKLYWPU [OLUL_[THQVYHJ[P]P[PLZPUPU[LYUH[PVUHS climate research. Portals Discovery Tools Search Earth system science, climate and weather science, climate Earth system and models observations • marine observations • Earth and models observations and • Geoscientific observations, and ecosystems • Terrestrial observations. and hydrology • Water Collection (NERDC), which covers five fields: covers five which (NERDC), Collection the National NERDIP, NCI have created Data Interoperability Research Environmental standards-based a unifying, Platform, to provide for can access that researchers infrastructure assets Having the data research. interdisciplinary computing co-located with the high-performance the use of through facility at NCI, and harmonised from means researchers international standards, government, academe and industry now have a platform on which they can trial new mechanisms for high-performance data analysis and modelling on a national, if not global, scale. standards, provenance standards, Data storage infrastructure Interdisciplinary metadata and data formats, metadata Interdisciplinary Virtual Laboratories Web and high Web access services performance data NCI’s National Environmental Research Data Interoperability Platform Data Interoperability Research National Environmental NCI’s

NCI’s National NCI’s Environmental Data Research Interoperability Platform Government, Government, academia and industry communities Figure 3: Figure Once ingest is complete, NCI will be home to Once ingest is complete, NCI will be home 10 PB of nationally and internationally than more will signiﬁcant datasets. The majority of this data Data Research form the National Environmental As a result, NCI’s RDSI-supported data storage RDSI-supported NCI’s As a result, full. All of this data has than 70% allocation is more for both primary andbeen made fully accessible access on the NCI for direct secondary use: either needing high performance ﬁlesystems for those services or via online data compute resources, In community. research for access by the broader is harvested by Research addition, all metadata discoverable broadly more Data Australia, to be international harvesters and discovery through mechanisms, including Google. Over the past year, the NCI Data Management Data Management the NCI the past year, Over ingestion of an impressive has overseen the Team the total data, bringing RDSI-approved 5 PB of this ingest rate of more an average weekly to 7 PB. At and largest this is both the fastest than 100 TB, nodes. among the eight RDSI data ingest

14 1 Annual Report 2014/15 17 LSP]L[OPZZLY]PJL^PSSWYV]PKL L [OL9LZLHYJO+H[H:LY]PJLZ KH[H[YHUZMLYYH[LZYHUNLMYVT )YP[PZO([TVZWOLYPJ+H[H*LU[LY ,HY[O:`Z[LT*\YH[VY .LVWO`ZPJHS-S\PK+`UHTPJZ3HIVYH[VY` .LYTHU*SPTH[L*VTW\[PUN*LU[YL

DOI minting Data services PUBLISHED DATA COLLECTIONS

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S c SERVICES RESEARCH DATA Data Services The newly formed NCI Research has been working to deliver NCI-hosted Team NCI the THREDDS Data Server. datasets through THREDDS, hosts most datasets through currently but also supports Hyrax, ERDDAP and Geoserver. build several will the Team Over the coming year, a tool other service tools for data users, including that allows NCI-hosted datasets to be displayed, and analysed via a web browser. searched

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DISPARATE DATA DATA DISPARATE COLLECTIONS Government agencies Universities Research institutes In late 2014, NCI delivered an online Data In late 2014, NCI delivered portal. As well as providing Tool Management Web data custodians with access to their Data also provides Tool Management Plan, the Web Digital Objective Identifier (DOI) minting and services. These deliverables metadata creation management minimise the workload for record the NCI GeoNetwork and data publishing through major milestones funded by The catalogue, and are Australian National Data Service. DATA MANAGEMENT WEB TOOL WEB MANAGEMENT DATA Data Management Plans record all the information Data Management Plans record each to organise, publish and share required key collection, including workflows, procedures, metadata and areas, contacts and responsibility been licencing information. The Plans’ fields have export to the ISO19115 mapped for straightforward GeoNetwork catalogue schema and NCI’s infrastructure. DATA MANAGEMENT PLANS MANAGEMENT DATA has developed The NCI Data Management Team Data and implemented comprehensive data Management Plans, working closely with of each custodians to maximise the potential utility collection. Figure 4: Figure

16 1 Annual Report 2014/15 19 Ingest as at 30 June 2015 (TB) size (TB) ANUBoMGA 4 IMOSGA, 4 1486 1413 175 7 7 7 GA UNSWANU, ARCCSS CSIRO, BoM, 3 30 2750ARCCSS 2300 15 1 BoM 166 ARCCSSBoM, 166 5 IMOSGA, 2 4 2 113 29 2,500 social sciences datasets from a wide variety of government and non-government organisations academic, Australia and globally. in Australasian earth observation data30 years of generated by the Landsat satellites. available onshore The most comprehensive publicly seismic, gamma-ray, Australian airborne magnetic, electromagnetic and gravity measurements. Archive of seabed video and stills collected on 21 marine from off surveys between 2007 and 2013 (including Antarctica). This collection includes ACCESS NWP data, MTSAT MTSAT ACCESS NWP data, This collection includes satellite data and radar data. Initial spin-up simulations from the new high (ocean) ACCESS of resolution coupled version Meteorological weather analysis and forecast model ACCESS Prediction System output from NMOC using the daily weathersince 2009; represents BoM's predictions. all the datasets and produced This collection includes ARC Centre of Excellence for Climate published by the System Science (ARCCSS) during its existence (2011- of datasets which are part of with the exclusion 2018), cooperation projects (for example CMIP5 experiments). Products Atmospheric Forcing Atmospheric reanalysis and observation data from local Australian and international sources such as NCEP1, ERA40c and gridded observation data ERA40, sets NCEP2, research. for weather and climate AWAP such as Australian landforms and seabed topography and second Shuttle 3 and 9 the 1, elevation data including datasets and derived Mission (SRTM) Topographic Radar products and Laser Inferometry Detection and Ranging (LIDAR) data. The NCI National Research Data Collection Data Research NCI National The Australian Data Archive (Social Sciences) Australian Earth Observation Data (Landsat) Australian Geophysical Data Collection Australian Marine and Imagery Video Collection Dataset Name Dataset Name Description3D Geological Models of Australia ACCESS-CM 0.25 Degree Simulations ACCESS Numerical Prediction Weather Models ARC Centre of OrganisationExcellence for Climate System Science Datasets Collection Atmospheric Forcing Dataset Products Atmospheric Re-analysis Products Australian Bathymetry and Reference Elevation Dataset Explore the NCI Catalogue at nci.org.au/data-collections Table 2: Table ”

We use data to… inform agricultural use data to… We ¸>LJHUUV^TLHZ\YL[OPUNZH[HJVTWSL[LS`KPɈLYLU[ Globally than we could before. and volume resolution of been the problem has there in agricultural science KLHSPUN^P[O[OPZKLS\NLVMKH[H¹ZH`Z+Y;H`SVY very closely with will allow me to work “The Precinct and look similar problems, people at ANU who have foundation of solutions on the to develop shared computing with its strong the fantastic NCI facility abilities.” 5*0»Z]PY[\HSLU]PYVUTLU[^PSSHSSV^+Y;H`SVYHUKOLY across collaborators from team to work closely with the country and the globe. about working with been challenging “What’s V[OLYZJPLU[PZ[ZPZ[OH[^LVM[LUSP]LPUKPɈLYLU[ JVTW\[H[PVUHSZ`Z[LTZ^L\ZLKPɈLYLU[HUHS`[PJHS [VVSZHUKP[»ZILLUX\P[LJOHSSLUNPUN[VÄUK^H`Z[V data. work together and share going to “In getting this system up, what we are incorporate into it is essentially a series of virtual we can come together ‘laboratories’ where or ‘rooms’ more our problems easily and share much more LɉJPLU[S`[OHU^LOH]LILLUHISL[VILMVYL¹ “ the globe respond to food security food issues. the globe respond to producers how best to… help the nation and producers best to… how

RESEARCH HIGHLIGHT RESEARCH

New agricultural precinct supported by NCI supported precinct New agricultural 0U+LJLTILY4PUPZ[LYMVY0UK\Z[Y`[OL/VU of announced the partnership MP, Ian Macfarlane (5<*:096HUK5*0PU[OLUL^(NYPJ\S[\YHSHUK Sciences Precinct. Environmental brightest minds will bring together the The Precinct MYVT*:096HUK(5<^P[OZ\WWVY[MYVT5*0[VMVZ[LY security and and innovation essential to food research challenges. environmental *:096YLZLHYJOLY+Y1LU;H`SVYZH`Z[OLWHY[ULYZOPW between the three will enable collaboration VYNHUPZH[PVUZVUSHYNLWYVQLJ[ZZ\JOHZZLX\LUJPUN most important the globe’s the genome of one of wheat. crops, in how we deal with data around “I’m interested and ecosystems more productive more making crops Z\Z[HPUHISL¹ZH`Z+Y;H`SVY data to understand how those plant systems use “We work and that translates into informing agricultural how best to utilise the systems that they producers to helphave on hand and how to adopt new solutions to food security the nation and the globe respond issues.” willThe Science and Industry Endowment Fund which million to support the program, $18 provide and data facilities includes access to supercomputing by $1M capacity at NCI, and which will augment NCI’s memory compute nodes. of new large

18 1 Annual Report 2014/15 21 Ingest Ingest as at 30 June 2015 (TB) size (TB) ARCCSS TERN, CSIROANU, 27CSIRO 12 27 1 BoM 10 2 366 232 BoM GA BoM, CSIRO, 2GA 44 2 18 ANU BoMCSIRO, 22 16 CSIROBoM, 205 4 171 CSIRO 2 70 6 150 70 Output from the high-resolution global Japanese Ocean the Earth Simulator (OFES); 30-year time series model For on 3-day temporal resolution. and seasonal variation in Phenocam images of cyclic biological systems. High-resolution plant growth imaging data. and ocean dataWeather from NMOC; represents BoM's daily observations analysis. model and climate Collection of meteorological data from the High Altitude dataCollection of meteorological from the High (HIWC) field Content Water Ice Crystal / High Ice (HAIC) Darwin area in the period campaign conducted in the January 2014. - March Draft Report Rainfall and Murray Darling Basin Plan Resources Water Australian Runoff data; output from the Assessment system Landscape model of catchment Assessment data. systems; Bioregional ObservationsWater Space sub-project from Data from the which of the National project, Flood Risk Information Portal has systematically Landsat analysed every pixel cloud-free observed 1998 and 2012. between ANU x-ray data since 2001 at acquired the Tomographic rock cores, images of fossils, micro-CT facility including notably insects grain packings and biological specimens, and human and animal bone. National Resource Management data (post-processed CMIP5) Ocean circulation wave and marine analysis and tsunami including forecast model output from NMOC, wave propagation model output; represents BoM's daily forecasting. Australian Model) experiment (Ocean Forecasting An OFAM with a 10-km simulating near-global, 1993 to 2012 of resolution (eddy-resolving) ocean general circulation model coupled with biogeochemistry. Ocean Forecasting Australia Model Ocean Model for the Earth Simulator Re-analysis Datasets Phenology Monitoring: Near Remote Surface Sensing Plant Phenomics Digital Data Repository Remote and In- situ Observations Products for Earth System Modelling Dataset Name Dataset DescriptionHigh Altitude Ice CrystalsIce - High Content Water Assets Key Water Models of Land and Organisation Dynamics Water from Space Data Collection National CT-Lab Data Dataset Tomographic Collection National Resource Management data Ocean and Marine Modelling and Forecast Products Ingest Ingest as at 30 June 2015 (TB) size (TB) GA 6 4 UNSW BoM CSIRO, NCI, 57CSIRO 2400 1488 1 ANU, CSIROGA, 2 MUTERN eMAST, 74 1 74 90 25 CSIROGA 435ANU 286 ARCCSS, UNSWCSIRO, 27 3 24 186 3 186 Archive of Global Navigation Satellite System data from including hundreds of GNSS sites throughout the world, the Global Navigation System, the Global Positioning Galileo and Quazi Zenith Satellite BeiDou, Satellite System, System. More than 11,000 film negatives, derivative contract prints More than 11,000 film negatives, Antarctic landscape Australian and and diapositives of the captured c.1928-1993. TERN facilities Data from a variety of sources including and OzFlux for the MSPN, Eco-Informatics, AusCover, testing of ecosystem models. Climate modelling data from the World Climate Research World Climate modelling data from the Programme. Collection of eReefs Hydrodynamic data model products. output from They include various coastal modelling data. hydrodynamics time and hindcast models of as near-real well as ecological and sediment processes. Output from the World Climate Research Programme’s Climate Research Programme’s World Output from the international project to downscale CMIP5 Global Climate Models with Regional Climate Models. Whole-genome sequences from 130+ melanoma patients.Whole-genome sequences Global datasets of the CABLE land surface for comparison model against observational CABLE is part of the data. Australian Community Climate Earth Systems Science ACCESS model. Earth observation data generated and NOAA by NASA satellites. impact and risk Observational and probabilistic hazard, floods and tropical tsunami, data covering earthquakes, cyclones.

Global Navigation Satellite System (Geodesy) Data Archive Ecosystem Modelling and Scaling Infrastructure (eMAST) Data Facility Digitised Australian Aerial Survey Photography Collection CSIRO Coastal Modelling Products Coupled Model Intercomparison Project (CMIP5) CORDEX Australasia Community Atmosphere Biosphere Land Exchange (CABLE) Model Collection Australian Natural Hazards Data Archive Bioplatforms Australia Melanoma Collection Dataset Name Dataset Description Organisation Dataset Australian Moderate Resolution Satellite Products (NOAA/ VIIRS MODIS, AVHRR, and AusCover)

20 1 Annual Report 2014/15 23 80 97 4310 47964 17162 3578 NCI also provided support to the Geoscience the Geoscience support to provided NCI also from Observations ‘Water Australia project Flood Risk part of the National Space’ (WOfS), a set deployed The NCI Team Project. Information Australia to enable Geoscience of data services satellite imagery access decades of to effectively surface water across to show the history of emergency providing the nation since 1987, understanding of potential managers with a new for won the award ﬂood impacts. The project work in the governmentnationally signiﬁcant Resilient Australia Awards. category of the 2014 (NERDIP; new data platform As part of NCI’s the data provide see page 14), the Team Geospatial Consortium services using Open that protocols (OGC) standards-compliant the data to the WOfS portal hosted at provide services Geoscience Australia. By deploying data community which comply with the relevant enabling we are standards, interoperability to easily utilise internationally researchers available tools and software. 23 5031 15107 18 2014 2015 2014 2015 2014 2015 2014 2015 2014 2015 Videos uploaded Minutes watched Views Subscribers Drishti software downloads

Figure 5: Figure Drishti YouTube channel statistics This year the NCI Digital Laboratories Team have Laboratories Team This year the NCI Digital developed a new ‘Virtual Desktop Infrastructure’ The VDI substantially simplifies (VDI) technology. complicated analysis workflows that span key multiple NCI systems by bringing together and compute data collections, analysis software, unified environment systems within a familiar, their own which users can access as though from So far the VDI has been deployed to computer. and Science Laboratory, the Climate and Weather such is due to be expanded for other applications, and as the Australian Geosciences Data Cube later this year. genomics research, Ingest Ingest as at 30 June 2015 (TB) size (TB) Total 10344 7485 TERN eMASTBoM 110ARCCSS 10 200 84 160 84 CSIRO, TERN TERN CSIRO, eMAST 6BoM 2 BoMANU 595 435 GA 50 25 227 172 118 31 • Climate & Weather Science Laboratory • Climate & Weather and • All Sky Virtual Observatory, • Virtual Geophysics Laboratory. We currently support the Australian Government currently We NeCTAR-funded: have also been instrumental in the We establishment of the Australian Geosciences Data Cube in partnership with Geoscience Australia and CSIRO. Tropical Cyclone Scenarios Cyclone Tropical modelling and forecasting dataCoordinated observing, monsoons and cyclones, including for tropical convection, over a one-year period. Assimilation of land surface observations, of collections comprising model system, pre-formatted for the DART-x inputs and outputs. Output from the SkyMapper telescope survey of the entire southern sky. Aperture Radar data covering 20 year archive of Synthetic Australian continent that can be used to observe cm- the scale ground motion and surface texture associated rock changes in vegetation or floods. type, Satellite-derived soil moisture products, from a range of Satellite-derived soil moisture products, years. spanning the last 20-30 data providers, analysis and climate Intra-seasonal and inter-seasonal ACCESS NMOC using the forecast model output from BoM's daily model runs and Prediction System; represents outlooks and hindcasts. climate output including NCI research data collection of NWP datasets arising from severe weather case studies undertaken at the Bureau of Meteorology

Year Of Tropical Of Tropical Year Convection Re- analysis Datasets Tropical Cyclone Cyclone Tropical Scenarios TERN eMAST Data Assimilation Synthetic Aperture Radar Data SkyMapper Southern Sky Survey Severe Weather Case Severe Weather Studies Seasonal Climate Prediction Data Collection Dataset Name Dataset Description Organisation Dataset Satellite Soil Moisture Products NCI is a world leader in the design and provision NCI is a world leader in the design and provision of digital laboratories, backed by our unique with integration of a 10 PB data repository and fastest first petaflop supercomputer Australia’s cloud. research Digital laboratories bring together in a single computing, for research place everything required including easy and fast access to vast data libraries and high performance computing and analysis and visualisation tools. resources, Digital Laboratories online interfaces tailor- Digital laboratories are data and services to suit specific made to provide fields. research

22 1 Annual Report 2014/15 25 further analysis. The new version of Drishti also Drishti also version of The new analysis. further mesh of watertight surface creation allows the for 3D which can be used for these structures, printing. Drishti the interactive of production, In its ﬁrst year Prayog, has tool, Drishti dataset presentation use regular in It is already been well received. and Manchester at the Diamond Synchrotron Kingdom. In March, in the United University, held a Biology in Crete The Institute of Marine of marine creatures, Drishti Prayog exhibition earnedand the new technology attention at the Day at The University Developers Touchscreen Prayog was also on of Reading, UK. Drishti in Conference Technology display at the Emerging UK, in June. Manchester, Credit Dan Sykes, NHM Credit Dan Sykes, including at London’s Natural History Museum, History Museum, Natural at London’s including objects and to explore researchers Drishti allows cutting them in minute detail without specimens 4,310 times in was downloaded open. Drishti 2014/15. funds from development Supported through past year Drishti has been in the NeCTAR, landmark-based enhanced with two updates: data and semi-automatic measurement segmentation. is a method used Landmark-based morphometrics and medical research extensively in palaeontology shape between biological for comparing size and involves adding digital specimens. The technique junctions in such as suture ‘landmarks’ to regions one bone touches another, mammal skulls, where and then or the peaks and valleys of eye sockets, measuring the distance between two landmarks. method to compare is a standardised The result samples. size and shape between different analysis Segmentation is a crucial ﬁrst step in the of volumetric data, whether it be medical, gas paleontological, material sciences or oil and data. Drishti now has a set of tools to semi- for automatically extract segments of interest

Drishti is a custom, open source software package software Drishti is a custom, open source scans.for visualising volumetric data such as CT Ajay Limaye Dr It was developed by NCI VizLab’s a decade ago. Used all over the world, than more DRISHTI AND DRISHTI PRAYOG DRISHTI AND DRISHTI PRAYOG 2014/15 has been a particularly productive year 2014/15 has been a particularly productive for the NCI VizLab, as demonstrated through in which the team has been the various projects involved. Today this team of specialist programmers works of specialist programmers this team Today partner NCI’s from closely with researchers them gain the greatest organisations to help it in clear and their data, and present insights from appealing ways. The value of scientiﬁc visualisation lies not of scientiﬁc visualisation The value but pictures, data into pretty in transforming and visualisation as a research in exploiting deeper which to gain tool through investigation than 20 datasets. For more insight into complex years, NCI VizLab a respected has developed in innovating and for its expertise reputation applying these techniques. Scientific VisualisationScientific

24 1 VOLUMINOUS produced by the newly established National CTLab, Oceanography velocity and density. The data is subsampled for based at ANU. The system will become the portal prototyping, before the generation of iso-surface In 2014, the VizLab team completed development VizLab has continued working with Dr Andy for CTLab users to view and download their data geometry and rendering using Houdini volume 1 work on the NeCTAR-funded, web-based volume Hogg and his team at ANU to visualise a 1/10th as soon as it has been reconstructed using NCI’s tools. The result is stunning animations of the rendering program, Voluminous, which runs on the degree model of the global ocean, which is run on Raijin supercomputer. global ocean system, revealing the hidden current NCI cloud and exploits GPU technology. Already Raijin and made possible through NCI’s ACCESS structures beneath the surface. more than 40 users have uploaded 66 datasets for SPECIALIST SERVICES scaling activity. The project is a complex one, with visualisation. more than 4,000 time steps, each at a resolution VIDEO: bit.ly/VizLab_Hogg The VizLab team are experts in applying of 3,600 x 2,700 x 50 with four separate ﬁelds: Voluminous is currently being enhanced to visualisation as a research and investigation tool to water temperature, salt concentration, current support the rendering and archive of MicroCT data gain deeper insight into complex datasets. Annual Report 2014/15

“WorkingWoWorkrkinng withwiwithh thethee NCINCCII VizLabVizzLaab teamteteamm hashaass eenenablednabableled mme ttoo ddidiscoversccovere resultsresuultst fromfroom mymy modelsmmoomodelsdedelsls tthathah thatt wouldwwoo woulduld otherwiseototheh otherwiserwrwisse havehah vvehave beenbee e n beenobscured.obob scsobscured.curureded. AssociateAAsssosociciaatte PPrProfessorroffese sosor AAnAndydy HoHHogg,ogggg”, ARAARCRC FutureFuututure FFeFellowllowow Associate Professor Andy Hogg,” ARC Future aanandnd ARCARARC CentreCeC nttrere ofof ExcellenceExE ceelllleenncce forfoor Fellow and ARC Centre of Excellence for CClClimatelimimatate SystemSySyststeemm ScSScience,cieencncee, AANANUNU Climate System Science, ANU

A still image from the VizLab’s simulation of Andy’s Hogg’s Southern Ocean research. 26 27 Meteorology Ecology

This year, VizLab has started a project with the Another exciting project, supporting the work of 1 Australian Bureau of Meteorology to develop Dr Tim Brown at ANU, involves visualising tree methods for visualising the data produced by the growth at the National Arboretum in Canberra. The ACCESS weather forecasting model [see page aim is to use LIDAR (or ‘light radar’), time lapse 10]. As a pilot project, data from a forecast of photography, and environmental and meteorological Cyclone Christine, which hit Western Australia data to create a digital laboratory that presents the on New Year’s Eve 2013, is being used as a test Arboretum’s development over the next decade. case with promising results. The plan is to develop The project will help researchers understand how workﬂows that allow for the automated production weather and climate variability affect tree growth. of high-quality visualisations after each new regional forecast as it is generated on BoM’s production systems. Visualisation of these vast datasets will provide greater insight for policy makers and public safety organisations than can numbers on a page.

Mathematics

Another ongoing VizLab project is the population of the EPINET (Euclidean Patterns in Non-Euclidean Tilings) database. In collaboration with Professor Stephen Hyde and Dr Vanessa Robins at ANU, VizLab is generating visual models of thousands of Digital representation of trees at the National Arboretum. crystallographic structures, to be made available as a large online database for chemists, physicists and mathematicians.

Visualisation of a simulation of Severe Tropical Cyclone Christine as it approached the Pilbara coast on 30 Dec 2013. The simulation was made using a research version of the Bureau of Meteorology’s ACCESS numerical weather prediction system. Green colours indicate clouds consisting of ice particles, while the white clouds consist of water droplets. The vertical shafts are rain, and the coloured line segments indicate the Our Users near-surface wind direction.

28 29 Annual Report 2014/15 31 ”

chemotherapy. The discovery has already spurred HJJLW[TP_[\YLZHUKKL]LSVWKL]PJLZ^P[OSHYNLY fault tolerances. at a molecular level how imperfections “By predicting with we can design products impact on performance, the outset.” from less susceptibility to faults (ZPUNSLWYLKPJ[PVUMVYQ\Z[VULZ\IZ[HUJLYLX\PYLZ – and each of individual calculations hundreds of computer memory. gigabytes requires structure 6US`[OL5*0Z\WLYJVTW\[LYJHUOHUKSLZ\JO[HZRZ ^P[OPUHYLHZVUHISL[PTLZH`Z+Y)HYUHYK +Y)HYUHYK^HZHSZV[OLYLJPWPLU[VM[OL7YPTL the Physical Sciences in 2009. Prize for Minister’s the development of a brain tumour the development “ Amanda Barnard. Amanda Barnard. RESEARCH HIGHLIGHT RESEARCH Top prize for NCI user prize Top 5*0Z\WWVY[LKYLZLHYJOLY(THUKH)HYUHYK^HZ Institute Feynman Foresight the prestigious awarded Prize in May 2015. +Y)HYUHYKPZIV[O[OLÄYZ[(\Z[YHSPHUHUK[OLÄYZ[ the award. woman to receive and computational theoretical “Using entirely TL[OVKZ+Y)HYUHYKOHZZWLHYOLHKLK stability of and understanding of the structure the Foresight announced carbon nanostructures,” Institute. important numerous “Although she has made of graphene, contributions to the modelling it is her work nanotubes, and diamond nanowires, greatest on diamond nanoparticles that has had the of molecular nanotechnology.” impact in the area

+ In 2014/15 NCI provided support to 555 projects projects support to 555 NCI provided In 2014/15 Of the users. research than 2,000 and more Scheme Merit Allocation National Computational NCI supports (see that university-based projects funded by the ARC 85% are than 4), more Table at least one 89% received and/or NHMRC and 191 NCI grant. A total of competitive research the from supported by $43 million are projects Industry of Excellence, Centres ARC through Fellowships and Project Hubs, Transformation Grants. 2,000 USERS 1 Nobel Prize winner 31 universities Hub 1 grants ARC Industry Transformation Transformation projects projects $43M ARC supported by 190+ Our users

Figure 6: Figure

We cater for the full research spectrum, from from spectrum, cater for the full research We to applied, strategic andfundamental investigation integrated provide We industry-driven research. of the to three compute and data services government science agencies – CSIRO, nation’s of the Australian Bureau Geoscience Australia, Australian at 31 – as well researchers Meteorology Council Research universities, ﬁve Australian an ARC Industry of Excellence, (ARC) Centres our industry partners. Hub, and Transformation Our Users Our and goals of our users by the research NCI is driven partner organisations.

30 2 Annual Report 2014/15 33 98 373 400 400 9282 8742 8377 8377 7540 6764 9190 2572 2941 1935 1340 88731 12600 89016 87349 20367 15424 110367 492186 see above (kSU) The Australian National University The Wales University of New South Monash University Adelaide University of University of Queensland University of Sydney RMIT University commercial projects) Developmental Share (incl. To t a l Stakeholder Excellence for ClimateARC Centre of System Science Astrophysics All-sky ARC Centre of Excellence for Astronomy Australia (NCRIS) BioPhotonics ARC Centre for Nanoscale GeodynamicsARC Research Hub for Basin of Sedimentary and Evolution Systems Ecosystem Research Network (NCRIS) Terrestrial CSIRO Australian Bureau of Meteorology Australian National University The Intersect Australia* allocation Total Geoscience Australia Deakin University QCIF Antarctic Climate Cooperative & Ecosystems Research Centre / Australian Antarctic Division

Compute allocation proﬁle for 2014/15 proﬁle allocation Compute

Flagship National Computational Merit Allocation Scheme National Computational Merit Universities supported by an ARC LIEF Grant Collaborators PARTNER SHARE MERIT ALLOCATION MERIT SHARE PARTNER

*Supported by an ARC LIEF Subscription Grant *Supported by an Table 3: Table ” Dr Lexing Xie, ANU Dr Lexing ” Flagship Scheme Flagship a number supports Scheme currently The Flagship in climate Excellence—notably of of ARC Centres ARC and photonics, astrophysics, system science, various NCRIS Hubs, and Industry Transformation sciences the environmental capabilities, notably in and astronomy. PARTNER SHARES PARTNER provided are HPC resources The majority of NCI’s a contracts. If you represent partnership through company or institution that would like to university, work with NCI, please contact [email protected] DEVELOPMENT SHARE to drive industry is used The development share innovation and industry, uptake, in line with the being pursued by the competitiveness agenda Australian Government. It is also used by NCI model, and its service, to evolve its business of universities and and impact into the work reach government agencies.

Associate Professor Jason Sharples, UNSW Jason Professor Associate We’re very grateful to have a resource like NCI. a resource like have very to grateful We’re large data sets. If we didn’t have access to NCI we wouldn’t even attempt it. attempt even wouldn’t NCI we access to have didn’t large data sets. If we

If we didn’t have the NCI facilities it could take almost a year just to process our data. process just to almost a year the NCI facilities it could take have didn’t If we Our bushﬁre simulations are extremely computationally demanding and generate very generate demanding and computationally Our bushﬁre simulations are extremely “ ncmas.nci.org.au

MERIT-BASED MERIT-BASED NCMAS the National support for secretariat NCI provides Allocation Scheme (NCMAS). Computational Merit open access scheme through This is the principal, research at publicly funded which researchers and governmentorganisations (i.e., universities, computational allocated instrumentalities) are ﬁve high-performance on the country’s resources In merit. on research computing platforms the NCMAS acts as the ‘computational effect, complement’ to the granting schemes of council, operating with the national research ARC assessment criteria equivalent to that of the through and NH&MRC, and determining allocations an independent, expert panel. of the the largest share For 2015, NCI provided nominally 75 million hours (15% NCMAS resources, by of the facility), with demand exceeding supply role a factor of 2.7. This demonstrates the critical of high-performance computing in maintaining the international standing of Australian research, particularly in the university sector. See NCI services can be accessed through a number of through can be accessed NCI services schemes: Access Schemes Access

“

32 2 Annual Report 2014/15 35

4% Sciences Biological Professor Martin Asplund. Photo by Stuart Hay. Asplund. Professor Martin

13% Technology Engineering &

21% Sciences Chemical Compute allocation of NCMAS projects on Raijin by research ﬁeld ﬁeld research Raijin by on projects of NCMAS allocation Compute

23% Physical Sciences Figure 7: Figure RESEARCH HIGHLIGHT 39% NCI researchers awarded AAS Fellowships NCI researchers awarded -V\Y5*0Z\WWVY[LKYLZLHYJOLYZ^LYLHUUV\UJLK in as Fellows of the Australian Academy of Science 2015. Martin Asplund and Earth Professor Astronomer ANU, Malcolm Sambridge from Scientist Professor Maria along with Materials Scientist Professor -VYZ`[OMYVT+LHRPU

UNSW@ADFA Total University Australia of Western Wollongong University of University of Technology Sydney Technology University of University of the Sunshine Coast University of Sydney Tasmania University of University of Queensland Australia University of South University of New South Wales University of New South University of Newcastle University of Melbourne University of New England The Australian National University The Adelaide University of Queensland University of Technology Queensland University of RMIT University Murdoch University NICTA Macquarie University Monash University James Cook University University La Trobe Flinders University Griffith University Curtin University Deakin University Australian Antarctic Division CSIRO Institution kSU Total ANSTO Table 4: Table

34 2 Annual Report 2014/15 37 ” Totten Glacier, Paul Brown. Glacier, Totten YLZVS\[PVU¹ZH`Z+Y.HS[VU-LUaP of order an we required the stage where at were “We to our compared in CPU hours magnitude increase YLNPVUHSZJHSLTVKLSZ was to those resources “The best way to access partner.” become a formal NCI is to collaborate with NCI’s The end goal of the work L_WLY[JVKLVW[PTPZH[PVU[LHTBZLLWHNLD[V to an ice sheet model to couple the ocean model the ocean lead to at how changes in look directly changes in the ice sheet. ;OLWYVQLJ[PZHJVUZVY[P\TIL[^LLU[OL(\Z[YHSPHU (U[HYJ[PJ+P]PZPVU[OL(U[HYJ[PJ.H[L^H`7HY[ULYZOPW HUK(*,*9* on Earth, melting of the of ice reservoir As the largest implications for sheet could have severe ice Antarctic [OL^VYSK»ZTHQVYJP[PLZZH`Z+Y.HS[VU-LUaP of how the ice sheet will respond unsure really “We’re sea to climate changes and how much potential a big risk them. There’s level rise could come from [VJVHZ[HSPUMYHZ[Y\J[\YL^OLYL`V\OH]LL_WLUZP]L population lives. most of the world’s ports and where ¸6\YYLZLHYJOPZMVJ\ZLKVUNL[[PUNHU\WWLYIV\UK WYLKPJ[PVUVMZLHSL]LSYPZLMVY[OLUL_[O\UKYLKVY years.” two hundred

OUR NEW PARTNERS NEW OUR We were at the stage where we required an order of magnitude increase in CPU hours. required an order of magnitude at the stage where we were We RESEARCH HIGHLIGHT: RESEARCH Predicting sea level rise sea level Predicting NCI’s newest partners, the Antarctic Climate and Climate partners, the Antarctic newest NCI’s ,JVZ`Z[LTZ*VVWLYH[P]L9LZLHYJO*LU[YL(*, *9*[OYV\NO[OL

Date1/5/201415/7/20149/10/2014 Partner Deakin University Monash University26/2/2015 ANU2/3/2015 Garvan Institute for Medical Research3/3/201511/3/2015 9 UNSW/ARCCSS24/3/2015 ANU 13 University of Sydney/CAASTRO 1525/3/2015Australia Geoscience 10/4/2015 attendees No. Australia Introduction to NCI Geoscience 12/5/2015 Name of course 13 Monash University22/5/2015 Introduction to NCI Introduction to NCI ANU 18 2425/5/2015 UNSW29/6/2015 10 UNSW30/6/2015 Introduction to NCI 10 UQ30/6/2015 10 Introduction to NCI Introduction to NCI UQ 23 ANU/CSIRO Introduction to NCI Programming on Raijin and Parallel Performance Workshop Research Data Management Introduction to NCI 8 12 12 35 50 Introduction to NCI to NCI Introduction 15 Programming on Raijin and Parallel Performance Introduction to NCI Analytics and Big Data with MATLAB Predictive Programming on Raijin and Parallel Performance A key role of the NCI User Services Team is of the NCI User Services Team A key role and advanced, training, both introductory providing to NCI users and partners. 2014/15 the NCI User Services Throughout worked to enhance their suite of training Team intermediate a new, produced materials. The Team level training course, ‘Performance and Parallel TRAINING NEW SELF-SERVICE PORTAL PORTAL NEW SELF-SERVICE NCI User Services continued the year, Throughout registration work on a new self-service development pre-release which underwent system, Mancini, 2015. testing in April–June email-intensive old The new system replaces with a self- workﬂows and approval registration and users to register service model that allows exchanging without connections to projects request releases Future email with the NCI Helpdesk. Investigators and Scheme will allow Lead Chief of their projects more Administrators to manage online. my.nci.org.au/mancini User services Table 5: Table

36 2 Annual Report 2014/15 39 ”

6US`[OLYLJLU[YPZLPUOPNOWLYMVYTHUJL and software computing hardware type of basin capability has made this TVKLSSPUNWVZZPISLZH`Z+LW\[`/\I +PYLJ[VY(ZZVJPH[L7YVMLZZVY7H[YPJL9L` this we need to perform “The software only be run on highly type of modelling can systems,” he says. parallelised computing NCI comes in; without a where “That’s JVTW\[PUNWSH[MVYTSPRL9HPQPU^LJV\SKU»[ L_LJ\[L[OLZLTVKLSZ¹ As is the case for all the Industry Hubs, the Basin GENESIS Transformation /\IPZZL[\WZV[OL(9*M\UKPUNPZ balanced with industry contributions. “We are working directly with international working directly are “We and Statoil, as well as companies such as Chevron SVJHSJVTWHUPLZ+.,66PS:LHYJOHUK0U[YLWPK .LVWO`ZPJZ[VKLZPNUZWLJPÄJYLZLHYJOWYVNYHTZMVY [OLPYIHZPUZVMPU[LYLZ[¹7YVMLZZVY4 SSLYZH`Z 2L`MVJ\ZHYLHZHYL[OL5VY[O>LZ[ZOLSMVM(\Z[YHSPH resources, richest natural gas – one of the country’s 7HW\H5L^.\PULHHUK[OL([SHU[PJ6JLHU continental margins. the New The Hub has also attracted funding from the Sydney Government to research South Wales Basin. ¸;OL:`KUL`)HZPUPZHNVVKL_HTWSLVM^OLYL it provides because competing interests are there \Z^P[O^H[LYHZ^LSSHZLULYN`YLZV\YJLZ¹L_WSHPUZ 7YVMLZZVY3V\PZ4VYLZP^OVSLHKZ[OL4LSIV\YUL University node of the Hub. ¸;OPZJVTWSPJH[LZ[OLL_WSVYH[PVUHUKTHUHNLTLU[ calls for advanced integrated and of these resources, improved basin modelling solutions that provide insights into basin dynamics.” The software we need to perform need to we our The software research can only be run using highly can only research parallelised computing platforms like Raijin. like parallelised computing platforms “ RESEARCH HIGHLIGHT RESEARCH 4D earth modelling supported by industrysupported by modelling 4D earth 5*0PZ[OLWYV]PKLYVMOPNOWLYMVYTHUJLJVTW\[PUN YLZV\YJLZMVY[OL 4(9*9LZLHYJO/\IMVY)HZPU Systems Geodynamics and Evolution of Sedimentary (GENESIS). modelling The Basin GENESIS Hub will use computer [VÄUL[\ULV\Y\UKLYZ[HUKPUNVM[OLUH[PVU»Z natural sedimentary basins, which hold many of the YLZV\YJLZ^L\ZLPUKH`[VKH`SPML will be of fundamental importance to The research [OLNLVZVM[^HYLPUK\Z[Y`\ZLKI`L_WSVYH[PVUHUK TPUPUNJVTWHUPLZL_WSHPUZ/\I+PYLJ[VY7YVMLZZVY +PL[THY4 SSLYMYVT[OL

supercomputing facilities. The kind of modelling that we are The kind of modelling that we doing is just not possible without “ don’t have to spend time and materials recreating spend time and materials recreating have to don’t of possibilities,” says Professor gamut the entire Greentree. ¸>LHYL]LY`L_JP[LK[VOH]LHJJLZZ[V5*0ILJH\ZL [OLRPUKVMTVKLSSPUN^LHYLKVPUNPZQ\Z[UV[ facilities.” possible without supercomputing ;OLNYV\WPZHSZVSVVRPUNH[UL^[`WLZVMÅ\VYLZJLU[ IPVTHYRLYZ\JOHZUHUVKPHTVUKZHUKUHUVY\IPLZ signals. as well as ways to combine sound and light and detection also looking at the creation are “We very are of sound using light, which is something we L_JP[LKHIV\[¹L_WSHPUZ7YVMLZZVY.YLLU[YLL and the same physics — light “Conceptually it’s when but sound kind of behave the same way, `V\[Y`[VJVTIPULMVYL_HTWSL\S[YHZV\UK^P[O because of is a big problem nanoscale optics there is a huge mismatch between the speed course there of sound and the speed of light. to work very hard “That means that technically it’s going on; we need very sophisticated, out what’s very powerful computer simulations.” OUR NEW PARTNERS NEW OUR RESEARCH HIGHLIGHT: RESEARCH Shining new light on the body new light on Shining

38 2

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“Modifying all the parameters of the system using

L_WLYPTLU[HSKL]LSVWTLU[VM[OLZL\ZLM\SZ[Y\J[\YLZ

The team say NCI allows them to accelerate the

work.

biomolecules of interest to understand how cells biomolecules of interest

These sensors could be used to detect particular

signal.

of a microbubble, it causes a blip in the resonance it causes a blip in the resonance of a microbubble,

When something comes in contact with the surface When something comes in contact with the

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bounce around inside a few million times, allowing a bounce around

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Professor Greentree. Professor

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Whispering Gallery resonators provide a highly provide Whispering Gallery resonators

same thing, but with light instead of sound.”

Adelaide is designing sensor platforms that do the Adelaide is designing sensor platforms that

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Greentree. Greentree.

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the other side of the dome can hear you because the the other side of the dome can hear you because

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resonators.

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including ones that incorporate including ones that incorporate

modelling to design new devices, modelling to design new

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and medical diagnosis.

biosensors for use in research biosensors for use in research

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BioPhotonics (CNBP) are using are BioPhotonics (CNBP)

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much of it in an anaesthetic. of it in an much strength of the bond between the chemical between the chemical of the bond strength computer is where and the nanosheet, which fore. modelling comes to the ¸([[OLTVTLU[[OLL_HJ[UH[\YLVM[OL IPUKPUNVMZVTLZ\IZ[HUJLZHUK[OLPYLɈLJ[VU is of the nanosheet properties the electronic Bernhardt. still unknown,” says Professor and need to study a strong “There’s \UKLYZ[HUK[OPZPU[LYHJ[PVU[VKLZPNULɉJPLU[ nanosensors.” ;OLNYV\W»ZJ\YYLU[WYVQLJ[ZJV\SKUL]LYOH]L of been performed using the supercomputers Bernhardt. the past, says Professor “Back in the 90s, I was working on small alkali only found metal cations,” she says. “They’re PUL_[YLTLZP[\H[PVUZZ\JOHZM\ZPVUYLHJ[VYZVY lasers, but we looked at them partly because small enough that we could actually they were perform the necessary calculations. working “Now my students and postdocs are commonplace systems, with large on more it would have been biomolecules or structures; impossible to study nicotine on graphene back in those early days.” Caffeine is fine in your everyday coffee, coffee, everyday is fine in your Caffeine but you probably wouldn’t want to find too find too to want wouldn’t probably but you “

r een a of b e Z s into useful chemicals,” she says. into useful chemicals,” 2 RESEARCH HIGHLIGHT RESEARCH Better materials for industrymaterials for Better 7YVMLZZVY+LIYH)LYUOHYK[MYVT[OLL\ZL9HPQPUHZHUL_WLYPTLU[HS[VVS for and test new materials to propose technologies, applications such as battery KL[LJ[PVUVM[V_PJTVSLJ\SLZHUKJVU]LYZPVU VM*6 7VZ[KVJ[VYHSYLZLHYJOLY+Y;HU]LLY/\ZZHPU investigation into the is leading the group’s design of ‘nanosensors’ based on nanosheets, which can be used to detect potentially harmful substances in our environment. many compounds that may not are “There IL[V_PJPUL]LY`KH`SPMLVYPUSV^HTV\U[Z but they might be undesirable in a particular LU]PYVUTLU[¹L_WSHPUZ7YVMLZZVY)LYUOHYK[ ¸-VYL_HTWSLJHɈLPULPZÄULPU`V\YL]LY`KH` JVɈLLI\[`V\WYVIHIS`^V\SKU»[^HU[[VÄUK too much of it in an anaesthetic.” molecules, including Many biologically relevant JHɈLPULUPJV[PULHUKL[OHUVSIPUK^LHRS` [V[^VKPTLUZPVUHSUHUVZOLL[ZZ\JOHZ graphene. of properties Upon binding, the electronic a clear the nanosheets change – providing has been signal that the molecule of interest detected. ideal for use as sensors Nanosheets are ILJH\ZLVM[OLPYL_[LUZP]LZ\YMHJLHYLHZ L_WSHPUZ7YVMLZZVY)LYUOHYK[ almost “Because these materials are made up of surfaces, you can entirely that’s sensory area have a very large still compact and light weight,” she says. better nanosensors is Key to creating PKLU[PM`PUN^H`Z[VPUJYLHZL[OLZWLJPÄJP[`HUK a number of a number of on rearrangements V_PKH[PVU “That means sort of being it’s in the destroyed ÄYZ[YV\UKVM transfer, electron not around so it’s to keep cycling.” Coote Professor and her team saw and these results decided to use computational chemistry to investigate why this WHY[PJ\SHYUP[YV_PKL ”

efficiency of the solar cell. efficiency The new compound doubled the The new TVSLJ\SL^HZ\UZ[HISL\WVUV_PKH[PVUHUKÔH[ it while structural changes could be made to stabilise RLLWPUNP[ZV_PKH[PVUWV[LU[PHS^P[OPU[OLPKLHSYHUNL for the dye. ¸>L\ZLK9HPQPU[VPU]LZ[PNH[LTHU`KPɈLYLU[ Z[Y\J[\YLZHUKJHTL\W^P[OÄ]LWYLKPJ[LK says. compounds that we thought would work,” she ¸5V[SVUNHM[LY^HYKHUPUKLWLUKLU[L_WLYPTLU[HS a solar cell using one manufactured group research the of our compounds. The new compound doubled LɉJPLUJ`VM[OLZVSHYJLSS¹ who is head of the Computer Coote, Professor (PKLK*OLTPJHS+LZPNU.YV\WH[(5<ZH`Z\ZPUN to computational quantum chemistry is crucial deeper insight a much and provides her research by than can be provided into chemical processes L_WLYPTLU[ absolutely could not do this work without access “We [V9HPQPU¹ZOLZH`Z “

RESEARCH HIGHLIGHT RESEARCH :\WLYJOHYNPUNZVSHYJLSSLMÄJPLUJ` (9*-\[\YL-LSSV^ Michelle Professor Coote and her team The Australian from National University OH]L\ZLK9HPQPU to double the LɉJPLUJ`VMZVSHY cells. 0UHK`LZLUZP[PZLK solar cell, the dye absorbs sunlight, causing the dye to change form and an electron release which generates A second electricity. component is then form needed to convert the dye back to its starting can begin again. This component is so the process JHSSLKHºYLKV_TLKPH[VY» ¸4VZ[K`LZLUZP[PZLKZVSHYJLSSZ\ZLHUPVKPKL TVSLJ\SLHZ[OLYLKV_TLKPH[VY¹L_WSHPUZ7YVMLZZVY Coote. it is “This has a number of disadvantages. Firstly, that cuts down on how much sunlight and coloured is available to be absorbed by the dye. ¸:LJVUKS`P[ZV_PKH[PVUWV[LU[PHSBP[ZHIPSP[`[VNP]L to the dye and thus convert it back to back electrons the dye, its starting form] is not very well matched to SLHKPUN[VPULɉJPLUJ`¹ had been proposing For several years, researchers [OL\ZLVMHUP[YV_PKLYHKPJHSHZ[OLYLKV_TLKPH[VY instead. ¸5P[YV_PKLYHKPJHSZHYLJVSV\YSLZZHUK[OLPYV_PKH[PVU potential is much closer to the range needed to get TH_PT\TLɉJPLUJ`PU[OLJVU]LYZPVUVM[OLK`L¹ L_WSHPUZ7YVMLZZVY*VV[L^OVPZWHY[VM[OL(9* *LU[YLVM,_JLSSLUJLMVY,SLJ[YVTH[LYPHSZ:JPLUJL who set out was that the researchers The problem [V[LZ[UP[YV_PKL\ZLKHTVSLJ\SL[OH[\UKLYNVLZ

40 2 Annual Report 2014/15 43

”

observational science. “The only way we can do some aspects of ocean“The only way we can says computer simulation,” is through research 7YVMLZZVY)PUKVɈ of discover the role models to creating are “We KPɈLYLU[MHJ[VYZZ\JOHZVJLHUÅVVY[VWVNYHWO` like the currents strong of really in the presence Current. Circumpolar Antarctic of these simulations, we have “Using the results WYVWVZLKVIZLY]H[PVUHSL_WLYPTLU[Z[VNVV\[HUK same things to validate our models. the measure ¸:V[OPZPZHNYLH[L_HTWSLVMOV^[OLVYL[PJHS ZPT\SH[PVUZ[VZVTLL_[LU[JHUKYP]LVIZLY]H[PVUHS science.” millions of compute simulations require The team’s tens and produce of processors, hours, hundreds beenof terabytes of data – logistics that have only advances in computational made possible by recent facilities such as NCI. have done this work,” years ago you couldn’t “Ten ZH`Z7YVMLZZVY)PUKVɈ¸5V^[OH[JVTW\[LYZ been a of these simulations, there’s capable are in oceanography. renaissance ¸;OLWYVQLJ[»ZYLZ\S[Z^PSSN\PKL[OLKL]LSVWTLU[VM Z[H[LVM[OLHY[NSVIHSVJLHUHUKJSPTH[LTVKLSZ more and respond our ability to predict and improve LɈLJ[P]LS`[VJSPTH[LJOHUNL¹ simulations to some extent can drive some extent simulations to This is a great example of how theoretical of how This is a great example “

p ves the dee ves the i t dr a RESEARCH HIGHLIGHT RESEARCH What drives the deep the deep What drives 7YVMLZZVY5H[OHU)PUKVɈHUKOPZ[LHTH[[OL

”

possible combinations. Ionic liquids are already being used by industry in being already are Ionic liquids ,\YVWL[VKPZZVS]LJLSS\SVZLH[Q\Z[ *SLHKPUN[VH is costs. The only downside in energy huge reduction [OLJVZ[VMWYVK\J[PVUZH`Z+Y7HZ about one trillion possible ionic liquids,” are “There she says. have to spend a century in the lab to be able “You’d all the possible combinations. That’s to go through Q\Z[UV[ZLUZPISLPU[LYTZVMLULYN`HUK^LULLKPVUPJ solutions soon.” +Y7HZPZHSZVJVSSHIVYH[PUN^P[O:PUNHWVYLHU to look at developing ionic company H2SG Energy devices for use as membranes in energy hydrogels such as fuel cells. the“Honestly I do believe that ionic liquids will be ZVS]LU[ZVM[OLM\[\YL¹ZH`Z+Y7HZ energy so fantastic in terms of reducing “They are be no alternative will probably but to go that there the cost of their for them, as long as we can reduce production.” lab to be able to go through all the be able to lab to You’d have to spend a century to in the have You’d “

RESEARCH HIGHLIGHT RESEARCH Solvents of the future of the future Solvents (9*-\[\YL-LSSV^+Y2H[`H7HZMYVT4VUHZO temperatures. “Ionic liquids are the considered solvents of the M\[\YL¹L_WSHPUZ +Y7HZ “They have ILULÄJPHS properties such as high conductivity and but they do not temperature, being liquid at room L]HWVYH[LHUK[OLTHQVYP[`VM[OLTHYLJOLTPJHSS` stable at higher temperatures. solvents will start to “That means when organic decompose, ionic liquids will actually stay intact don’t which is fantastic because it means that you your solvent, plus you have to constantly replenish ^PSSUV[OH]L[OL[V_PJWYVK\J[ZHZZVJPH[LK^P[O solvents.” organic generated by weakening the Ionic liquids are their interactions in ionic compounds to reduce melting temperature. of ions; “Basically ionic materials consist entirely MVYL_HTWSL[HISLZHS[JVUZPZ[ZVMVUS`ZVKP\THUK chloride ions. Because the main attraction is ionic, is so high that these it means that the strength compounds have a high melting temperature. chemical “The idea behind ionic liquids is to introduce away from that either ‘shield’ or draw charge groups is a conductive salt and the result charge the centre that has a low melting point.”

42 2 Annual Report 2014/15 45 ”

in size.

Our dataset is around half a petabyte Our dataset is around half a petabyte Neutron stars display a very characteristic signal, stars Neutron Bailes. says Professor ¸>OLUHUL\[YVUZ[HYW\SZLOP[ZV\Y[LSLZJVWLP[ÄYZ[ radio stations and then appears in the high frequency radio it sort of sweeps down to the lower frequency stations afterwards. ¸>L\ZL9HPQPU[VZLHYJOMVY[OLZLJOHYHJ[LYPZ[PJ KLSH`ZIL[^LLUV\YYLN\SHYS`ZWHJLKYHKPV Z[H[PVUZ[VÄUKV\YUL\[YVUZ[HYZ¹ :VMHY[OLWYVQLJ[^OPJOPZHJVSSHIVYH[PVU^P[O *:096[OL4H_7SHUJR0UZ[P[\[L[OL

” but with a much 2

effectively. carbon tend to bind CO to carbon tend Current materials for capturingCurrent for materials , predicting the binding strength and voltage the binding strength , predicting 2 “ NCI to do is search for materials that have a NCI to do is search ZPTPSHYJHWHJP[`[VIPUK*6 YLZWVUZLWYVÄSL[VWPUWVPU[HTH[LYPHS^P[OPKLHSS` balanced properties. very numerically intensive “These are calculations, which demands that we have of capability that access to a facility of the order [OL5*0OHZ¹L_WSHPUZ7YVMLZZVY:TP[O is no other way you can do this work.” “There smaller bandgap.” ;OL[LHTPZY\UUPUNÄYZ[WYPUJPWSLZHUKLSLJ[YVUPJ Z[Y\J[\YLJHSJ\SH[PVUZVU9HPQPU[V^VYRV\[ L_HJ[S`OV^LHJOUL^TH[LYPHSPU[LYHJ[Z^P[O *6

2 go.” 2 too strongly, which too strongly, 2 in contact with these 2 VɈHUK[OH[JVZ[ZTVUL`¹ 2 at all. But if you put an electrical too 2 2 RESEARCH HIGHLIGHT RESEARCH Carbon capture’s ‘Goldilocks problem’ ‘Goldilocks capture’s Carbon LɈLJ[P]LS`;OPZ causes problems when the carbon needs to be for again released sequestration or recycling. ¸0M[OLTH[LYPHSIPUKZ[V*6 JOHYNLVU[OLTH[LYPHSZ\KKLUS`P[IPUKZ*6 L_WSHPUZJOPLMPU]LZ[PNH[VY7YVMLZZVY:LHU:TP[O a ‘Goldilocks problem’.” “It’s taking a novel Smith and his team are Professor for new materials. They to the search approach OH]LPKLU[PÄLKZL]LYHSTH[LYPHSZ[OH[HKVW[ HS[LYLKIPUKPUNILOH]PV\Y^OLUL_WVZLK[V electrical charge. ¸5VYTHSS`PM`V\W\[*6 materials there is very weak binding – they won’t is very weak binding – they won’t materials there JHW[\YL*6 is the basic problem with current materials, then with current is the basic problem you have to heat them up to a high temperature [VW\SS[OL*6

The result is a material that can be ‘switched’ on The result HUKVɈ^P[OHULSLJ[YPJHSJOHYNLZPKLZ[LWWPUN [OLL_WLUZP]LOLH[PUNYLX\PYLTLU[ZVMJ\YYLU[ industry materials. X\P[LLɈLJ[P]LS`¹ZH`Z7YVMLZZVY:TP[O¸(UKPM `V\[OLUYLTV]L[OLJOHYNLP[SL[Z[OL*6

44 2

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carbon from power carbon from

for capturing

Current materials Current

materials.

carbon capture carbon capture

spot’ of new

pinpoint the ‘sweet

supercomputer to supercomputer

are using NCI’s using NCI’s are

from UNSW from 9LZLHYJOLYZ Annual Report 2014/15 47 ”

activity of graphene nanoflakes. “Graphene is a very hot topic at the moment,” says “Graphene is a very hot topic at the moment,” Karton. Professor ¸0[ZKPZJV]LYLYZLHYULKH5VILSWYPaLPUQ\Z[ ZP_`LHYZHM[LYP[ZKPZJV]LY`4VZ[JVTWV\UKZVM OPZ[VYPJHSZPNUPÄJHUJLOH]LILLUYLJVNUPZLK^P[O a Nobel Prize 20 or even 30 years after discovery. how amazing this material is.” That’s (ZZPZ[HU[7YVMLZZVY2HY[VUHUKOPZ[LHT\ZLK9HPQPU [VZOV^MVY[OLÄYZ[[PTL[OH[NYHWOLULUHUVÅHRLZ JV\SKLɉJPLU[S`JH[HS`ZLHYHUNLVMJOLTPJHS reactions. they used The sophisticated computational modelling had enormous compute and data requirements. ¸.YHWOLULUHUVÅHRLZHYLYLSH[P]LS`SHYNLHZ far as molecules go, which meant the compute of the modelling increased requirements L_WVULU[PHSS`^P[O[OLZPaLVM[OLZ`Z[LT ¸>LYLX\PYLKYLHSS`SHYNLZJHSLJHSJ\SH[PVUZ[OH[ do on any other cluster in Australia but we couldn’t 9HPQPU crucial for this really “The two things that were WYVQLJ[^LYL]LY`SHYNLTLTVY`HUK]LY`SHYNLHUK done it without the NCI have couldn’t fast disks. We facilities.” Our team has discovered a new catalytic catalytic a new has discovered Our team “ RESEARCH HIGHLIGHT RESEARCH New function for Nobel compound compound for Nobel New function 9LZLHYJOLYZOH]L\ZLK9HPQPU[VKPZJV]LY[OH[UHUV the rate sized fragments of graphene can speed up of chemical reactions. the University Amir Karton from Assistant Professor VM>LZ[LYU(\Z[YHSPHZH`Z[OLÄUKPUNZ\NNLZ[Z carbon – might have graphene – sheets of pure potential applications in catalysing chemical of industrial and medical importance. reactions ¸.YHWOLULPZVULVM[OLTVZ[L_JP[PUNTH[LYPHSZ [V^VYR^P[OPUUHUV[LJOUVSVNÌLJH\ZLP[Z+ make unique chemical properties and structure candidate for new applications like it a promising nanodevices that can be used in mobile phones, says energy,” devices and renewable health care Karton. Professor ¸,]LYZPUJL[OLKPZJV]LY`VMNYHWOLULPU for applications. scientists have been searching ¸6\Y[LHTOHZKPZJV]LYLKHUL^JH[HS`[PJHJ[P]P[`VM NYHWOLULUHUVÅHRLZÔPJOPZ]LY`L_JP[PUN¹ for its weight – about strong Graphene is remarkably than steel – and conducts heat 100 times stronger HUKLSLJ[YPJP[`^P[ONYLH[LɉJPLUJ` to have The global market for graphene is reported US$9 million per year with most sales reached electronics, concentrated in the semiconductor, composites. and battery energy ” 7YVMLZZVY3`VUZ

to model a single month. to It takes us about eight hours time real It takes “ agriculture, where you’re looking at thousands of looking you’re where agriculture, HJYLZ¹ZH`Z7YVMLZZVY3`VUZ¸@V\JHU»[[HRLHJ[PVU against that.” ;OLVUS`^H`MVYIYVHKHJYLMHYTLYZ[VH]VPKMYVZ[ so they can damage is to know the timing of frosts HKQ\Z[[OLPYWSHU[PUNKLJPZPVUZZH`Z is if you plant too early or late you’ve “The problem is going to be also got to worry about whether there when you need it,” he around enough soil moisture says. basically trying are quite a nifty balance. We “So it’s [VZVS]L[OH[WYVISLT^P[OMHYTZJHSLTL[LVYVSVN`¹ western Australia RESEARCH HIGHLIGHT RESEARCH More frosts to hit WA crops WA to hit More frosts

46 2

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amounts of data.”

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these studies over 30 years, so you can imagine it

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do is to take global climate models

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team at Murdoch University are University are team at Murdoch

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billion agricultural industry.

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5L^YLZLHYJOWLYMVYTLKVU9HPQPU will become even drier, with severe severe with will become even drier, Annual Report 2014/15 49 ” “

We can do so much more now than more now can do so much We “These molecules and proteins are very dynamic, are “These molecules and proteins TV]PUNÅL_PISLZ`Z[LTZ¹OLZH`Z scientists thought of molecules binding “Traditionally to active sites like a ‘key in a lock’. the lock and key at home on your “But the reason is because the components don’t door works front TV]L¶[OL`»YLPUÅL_PISL ¸0MIV[O`V\YRL`HUKSVJRHYLÅL_PISLHUKJHUTV]L harder. and change shape, that makes it a whole lot molecule that not quite as simple as making a “So it’s ^PSSÄ[[V[OLL_HJ[ZOHWLVM[OLHJ[P]LZP[L¹ the more computing power, the The greater accurately these molecules can be modelled. it’s “If we had unlimited computing power – and as computers will happen in the future what probably HK]HUJL¶^L^V\SKYLWLH[V\YL_WLYPTLU[Z statistics of how well a robust times to get really and therefore certain molecule binds to the protein OV^LɈLJ[P]LP[JV\SKILHZHKY\N¹ZH`Z+Y>PSZVU or now than even three can do so much more “We Ä]L`LHYZHNV[OHURZ[V[OL^H`JVTW\[PUNRLLWZ advancing.” even three or ﬁve years ago thanks to years ago thanks to three or ﬁve even the way computing keeps advancing. computing keeps the way RESEARCH HIGHLIGHT RESEARCH Computer-aided drug design drug design Computer-aided +Y+H]PK>PSZVUMYVT3H;YVILPSZVU could “If we could stop these kinases working, we those disease states.” target +Y>PSZVUHUKOPZ[LHTHYL\ZPUNTVSLJ\SHY TVKLSSPUNWYVNYHTZVU9HPQPU[VKLZPNUZTHSS molecules that block the kinases’ active sites. of these kinases we “By understanding the structure JHUILNPU[VKLÄULZTHSSTVSLJ\SLZ[OH[JV\SKIPUK and to and block up the active sites of these proteins functioning,” he says. stop them from ;OL[LHTPZ^VYRPUN^P[OL_WLYPTLU[HSIPVSVNPZ[Z[V [LZ[[OLPYJVTW\[LYKLZPNULKKY\NZPU[OLSHI ¸>LTVKLSSV[ZVMKPɈLYLU[TVSLJ\SLZHUK[OLU choose the best 10 to synthesise and perform IPVSVNPJHSHZZH`Z^P[O¹L_WSHPUZ+Y>PSZVU ¸;OLUVU[OLIHZPZVM[OVZLL_WLYPTLU[Z^LNV IHJRHUKTVKPM`[OLTVKLSZ[VYLÄUL[OLILZ[[HYNL[ molecules. and have been making some good progress “We’ve several lead compounds that look promising.” ;OLWYVJLZZPZJVTWSL_HUKJVTW\[LPU[LUZP]LZH`Z +Y>PSZVU ” ILY`SSP\TMV\UK surface. on Earth’s +Y:TP[O»ZJVSSLHN\L +Y

in the Sun’s intensity is critical to is critical to intensity in the Sun’s Understanding patterns of variation of variation Understanding patterns understanding future climate change. understanding future climate the Earth’s polar ice you can reconstruct the activity ice you can reconstruct polar the Earth’s of the Sun in past times.” Understanding patterns of variation in the Sun’s climate future intensity is critical to understanding JOHUNLZH`Z+Y:TP[O^OVZLL_WLKP[PVUZHYL M\UKLKI`[OL(\Z[YHSPHU(U[HYJ[PJ+P]PZPVU 6MJV\YZLUV[OPUNPZL]LYHZZPTWSLHZP[ZLLTZ the a whole range of factors, such as are There ,HY[O»ZKPWVSHYTHNUL[PJÄLSK[OH[HɈLJ[[OLSL]LSZVM that increased know any better you might interpret in solar activity, concentration as being a decrease not. but it’s ¸;OLTVKLSSPUNVU9HPQPUYL]LHSLK[OH[P[PZHJ[\HSS` caused by a change in the weather systems, which has allowing stratospheric stratospheric air, TVYLILY`SSP\TPUP[[OHU[YVWVZWOLYPJHPY[V descend down to the site.” Dr Andrew Smith holds an ice Dr Andrew for analysis core “ RESEARCH HIGHLIGHT RESEARCH Tracking the Sun’s history the Sun’s Tracking

48 2

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bringing back ice cores for analysis. for analysis. bringing back ice cores

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Sun’s activity over recent millennia. millennia. recent activity over Sun’s 9HPQPUPZOLSWPUNYLZLHYJOLYZ[V[YHJR]HYPH[PVUZPU[OL 3 Our Infrastructure

51 Annual Report 2014/15 53 This year the HPC Systems Team has also Team This year the HPC Systems custom job-monitoring enhanced Raijin’s of SU usage and per with the addition dashboard, job statistics. per project and per user, stakeholder, to work with staff help support These improvements throughput. jobs to increase users to optimise their been evaluating the the team have Finally, generation processors performance of new next supercomputer for NCI’s in preparation deployment. 57,472 Intel Xeon cores 57,472 Intel Xeon cores (Sandy Bridge, 2.6 GHz) Inﬁniband full fat-tree Mellanox FDR 56 Gb/sec interconnect • Fujitsu Primergy cluster • Fujitsu Primergy cluster • 1.2 PFlops peak performance • • • 160 TB main memory • 10 PB disk storage hours/annum • 503M core packages • 300+ software • Access to 20 PB data repository Raijin new Installed for testing in January 2014, Raijin’s made available accelerators were Mellanox software CSIRO’s to users in July 2014. Benchmarking using shown Cubic Conformal Atmospheric Model has of the accelerators, along with that the introduction has led to a 2.5-fold adoption of hyperthreading, run-time. efﬁciency in the model’s Our Infrastructure Our

Our Vendors

52 3 Annual Report 2014/15 55 Access to 20 PB NCI’s site-wide high-speed parallel filesystems Solid State Disk (TB) Main memory (TB) 25 160 Yes 4.6 12.8 Yes 25 160 No Interconnect 3968 Mellanox FDR 56 Gb/sec Infiniband full fat-tree Dell 10 Gb/ sec Ethernet Mellanox FDR 56 Gb/sec Infiniband full fat-tree 2368 Core Core hardware Physical cores Intel Xeon Sandy Bridge, 2.6GHz Intel Xeon Westmere, 2.6GHz Intel Xeon Sandy Bridge, 2.6GHz Physical Physical cores 0 1\UL 1\UL 500 4000 3500 3000 2500 2000 1500 Nodes Peak performance (Tflops) 33.5 100 1,600 4 32 768 33.5 100 1,600 7ÅVWZ 71 232 Operating Operating platform Red Hat OpenStack Red Hat OpenStack Ubuntu OpenStack Nodes 132 37.5 Cloud statistics Researchers affiliated with Australian universities NCI’s cloud environment NCI’s

Peak Performance 0 0 Cloud to Available Tenjin NCI partners RHOS NCI partners NeCTAR 50 90 75 60 45 30 15 Figure 8: Figure Table 6: Table 250 200 150 100 RHOS cloud Hat OpenStack (RHOS) The NCI Red private cloud. It is our first-generation environment September 2013. was commissioned in NeCTAR of the Australian NCI is one of eight nodes National eReserach Collaboration Government’s federated research (NeCTAR) and Resources Tools node, which came NeCTAR cloud initiative. The NCI physical 1,600 2014, provides online in March affiliated with Australian researchers to cores nodes, which universities. Unlike the other NeCTAR the on generic or commodity hardware, based are specification. NCI node is of supercomputer which is encompassed within In contrast to Tenjin, cloud rich site-wide filesystems, the NeCTAR NCI’s is managed, like the other nodes of the NeCTAR the University federation, in a centralised way from of Melbourne. In 2014/15, Tenjin’s data storage system has been has been system data storage Tenjin’s In 2014/15, TB to 1 PB capacity. 500 from upgraded

The HPC Systems Team also contributed The HPC Systems Team its increasing a patch to Parallel Debugger, to theoretically 112 cores scalability from – limited only by physical unlimited cores making the software memory – effectively exascale ready. In the course of maintaining Raijin, NCI’s NCI’s of maintaining Raijin, In the course find and repair often Teams expert System the team the past year, bugs. In software that patches five Lustre have contributed available to the open have since been made The team also community by Intel. source fixes to Raijin’s contributed several bug including PBSPro, scheduling software, and walltime limits, bonus time calculation memory leak, which and fixing an ancient into the upcominghas been incorporated led These contributions of PBSPro. release deliver talks at Altair to to an invitation from ‘15. ‘14 and PBS User Group Supercomputing EXPERT STAFF EXPERT

Tenjin is specifically designed for data-intensive Tenjin as genomics, earth system science, such research, for and geophysics. It is an ideal environment access to the datasets held in requiring research Data Collection. Research the NCI Environmental Tenjin, NCI’s supercomputer-grade cloud, was cloud, supercomputer-grade NCI’s Tenjin, made available to our partner organisations in has been September 2014. Since then, Tenjin than 99.5% uptime. maintained at greater TENJIN Cloud over three spread NCI cloud facilities are cloud, available to all installations: the NeCTAR clouds, available users; and the ROHS and Tenjin official partner organisations. The NeCTAR to NCI’s built to supercomputer clouds are and Tenjin foundation specification with the same hardware fastest the as Raijin, making NCI’s and interconnect in the Southerncloud environment Hemisphere.

54 3 Annual Report 2014/15 57 1\UL 1\UL Raijin compute data movers Raijin login + 56 Gb FDR IB FaBRIC 7.6PB /short up to 140 up to 150GB/sec Active job storage up to 45 Cloud 56 Gb FDR IB FaBRIC This year the Data Storage Services Team have have Team Services Storage the Data This year Spectra NCI’s the capacity of also expanded data hold archival tape libraries, which Logic T950 parallel up for our site-wide back and provide capacity of The potential raw storage filesystems. to 25 PB from has been increased these libraries than installation of more with the 49 PB this year, these libraries currently 1,440 tapes. Together, data. than 12 PB of hold more filesystems have been maintained at Overall, NCI’s this financial year. than 99% uptime greater Access speed (GB/sec) 0 80 60 40 20 22.1PB /g/data 140 120 100 Internet up to 140GB/sec Active project storage VMware 10 GigE 21.8 12PB mass data up to 140MB/sec Archival tape storage Archival 11.9 Data storage statistics Filesystem configuration Filesystem configuration services NCI data Storage capacity (PB) 0U(WYPS5*0ZPNULKH 4KLHS^P[O-\QP[Z\ management storage and data to work with installNetApp to supply and company NKH[H;OLUL^-(:,ZLYPLZHUK,-HSS ÅHZOZ[VYHNLHYYH`ZWYV]PKLHUHKKP[PVUHS accessible capacity, PB of persistent storage H[\W[V.)ZLJVU9HPQPUNKH[H^PSS JVUZPZ[VM 9HJR

(A*Star) to improve global data transfer speeds. global data transfer improve (A*Star) to >VYRPUNPUJVSSHIVYH[PVU5*0HUK(:[HYZ[HɈ\ZLK0UÄUP)HUK[L LɉJPLUJ`VM[OL((95L[WPWLSPUL[OH[J\YYLU[S`SPURZ[OLZLVYNH In a demonstration at :\WLYJVTW\[PUNº[OL[LHT system resulted showed that the new dataset from in transfer of a 1.2 TB :PUNHWVYL[V(\Z[YHSPHPUQ\Z[ using to 9 hours minutes, compared The TCP/IP protocol. the standard on NCI’s data was then analysed ;LUQPUJSV\KHUK[OLYLZ\S[ZYL[\YULK immediately to A*Star. in breakthrough This profound [YHUZJVU[PULU[HSKH[H[YHUZMLYOHZ THQVYPTWSPJH[PVUZMVYPU[LYUH[PVUHSS` JVSSHIVYH[P]LYLZLHYJO"OPNOZWLLK ‘globally distributed cloud computing’ – the capability todata transfer will enable the possibility of ZWSP[QVIZV]LYT\S[PWSLPU[LYJVU[PULU[HSJSV\KLU]PYVUTLU[Z 5*0OHZILLU^VYRPUN^P[O(:[HY[VNYV^[OLº0UÄUP*VY[L_»UL[^ <:<21HWHU:V\[O2VYLH-YHUJLHUK7VSHUKOH]LHSSPTWSLTLU Singapore. Globally distributed cloud distributed cloud Globally 0U5V]LTILY5*0[LHTLK\W^P[O:PUNHWVYL»Z(NLUJ`MVY:JPL

In January 2015, the upgraded /g/data2 filesystem service, with an expansion full production entered 4.5 PB to 6.7 PB. Eight major data collections from totaling 2,018 TB have been migrated from and /g/data1 to /g/data2 to allow for growth These infrastructure performance. improved provide NCI’s site-wide parallel Lustre filesystems have filesystems site-wide parallel Lustre NCI’s with this financial year, been enhanced greatly in the addition of 10 PB capacity and an increase 45 GB/sec to up to 90 GB/sec, transfer speed from to 140 GB/sec in and which is expected to increase the following year. ENHANCED STORAGE CAPACITY ENHANCED STORAGE Data Storage

56 3 ENHANCED TRANSFER SPEEDS

The NCI Data Storage Services and HPC Systems NCI’s primary internet connection was also 3 teams have worked together to significantly upgraded, in August 2014, to the latest generation improve data transfer efficiency within the NCI AARNET4 link, moving from a capped to a facility. The result is an increase in data migration dedicated full bandwidth 10 Gigabit connection. rates between filesystems to more than This improved connection has boosted the ingest 15 GB/sec with the introduction of an of nationally and internationally sourced data open-source distribution copy tool. collections as part of the RDSI project, as well as offering improved transfer speeds to users connecting to Raijin from outside NCI.

Superfast international data transfer NCI is working with data managers from around 3HIVYH[VY`PU[OL<:(\ZPUNOPNOZWLLKNSVIHS the country and the globe to quickly and reliably networks. transfer very large datasets. This undertaking has only been possible So far NCI has ingested 1.5 PB of the Coupled ILJH\ZLVM[OLL_WLY[PZLVM5*0Z[HɈ^OVOH]L 4VKLS0U[LYJVTWHYPZVU7YVQLJ[*407 achieved a very high fraction of the theoretical KH[HZL[MYVT[OL3H^YLUJL3P]LYTVYL5H[PVUHS IHUK^PK[OVMNSVIHSUL[^VYRZBZLLWHNLD

4 Outreach

58 59

Annual Report 2013/14 61 ]LTILY (\N\Z[ 6J[VILY +LJLTILY 1HU\HY` 20 April 2015 21 April 2015 23 April 2015 22 May 2015 1\S` (\N\Z[ (\N\Z[ Date ;LHT :LW[LTILY Building tours and outreach activities outreach tours and Building 5*90::OV^JHZLH[7HYSPHTLU[/V\ZL3HRL.PUUPUKLYYH*\I:JV\[ZChina Scholarship Council *V\UJPSVM(\Z[YHSPHUSummer SchoolANU Astroinformatics CommitteeGeneral meeting of the National Science Week University masters students Tokyo GA from Geochronologists Universities Australia Higher Education Conference+LWHY[TLU[VM*VTT\UPJH[PVUZ )LPQPUN0UZ[P[\[LVM;LJOUVSVN` .PYSZPU0*;+H` ANU Computer Science undergraduates 5V =PJ[VYPHLSSPUN[VU 3(5+:(;*VUMLYLUJL :LW[LTILY +LJLTILY 18 February 2015 6J[VILY 2015 10 March 13 February 2015 26 February 2015 2015 3 March 18 May 2015 1\UL Group .YV\WVM *VTT\UPJH[PVUZ+PYLJ[VYZ candidates Scholarship Tuckwell <5:>L9LZLHYJO*VVYKPUH[PVU.YV\W & Society Fenner School of Environment the ANU students from Undergraduate Science in at the National Science Week on NCI and supercomputing Public lecture ACTion day at ANU +LSLNH[LZMYVT8H[HY

YOUTUBE VIEWS YOUTUBE TWITTER FOLLOWERS TWITTER FACEBOOK LIKES FACEBOOK

60 4 Annual Report 2013/14 63 25 March, 25 May, 25 May, 25 March, 2015 30 June AustraliaAustralia 2 August 2014 USA 2014 4-5 August UKUK 2014 August 10-14 Australia September 2014 1-3 France September 2014 15-18 September 2014 1-4 Singapore 2014 22-23 September 2014 October 7 AustraliaUSA 29 October 2014 USAAustralia 2014 November 15-20 USA 8-9 December 2014 2014 22-24 November AustraliaAustralia 2015 February 2014 December 18-19 15-19 Japan 2015 26-27 February Australia 2015 - 6 March February 24 USA 2015 3-7 March Australia 2015 March Singapore 11-13 2015 March 7 2015 March 17-20 AustraliaAustralia 2015 24-25 March 2015 25 March Australia FranceAustria April 2015 7-10 Australia April 2015 12-17 2015 May Australia 11-13 Australia 2015 May 19 Australia 2015 May 27-29 UK 2015 5 June JapanAustralia 2015 June 8-12 2015 June 16-20 2015 26 June Conference presentations by NCI staff by NCI presentations Conference

ConferenceMolecular Modeling Country Date Drishti Workshop AmericanAnnual Meeting Chemical Society Advancement Scientific for Tomography Drishti Workshop Workshop Oil and Gas Industry Conference & Developers Admin Lustre Council HPC Advisory OzEWEX Conference Supercomputing Drishti Workshop OzViz American Union Annual Meeting Geophysical User Group SGI Data Migration Facility Conference Science ICT Network Technologies on Operational Regional Internet Conference Pacific Asia Virtual NeCTAR Laboratories Workshop Workshop Oil and Gas Education Australia Higher Universities Frontiers Supercomputing Science Meets Parliament Systems Software on Environmental International Symposium Workshop Optimisation and Performance Programming Parallel Modelling in Chemistry Transfer : Charge Workshop CECAM Geosciences Union Annual Meeting European Agenda Technology Higher Education Workshop Model Evaluation Blue Planet Symposium on Modelling the Ocean Workshop International Workshop Office Collaborators UK Meteorology Computational Methods ICQC Satellite Meeting: Novel Workshop Data Science Programme National Environmental Table 8: Table

62 4 4

5 Governance and Finance 64 65 Annual Report 2014/15 67 Dr Chris Pigram Dr Robert Frater Mr Graham Hawke Independent Member Bureau of Meteorology Bureau Vice-President Innovation, ResMed Ltd. Vice-President Deputy Director (Environment & Research), & Research), (Environment Deputy Director Chief Executive Ofﬁcer, Geoscience Australia Chief Executive Ofﬁcer, CSIRO Dr David Williams Dr Thomas Barlow Independent Member Independent Member, Independent Member, Professor Robin Stanton Robin Stanton Professor Professor Margaret Harding Harding Margaret Professor Deputy Vice-Chancellor (Research), ANU Deputy Vice-Chancellor (Research), Research Strategist, University of Sydney Research Former Pro Vice-Chancellor (eStrategies), ANU Former Pro Executive Director National Facilities & Collections, Executive Director Chair Director, NCI Director, Professor Lindsay Botten Professor Emeritus Professor Mark Wainwright, AM Wainwright, Mark Emeritus Professor Board Members

tt l ti i O Organisational structure

One member appointed by each of the Major One member appointed CSIRO, BoM and GA) Collaborators (ANU, members Additional independent board Board appointed for two-year terms by the NCI on the basis of their expertise the Finance, Audit, Risk and Management Committee

• An independent Chair appointed by the Board • An independent Chair NCI • The Director, • • • the Nominations Committee •

Fi NCI is governed The Australian National by which of the NCI Board, University on the advice comprises: is advised by: The Board and Finance and The NCI Board Governance Governance Figure 12: Figure

66 5 Annual Report 2014/15 69 $ Financial report report Financial NCI Collaboration Income NCI Collaboration Income Other grant income Income Investment Salaries & Related Costs - Capital Equipment - Non-Capital Equipment Utilities & Maintenance Expenses & Survey Field Travel Materials Expendable Research Contributions150,500 699,118 Consultancies 641,852 Consumables 8,761,739 Other Expenses 8,316,892 201,806 6,287,212 104,072 5,476,645 402,817 3,461,526 244 149,894 Unspent Balance as at 30 June 2015 2015 Unspent Balance as at 30 June 15,666,157 Balance as at 1 July 2014 Balance as at 1 July Add Expenditure Before Funds Available Total Less 17,305,665 34,586,102 Total Income Total to other Transfers Expenditure Total 17,280,437 1,546,064 18,919,945 Current Period 9: Table OF INCOME AND EXPENDITURE STATEMENT 30 June, 2015 2014 to 01 July, For the Period accounts associated project Collaboration and For the NCI Current REVIEW/AUDIT Each funding contract held by ANU as represented and auditing by NCI has specific financial reporting and NCI, in conjunction with the requirements, Finance and Business Services Division University’s and Corporate Governance and Risk Office, acquit with these funds in accordance individual project requirements. This consolidated statement has been reviewed Finance and Business Services by the University’s that:Division. The Chief Financial Officer certifies financial The statement accurately summarises the have of these grants and that these records records maintained so as to accurately record been properly of these grants. the Income and Expenditure EXPENSES high-end research national, NCI, as Australia’s high-end world-class, service, provides computing do to order In researchers. Australia’s services to of money in its significant amounts this, NCI invests computing high-performance team of expert staff, maintenance to and utilities and infrastructure, in is reflected This operate this infrastructure. Of note is the ‘transfers profile. expenditure NCI’s transfers reflects item; this to other’ expenditure for capital works of the University to other areas funded under various and other internalpurchases contracted projects.

NCI also administers a number of grants and NCI also administers a number of grants contracts outside of the NCI Collaboration accounts. These special-purpose arrangements and infrastructure fund clearly defined projects, synergistic benefits to the NCI services that provide Collaboration. The NCI Collaboration Agreement enables The NCI Collaboration Agreement leading research-intensive many of Australia’s universities and science agencies to collectively single fund a capability beyond the capacity of any (including these institutions institution. Together, the ARC, ANU, CSIRO, BoM, Geoscience Australia, universities and a range of other research-intensive of NCI’s and consortia) fund a significant proportion proportion operating costs. A small, but growing, the of NCI Collaboration income comes from sector. commercial NCI COLLABORATION INCOME NCI COLLABORATION Each funding contract is accounted for in a distinct Each funding contract and the ledger, account within the University acts appropriate and where University facilitates, on and resolutions directions on, the NCI Board’s consistent with they are NCI matters insofar as and not contrary to funding contract the relevant University Statutes and policies. NCI is an organisational unit of The Australian unit of NCI is an organisational by represented The ANU, as National University. that funding contracts numerous NCI, administers In the interests operations of NCI. support the the NCI of picture a comprehensive of providing consolidating these report operation, a financial presented. funding contracts is Financial report report Financial

68 5 6 Appendix

71 Annual Report 2014/15 73 Total Total 3500 2300 2010 (kSU) Allocation Catherine Stampfl, University of Sydney University Catherine Stampfl, 3254 CSIROXuebin Zhang, Monash UniversityEkaterina Pas, 3017 3000 Bureau of MeteorologyThurston, William Australian National Adrian Sheppard, University 2500 University of NSWClaire Carouge, 2150 Australian National Christoph Federrath, University Monash UniversityJulio Soria, 1974 Shin-Ho Chung, Australian National Australian Shin-Ho Chung, University First-Principles Investigations of Processes and Properties in First-Principles Investigations and Devices Coatings, Catalysis, Information ServicesWater GeochemistryAtomistic Simulation for and Nanoscience models Downscaling future climate change from CMIP5 climate with an eddy-resolving ocean model Technology Curtin University of Julian Gale, ACCESS Model Optimisation ProjectNCI-Fujitsu Collaboration Unified Model porting NCI Mark Cheeseman, 3250 Application of Quantum Chemistry Methods for Development and materials the prediction of physicochemical properties of ionic High-resolution Downscaled Climate Runs Bureau of Meteorology Adam Smith, Asia-Pacific RegionGeohazard Modelling for the Computational Nanomaterials Science and Engineering 3010 3250 Molecular simulation of carbon fibre composites Prediction Specialised Forecasting and Environmental Weather Queensland University of Sean Smith, CSIROAustralia Geoscience Phil Cummins, Jack Katzfey, Systems properties of Understanding petrophysical and multiphase flow Bureau of Meteorology Pugh, Tim 3D imaging and modelling rock through experiment, Deakin UniversityWalsh, Tiffany Development of volcanic risk models 2729 2750 Structural and Mechanistic Chemistry 3000 FlowsTurbulent and Transitional High-Order Methods for modelling within the Centre of Excellence regionalizing Terrestrial 2898 2630 land surface processes Monash University Hugh Blackburn, From Plume Source to HotspotAustralia Geoscience Adele Bear-Crozier, Simulation and Modelling of Particulate Systems Sydney University of Leo Radom, TransportersMolecular Dynamics Simulations of Ion Channels and 2226 University of Sydney Serdar Kuyucak, 2257 in Star Cluster Formation Turbulence Jet-Driven Investigations of transitional and turbulent shear flows using direct of NSW University Yu, Aibing numerical simulations and large eddy simulations 2040 2256 Australian National University Rhodri Davies, 2100 2057 Project Title Science and ProcessesClimate Change Access-to-Space Scramjets Enhancement in Performance Access-to-Space Scramjets in Performance Enhancement University of QueenslandWheatley, Vincent reconstructions dynamic tectonic Towards University of QueenslandAnimals on Biological Ion Wheatley, Vincent Venomous from Toxins Action of 3853 Studies Channels Molecular Dynamics Meteorology Bureau of Aurel Moise, 3853 of Sydney University Dietmar Mueller, 3900 Institution Lead CI, 3605

Total Total 4250 7980 9000 9364 (kSU) 11568 10521 Allocation Matthew England, University of NSWMatthew England, CSIROAnthony Rafter, Australian National University 5602 Michelle Coote, 5300 Australian National University Andrew Hogg, 5235 5344 University of QueenslandAlan Mark, 4945 Australian National Malcolm Sambridge, University Robert Rees, Royal Melbourne Institute of Robert Rees, Technology Martin Asplund, Australian National Martin Asplund, University Jill Gready, Australian National University Jill Gready, Melbourne Institute of Royal Salvy Russo, Technology 18000 Swinburne University of Ming Liu, Technology Australian National Geoffrey Bicknell, University

Bulk metallic glasses University of NSW Michael Ferry, 4009 Computational Earth Imaging Electromagnetic Structure of Matter present and future climate variability and change in the Past, Southern Hemisphere Adelaide University of Derek Leinweber, 6320 CO2 conversion in catalytic MOFs CSIROThornton, Aaron 4299 Direct Numerical Simulations of Turbulent CombustionTurbulent Direct Numerical Simulations of of NSW University Evatt Hawkes, Australia and the Regional-Scale Seasonal Prediction Over Eastern Coral Sea and Controlling Approach to Understanding A Quantum-Chemical Chemical Processes 6324 Mechanisms and attribution of past and future ocean circulation change Strategic Radar Enhancement Project and dynamic Understanding the structural From molecules to cells: properties of cellular components at an atomic level territorial watersAustralia's Modelling biophysical connectivity in Australia Geoscience Johnathan Kool, Bureau of Meteorology Peter Steinle, 4850 5051 Joint project on ACCESS-CM2 developmentJoint project on Storage Molecular Simulations of Ionic Liquids for Energy Applications CSIRO Daohua Bi, 8200 3D magneto-hydrodynamical stellar modelling and 3D non- 3D magneto-hydrodynamical stellar modelling and equilibrium radiative transfer Simulation studies of biological and synthetic channelsWinds and Interactions Jets and Accretion Disks, Astrophysical with the Surrounding Medium Australian National University Ben Corry, 9800 Quantum Modelling of Photo-Electrode Materials Quantum Modelling of Photo-Electrode Computational Design of Complex Materials BLUElink3 Project Bureau of Meteorology Gary Brassington, 10100 ACCESS to decipher Rubisco structure, Simulation and Phylogenetics function and evolution CSIRO Hirst, Tony 20040 The Dynamics of the Southern OceanThe Dynamics of the Southern Australian National University Andrew Hogg, 20300 BoM ESM research Bureau of Meteorology Michael Naughton, 23450 Seasonal Prediction Systems and ScienceSeasonal Prediction Systems Meteorology Bureau of Guo Liu, 24500 Properties and Stability of Nanoparticles for Advanced ApplicationsAdvanced for Stability of Nanoparticles Properties and CSIRO Amanda Barnard, 37820 Project Title Institution Lead CI, Compute projects supported NCI in 2014/15 projects Compute by

72 6 Annual Report 2014/15 75 987 975 950 Total Total 1000 (kSU) Allocation Dietmar Dommenget, Monash UniversityDietmar Dommenget, Royal Melbourne Institute of Yarovsky, Irene Technology 995 University of Christoph Rohmann, Queensland Monash UniversityNikhil Medhekar, University of QueenslandBenjamin Powell, 971 Australian National Adrian Sheppard, University 957 CSIROJing Huang, University of NSWJason Evans, University of MelbourneWayth, Randall 942 University of Queensland 910 Jason Dossett, 900 University of QueenslandRussell Boyce, 898 850 Simon Ringer, University of Sydney University Simon Ringer, Monash UniversityMichael Reeder, of Queensland University Aijun Du, 1006 CSIROAmanda Barnard, 1003 UniversityAustralian National Jill Gready, 1000 1000 Royal Melbourne Institute of Allen, Toby 1000 Technology Global scale decadal climate variability in a ACCESS hierarchy of Global scale decadal climate variability in a climate models and Theoretical Investigation of novel materials for industrial biomedical applications composites Computer aided materials design for metal matrix reinforcements Chemical and Mechanical Atomistic Simulations for Electronic, Properties of Nanoscale Materials Bluelink developments electronic Computational approaches to organic photonic and from strongly electronics to device engineering materials: Probing Complex and Computational Mesoscale Physics, Hierarchical Material Structure records Hi-res mapping of renewable energy from meteorological for Australia SeriesTime Mitigation of Site Specific Errors from Geodetic Modelling of the Plasma Production of NanostructuresAustralia Geoscience Michael Moore, Australia Precipitation-groundwater interactions over eastern climate change impacts at multiple scales CSIRO Peter Oke, Modelling and simulation of dynamic bushfire propagation CSIRO Anthony Murphy, All-sky Advanced Processing of the GaLactic and Extragalactic 920 Survey MWA University of NSW Jason Sharples, efficient cosmological tests of modified gravity through Towards numerical simulations Physics of the interactions between high-speed craft and their environment 900 911 971 Project Title core analysis conventional and digital Integration of in Fluid FlowsTransition correlations in advanced materials: Exploring structure-property simulation and atomic resolution Nexus between computational University of NSWmicroscopy Arns, Christoph Australia's regional rainfall distribu- Predicting and understanding tion in a changing climate and Environmental Nanoelectronics Nanomaterials for Energy, from Modelling towards Rational Design Contribution Applications: 1020 Theory of Nanomorphology and the Environmental and Simulation Stability of Nanostructures and Protein Dynamics, Simulation of Enzyme Mechanisms, Institution Lead CI, Structures and Properties Monash UniversityThompson, Mark South Pacific High-resolution Climate Model SimulationsAnimal toxins as novel analgesics and pesticides 1012 University of MelbourneWalsh, Kevin transport Mechanisms of charge-membrane interactions and Australian National University Rong Chen, 1000 1000

Total Total 1300 1340 1530 1700 (kSU) Allocation Simon Campbell, Monash UniversitySimon Campbell, 1254 University of NSWSean Li, Monash UniversityGregory Sheard, University of MelbourneAndrew Ooi, 1178 1195 University of SydneyPascal Elahi, 1050 1035 Robert Stranger, Australian National Robert Stranger, University Benjamin Galton-Fenzi, University of Benjamin Galton-Fenzi, Tasmania Bernhard Mueller, Monash UniversityBernhard Mueller, Griffith UniversityDebra Bernhardt, 1697 Monash UniversityZhe Liu, 1584 Royal Melbourne Institute of Manolo Per, Technology 1563 John Abraham, University of Adelaide University of Abraham, John 1930 University of MelbourneTescari, Edoardo University of Swinburne Matthew Bailes, Technology 1700 talysis, battery technologies and talysis,

Project Title Institution Lead CI, Geophysics Fixing the weak link in stellar Convective nuclear burning in 3D: models Australia Geoscience James Goodwin, 1260 ACCESS preparation for IPCC AR5ACCESS preparation for IPCC CSIRO Hirst, Tony 1291 Computer-Aided Materials Design for Clean EnergyComputer-Aided University of Queensland Chenghua Sun, 1292 AustraliaRegional Climate Modelling in South-east Investigating electronic properties of novel oxide materials for spintronic and energy applications University of NSW Jason Evans, 1200 The role of convection in ocean circulation National UniversityAustralian Ross Griffiths, and future present Abrupt climate change events in the past, 1300 University of NSW Katrin Meissner, High-magnetic-field liquid-metal flows for fusion power and big- data cooling solutions 1216 Advanced Modelling of Biological Fluid FlowsComputational Fluid Dynamics Studies of Bluff Body and Heat in a Buoyant Channel Transfer Alternative The Survey Simulation PipeLine: SSimPL-ACS Cosmologies Study Monash University Kerry Hourigan, 1176 Computational Studies of the Mn/Ca Cluster in Photosystem II Computational Studies of the Mn/Ca Cluster in Photosystem Research, development and production computing Research, Development and application of bio/nano interfacial simulationsDevelopment and application of bio/nano interfacial Deakin UniversityWalsh, Tiffany 1519 sensors Geoscience Australia Landsat Data ProcessingAustralia Geoscience Shell Burning in Supernova The Last Minutes of Oxygen Progenitors New materials and fluids for ca shocksMix in high-acceleration implosions driven by multiple Australia Geoscience Wu, Wenjun structural and First-principles computational designs for advanced University of SydneyThornber, Ben functional materials Application of Quantum Monte Carlo methods Development and 1700 1572 Direct and Large-Eddy Simulations of Turbulent Reacting Jets Reacting Turbulent Simulations of Direct and Large-Eddy Conditions Under High Pressure Atmospheric and oceanic processes and dynamicsAtmospheric and oceanic At High and Intergalactic Gas The Interplay Between Galaxies Redshift of Melbourne University Lane, Todd 1745 Instabilities in the convecting mantle and lithosphere the convecting mantle Instabilities in Melbourne University of Louis Moresi, binaryA search for highly accelerated pulsars 1805

74 6 Annual Report 2014/15 77 600 600 550 500 500 Total Total (kSU) Allocation Jingxian Yu, University of AdelaideJingxian Yu, 609 University of Swinburne Luz Garcia, Technology Australian National Robert Stranger, University Adelaide University of David Huang, University of NSWArgueso, Daniel University of NSWJason Sharples, 599 Royal Melbourne Institute Andrew Greentree, of Technology 591 560 of Melbourne University Webley, Paul Australian National University Brian Schmidt, 550 Adelaide University of Jiao, Yan 518 University of MelbourneDaniel Chung, Australian National Giampiero Iaffaldano, University 502 500 Deakin UniversityGleb Beliakov, Australian National University Justin Borevitz, 500 Swinburne University of Shahab Joudaki, 500 Technology University of Queensland Liao, Ting 500 Project TitleMolecular Interactions between Structures the Relationship Understanding Peptronics: and Properties galaxy surveyBuilding a synthetic SAMI of spiral galaxies Modelling and simulating the evolution UWA Enzymatic CatalysisMolecular Simulations of State-based institutionsTaranu, Dan with metal absorption line ratios Diagnosing Hydrogen Reionization Metal Complexes Transition using Activation Small Molecule Australia Western University of Chris Power, 600 Institution University of Sydney Lead CI, Jordan, Meredith atmospheric turbulenceLarge-eddy simulation of Wollongong University of Yu, Haibo 600 functional Multi-scale modelling of soft condensed matter in materials and biology on the local Impacts of future land-use changes and urbanisation 609 and regional climate of Sydney area University of Melbourne Lane, Todd 600 the interaction Investigation of atypical bushfire spread driven by terrain and fire of wind, Atom-photon interactions in biologically relevant media CombinatoricsExact Enumerations in Statistical Mechanics and 600 University of Melbourne Iwan Jensen, Remotely sensed observations for Earth system modelling separation: First-principles computation study of Zeolite for gas design novel molecular sieving mechanism and rational Bureau of Meteorology Leon Majewski, of Nanoconfined FluidsTransport Interfacial Barriers for the 550 Thermonuclear for Transfer I Supernovae Modelling Radiative Type and Core-collapse Explosions of Queensland University Suresh Bhatia, 550 on carbon Modeling electrocatalytic energy conversion reactions based materials by DFT for optimal catalyst design with A numerical investigation of turbulent flow over surfaces 529 spatially varying roughness quantifying controls on Australia-Antarctica divorce: Modelling the plate motions Large scale high accuracy computations for studies of Riemann's as part of the 8th Hilbert problem zeta function, Throughput Phenomics High An Open Source, TraitCapture: pipeline Deciphering the genetic control of diseases Gravitational Lensing Weak Gravity on Cosmic Scales with Testing and Redshift Space Distortions Theory Design of Carbon Based Materials for Density Functional Energy Application LES of high Reynolds number turbulent wall bounded flows University of QueenslandVisscher, Peter University of Melbourne Jason Monty, 500 484

800 700 700 693 Total Total (kSU) Allocation David Karoly, University of MelbourneDavid Karoly, University of SydneyPatrice Rey, Melbourne Institute of Royal Salvy Russo, 820 Technology of Queensland University Elizabeth Krenske, 807 785 Macquarie UniversityOrsola De Marco, 741 Australian National University Ivo Seitenzahl, University of Benjamin Galton-Fenzi, Tasmania 700 Australian National Shin-Ho Chung, University University Ananthanarayanan Veeraragavan, of Queensland CSIROMatthew Chamberlain, 683 University of SydneyJeffrey Reimers, 659 Monash UniversitySergiy Shelyag, Monash University Schellart, Wouter University of NSWAshish Sharma, 644 635 610

Project Title Institution Lead CI, The dynamics of protein-ligand interactionsThe dynamics Australian climate of changes in Mechanisms and attribution extremes University Monash David Chalmers, 835 Land Surface ScienceLand Surface University of NSW Pitman, Andy 846 Numerical Simulations of Microcombustors Computational Investigation of Sodium Gated Ion Channels Modelling of Chemical Systems Including Molecular Excited States, Applications and Molecular Electronics Photosynthesis, of Sydney University Serdar Kuyucak, 665 Metal Nanoclusters as Catalysts for Photoreduction of CO2Metal Nanoclusters as Catalysts for Photoreduction transfer for Hydrodynamical explosion simulations and radiative thermonuclear and core-collapse supernovae Adelaide University of Gregory Metha, 709 solid surfaceAtomistic simulations of nanoscale liquid flow on University of Sydney Luming Shen, 700 Genomic analysis transcriptomics and epigenomicsCoral genomics, Radiative magneto-hyrdrodynamic modelling of interconnected solar interior and atmosphere Australian National University Sylvain Foret, Australian National University Gavin Huttley, 650 676 Modelling the formation of sedimentaryModelling the formation basins and continental margins of Materials and Nanomaterials Prediction of the Properties protein-inhibitor interactions and chemical Theoretical modelling of reactivity flows in expansion tubesSimulation of hypersonic in the era of Common envelope interaction and stellar outbursts time-domain Astrophysics and mixing in the Southern OceanTurbulence University of Queensland David Gildfind, 780 Antarctica and the Southern Modelling of the interaction between Ocean Tasmania University of Nathan Bindoff, Cationic Membrane Voltage-Gated Computational Studies on Channels shiftsprotein structure calculation using pseudocontact 725 University of Queensland Thomas Huber, Change ACCSP Dynamical Ocean Downscaling of Climate Projections 700 WingsAerodynamics of Flapping Low Reynolds Number ADFA Young, John antioxidants computational design of better Mimicking nature: Australia Western University of Amir Karton, 650 Role of subduction zone interface mechanical coupling on 680 subduction dynamics and overriding plate deformation Dynamical downscaling hydro-climatic simulations for water resources planning and management in a changing climate

76 6 Annual Report 2014/15 79 320 320 310 300 298 275 250 Total Total (kSU) Allocation Chennupati Jagadish, Australian National Australian National Chennupati Jagadish, University National Australian Frankcombe, Terry University of NSW University Rita Khanna, Monash UniversityMichael Reeder, 319 315 Technology, of University Peter Jones, Sydney Australian National University Brian Schmidt, of Melbourne University David Karoly, 300 Australian National Thomas Welberry, University Royal Melbourne Institute of Jared Cole, 300 Technology University of SydneyDorian Hanaor, Australian National University Matthew Field, Australian National Graham Hughes, 290 University 292 SydneyTechnology, University of Daniel King, 255 Australian National University Brian Schmidt, 250 University of MelbourneIvan Marusic, Royal Melbourne Institute Michelle Spencer, of Technology 250 Project Title optoelectronic devices Nanostructured phase and solid dynamics in gas phase, Efficient chemical heterogeneous systems Surface Temperature Investigations of High Atomic Level Novel Steel Thermodynamics of Molten Solar Rain anticyclones and the connection to The dynamics of subtropical Australia bushfires in southern heatwaves and drought, of Bio-MacromoleculesThe Mechanical Properties of protein fragments and peptidesHarnessing the bioactivity Institution Lead CI, Transporter ABC in the Hydrolysis ATP Allosteric Control of Catalytic Cycle University of Sydney Marcela Bilek, Monash University Ravi Jagadeeshan, Ib/c Type Multi-dimensional radiative transfer simulations for supernovae Coupled Chemistry Climate Modelling of Stratospheric Ozone Depletion and Recovery 313 314 Model Systems Computation of X-Ray Diffraction Patterns for 3D in search of the source of Paramagnetic spin states on diamond: CSIROTroccoli, Alberto surface noise Activity in Understanding the Origins of Enhanced Photocatalytic Theory Nanostructures Using Density Functional TiO2 doped high-throughput system for identifying genetic variation A robust, from very large genome sequence datasets solar Modelling of high-temperature receivers for concentrating thermal energy systems 318 Wind and Coastal Inundation ModellingSevere ASPECT mantle slab dewatering using Tracking Alloys for use in advanced nuclear Investigation of High Entropy applications Will East coast lows change in frequency or intensity in the future?Australia Geoscience Arthur, Craig University of NSW Jason Evans, Quantum Chemical Modelling of Nanoscale Chemical Processes Macquarie University Craig O'Neill, University of Newcastle Alister Page, simulations for Multidimensional Modelling supernova explosions: Ia explosions Type Quantitative Goldbach Conjecture 270 251 Numerical modelling and application to aquatic Turbulence: 255 250 ecosystem functions Modelling Nanoscale Materials for Sensing and Device Applications Computational investigation of new selective transport materials Deakin University Maria Forsyth, Disc Brake Squeal University of NSW David Harvey, 243 250 ADFA Joseph Lai, 241

450 400 Total Total (kSU) Allocation Evelyne Deplazes, University of QueenslandEvelyne Deplazes, of Queensland University Mark Ragan, 483 Deakin UniversityYang, Chunhui 479 National Australian Megan O'Mara, University 455 Adelaide of University John Bowie, 438 Australian National Andre Rene Offringa, University Geoscience Australia Wu, Wenjun University of MelbourneLars Goerigk, 380 SydneyTechnology, University of Ao, Zhimin 378 364 University of NSWJudy Hart, Monash UniversityFabio Capitanio, 355 343 University of NSWAlejandro Di Luca, 325

Project Title Institution Lead CI, Developing computational methods to improve the accuracy of improve the accuracy of methods to Developing computational obtained from DEER spectroscopy structural data TransportersFree Energy Simulations of Ion Channels and at low The spectral details of extragalactic point sources frequencies University of Sydney Serdar Kuyucak, 405 Virtual Laboratory Marine Design and development of new inexpensive materials for efficient hydrogen production and storage Bureau of Meteorology Justin Freeman, 360 Chemistry at Semiconductor and Oxide Surfaces University of SydneyWarschkow, Oliver 405 TheoryAtomic Collision Coastal OceanographyTheir Role in Oceanic Nepheloid Layers and ADFA Wang, Xiao Hua Subduction with an Tectonics 4-D Numerical Models of Plate Upper Plate Technology Curtin University of Igor Bray, with the MWAVariables and Transients Influence of sea surface temperatures and orography on the development of East Coast Lows 360 346 University of Sydney Martin Bell, 330 Comparative analysis of gene and protein families in genomes families in genomes analysis of gene and protein Comparative from diverse environments AssimilationeReefs EnKF Data Advanced Engineering Materials and Multiscale modelling of Structures substrate recognition protein dynamics, Investigating membrane and transport of malarial drug targetsStructural characterisation dynamic simulation of biofunctional molecular Bioinformatics, fragmentation mechanisms proteins and mass spectrometric What Regulates Star Formation? CSIRO Emlyn Jones, Monash University Sheena McGowan, 448 Australia's climateThe effects of tropical convection on (MODIS) Moderate Resolution Imaging Spectroradiometer Thematic Products 468 Monash UniversityWurster, James Theoretical Quantum Chemistry including Quantum Refinement of University of NSW Nidhi Nidhi, Methods DNA Structures and Development of new Computational Nanoporous membranes for energy applications two- First-principles calculations on heterostructures of 418 dimensional materials for different applications Aegean-Anatolia Collisional SystemUnderstanding the 400 University of Queensland Marlies Hankel, Sydney University of Patrice Rey, 369 Atmospheric Constituents for Climate Trace Assimilation of 362 University of Melbourne Peter Rayner, Bias removal in data assimilation systems for flood forecasting 350 Monash University Pauwels, Valentijn Wind ClimatologyWRF Wind Generation Project: ARC Linkage 340 University of Queensland Michael Hewson, 323

78 6 Annual Report 2014/15 81 175 170 165 145 Total Total (kSU) Allocation LiangChi Zhang, University of NSW University of LiangChi Zhang, National UniversityAustralian Elmars Krausz, 180 181 Australian National Stephen Williams, University National Australian Marcel Cardillo, University Griffith UniversityWang, Yun National Australian Anatoli Kheifets, University University of QueenslandKatherine O'Brien, 170 University Xiaolin Wang, of Wollongong 162 Monash UniversityKris Ryan, 161 ADFA Colin Simpson, Monash University Garoni, Timothy Monash UniversityAilie Gallant, 161 158 Monash UniversityPaul Cally, 160 ADFA Andrew Neely, 157 Tasmania University of Matthew King, 152 University of QueenslandNatalie Connors, UniversityAustralian National Tregoning, Paul 150 150 150 University of NSWGraham Ball, 150 Australian National Naomi Haworth, University 146 tegies with climate change Project Title metallic of metal/semi-conductor/bulk Multiscale mechanics and graphene-polymer mixed lubrication systems, glass (BMG) composites in carboxylate ligands coordinated Vibrational Frequency changes of the metal oxidation state to manganese as a function semiconductor latticesLocating defects in doped Materials out of Equilibrium Computer Simulation of Glassy evolutionaryUnderstanding patterns of and ecological diversification Australian National University Scott Medling, and computational design of perovskite Theoretical understanding solar cells Institution Lead CI, 175 Theory of multiple atomic ionization Anatomy of Social Media PopularityThe health: Impacts of environmental change on coastal ecosystem application of the eReefs coupled hydrodynamic-biogeochemical model molecular Searching for highly conductive molecules for future circuits and sensors jets moving The evolution and stability of vortex rings and synthetic parallel to a flat plate National UniversityAustralian Lexing Xie, jets on fire Numerical investigation of the impact of low-level behaviour analysis and application of Monte Carlo methods in Design, 165 statistical mechanics heat Mesoscale modelling of urban landscapes for assessing adaptation and mitigation stra Biology needs rheology interior structure Numerical modelling of MHD effects and sunspot and dynamics flight and Fluid-thermal-structural interactions for high-speed propulsion Theoretical study of 2D and 3D topological materials high resolution Antarctic Ice Sheet through Reconstructing the numerical modelling Molecular Dynamics Investigation of Epitopes and Biosurfactant Structural Stability University of NSW Anh Pham, Analysis and interpretation of mass redistribution on Earth derived Monash University Ranganathan, Prabhakar from space gravity observations Ab Initio Studies of Inorganic and Organometallic DFT and Complexes and Drug DNA complexes 155 Australian ContinentAssessing geothermal energy potential for the Australia Geoscience David Lescinsky, 150 How does insulin work? 145

240 240 225 210 194 185 Total Total (kSU) Allocation Christopher Blake, Swinburne University of Swinburne University Blake, Christopher Technology of Swinburne University Blake, Christopher Technology of NSW University Narjes Gorjizadeh, Monash UniversityKris Ryan, 240 Australian Nuclear Simon Middleburgh, Organisation Technology Science and 228 University of SydneyHareth Mahdi, University of QueenslandDavid Parkinson, Macquarie UniversityKevin Cheung, Kei-Wai 224 221 220 Australian National Robert Stranger, University Monash UniversitySteven Siems, University of SydneyWilliamson, Nicholas University of SydneyWidmer-Cooper, Asaph 206 208 University of SydneyChris Ling, 203 Australian National University Jason Bragg, 203 Australia Geoscience Matthew Garthwaite, 200 Western University of Marcin Sokolowski, Australia 200 University of Altarawneh, Mohammednoor Newcastle

Project Title Institution Lead CI, Improving cosmic expansion and neutrino mass measurements mass measurements expansion and neutrino Improving cosmic with new simulations Functionalized graphene for next generation nanoelectronicsFunctionalized graphene accident Developing a materials understanding of the silicide an atomic scale study tolerant fuels: University of MelbourneCervenka, Jiri 225 ANU Mathematical Sciences Institute Novel methods for phylogenetic inference using genome-scale data Australian National University Andrew Chew, 200 Swinburne Testing the cosmological model at low redshift: Mock model at low redshift: the cosmological Testing Swinburne surveys Taipan catalogues for the 6dF and reaction between complex carbon- Atomic scale modelling of phase towards a novel approach for bearing materials and metallic for sustainable environment recycling waste polymers and Supramolecular ChemistryComputational Bio-inorganic characterising shear forces in Shear induced platelet aggregation in-vitro geometries University of NSW Ian Dance, Designing Better Catalysts Dark Energy Gravitational Lensing in Coupled Dark Matter: 233 Cosmologies tests of f(R) Using numerical simulations to enhance cosmological gravity Landfall Structure, Cyclone Formation, Tropical Numerical Study of associated with Land-surface Variability Processes and Climate Changes Tasmania University of Yates, Brian Magnetotelluric and Electrical data inversionTD-DFT Studies of Organometallic and Metal Cluster DFT and Systems Australia, Simulations of wintertime storms across Southeast 225 and the Southern Ocean Tasmania Australia's in Purging and destratifying of thermal and saline pools inland rivers Australia Geoscience Jingming Duan, Establishing Interactions and self-assembly of colloidal nanorods: design rules for creating new nano-structured materials to A combined experimental and computational approach understanding and developing solid-state ionic conductors 210 Dynamics of DNA Clamps and Clamp LoadersGeodetric research to measure surface deformation of the Australian continent Wollongong University of Aaron Oakley, Simulation of expected sky signal for the BigHorns project Fundamental Understanding of the Role of Singlet Molecular 200 Oxygen in Spontaneous fires Analysis of complex genomes University of Queensland David Edwards, 184

80 6 Annual Report 2014/15 83 95 90 88 84 100 Total Total (kSU) Allocation Zbigniew Stachurski, Australian National Zbigniew Stachurski, University University of SydneyAlejandro Montoya, 93 Australian National Nicolas Cherbuin, University University of Tomljenovic-Hanic, Snjezana Melbourne Royal Melbourne Institute Suresh Bhargava, of Technology Australia Geoscience David Lescinsky, Tasmania University of David McGuinness, 80 80 CollegeAvondale Gemma Christian, 80 University of NSWMichael Paddon-Row, 80 Gleb Beliakov, Deakin University Gleb Beliakov, University of NSWAssadi, Al Mohammad University of Queensland Croll, Tristan 100 100 Technology tion tree National UniversityAustralian William Foley, 95 Scale Resolving Turbulence Simulations of Multi-layer Orthogonal- Turbulence Scale Resolving Arrays offset Plate of Clay Structures for CO2 carbonation Modelling Dehydroxylation applications processing DEM SRTM The evolution of the mitochondrial genome Behavior in Fluid Bed ReactorsTransfer Flow and Heat resonance and ageing a magnetic cognition, Brain structure, imaging investigation methodPiezoelectric bone remodeling analysis by finite element University of NSW Zongyan Zhou, Australian National University Qing-Hua Qin, University of Sydney Madeleine Beekman, Diamond-based quantum devices National Remote Sensing Processing Facility 90 Australia 92 Geoscience Wilson, Nerida Australian Solar Energy Forecasting System 92 ions (As and Hg) An investigation on the interaction of heavy metal with Surface Enhanced Raman Spectroscopy materials Conformational regulation of enzyme function 93 CSIRO Edward King, Design using genetic algorithms University of NSW Merlinde Kay, Services DeliveryWeb EODS Primary production in space and time Monash University Ashley Buckle, Tough2- Multiphase fluid flow and heat transport modelling with MP Applied and Alpha Olefins Mechanistic Production of Linear 84 Investigations 85 Quantum Chemical Molecular Properties University of NSW Mark Hoffman, 83 Computational investigation of oxygen activation in metalloenzymes Macquarie University Bradley Evans, Australia Geoscience Aaron Sedgmen, TurbomachinerySupercritical CO2 Air Quality ProjectionFuture 83 Computational Quantum Chemical Studies of Stereoselectivity of Trobe 80 La Wilson, David Organic Reactions 80 University of Queensland Ingo Jahn, 80 CSIRO Martin Cope, 80 80 Project Title for studies of Riemann's high accuracy computations Large scale zeta function polymer chemistry of high temperature Atomistic investigation for and sustainable environment novel recycling solutions Therapeutics and Vaccines of Ebola Aided Design Computer transitions in the insulin receptor Investigation of structural Flinders University Nikolai Petrovsky, Australia's founda Eucalyptus: Whole genome analysis of 100 Institution Lead CI,

125 105 100 Total Total (kSU) Allocation Sergio De Luca, University of NSW University Sergio De Luca, of Queensland University Stefano Bernardi, Western of University Dino Spagnoli, Australia 130 131 University of NSWYi, Jiabao Tasmania University of Petra Heil, Australian National University Kam, Timothy 125 University of SydneyAhmad Jabbarzadeh, 123 125 121 James Cook UniversityRosalie Hocking, 120 University of NewcastleEric Kennedy, University of NewcastleMarian Radny, Royal Melbourne Institute Dougal McCulloch, 110 of Technology 106 University of NewcastleJuita Juita, University of SydneyArmfield, Steven 102 Australian National Account, Alistair Rendell University 101 Technology Curtin University of Andrew Rohl, 100

Project Title Institution Lead CI, Structural and functional simulations of protein drug targetsStructural and functional of fluctuating hydrodynamics for fluid- Particle-based simulations micro/nano scales structure interactions at of Sydney University William Church, 136 eReefs Marine Modelling GBR1eReefs Marine CSIROBaird, Mark 138 Mesoscale Modelling of Rainfall for Sea Non-equilibrium plasma conversion of toxic halogenated value added compounds and waste halogenated refrigerants to polymers CSIRO Marie Ekstrom, 111 Small molecules for organic photovoltaics and light emitting diodes for organic photovoltaics Small molecules Technology of Curtin University Ante Bilic, 142 systemsModelling of multi-layered and adaptive structural University of Sydney Gianluca Ranzi, 117 Australian Water Resource Assessments Calibration TestAssessments Calibration Resource Water Australian CSIRO Dave Penton, 118 Large scale online learning with a mixed regularization model Separation of ions and small molecules using Molecular Dynamics Separation of ions and small simulations AlGaN/ Modelling surface electrochemistry-transport coupling in GaN-based sensors and spin manipulation in oxide Mechanism of ferromagnetism diluted magnetic semiconductors Analysis and interpretation of space gravity observationsAntarctic sea-ice kinematics derived from high-resolution (East) satellite imagery Australian National University Tregoning, a new Paul and Forward Guidance Monetary Policies: Traps Liquidity computational dynamic game perspective 125 of Molecular and Dissipative Particle Dynamics Simulations Polymeric Systems Extended Hydrological Prediction modelling to reaction Catalysts for Clean Energy from experimental data mechanisms Hybrid 2D Materials Bureau of Meteorology David Kent, 120 Surfaces, Catalytic Reactions on Metal-oxide and Metal-chloride and Hybrid Molecular Electronics on Semiconductor Surfaces Electronic structure of boron nitride and other novel coating systems SydneyTechnology, University of Ford, Mike Catalytic Reactions in the Gas Phase and on Metal-oxide and Metal-chloride Surfaces 118 Access MemoryResistive Random Direct simulation of transition for natural convection flow in inclined differentially heated cavities Quantum SimulatorAdditives on Realistic Modelling of the Effects of Solvent and Crystallisation Australian National University Elliman, Robert 101 Wollongong University of Willy Susilo, 101

82 6 Annual Report 2014/15 85 50 50 48 43 Total Total (kSU) Allocation Amanda Karakas, Australian National Australian Amanda Karakas, University Joe Hope, Australian National UniversityAustralian Joe Hope, 50 University of NSW LiangChi Zhang, Australian National University Abram, Nerilie 50 50 Technology, University of Peter Jones, Sydney University of NSWSteven Phipps, Australian National Michael Collins, University 50 University of QueenslandWentrup, Curt 47 Australian National UniversityAntonio Tricoli, CSIROBrad Wells, 45 University of SydneyVassallo, Tony University of Anastasios Papaioannou, Sydney 44 University of NSWTian, Fangbao 45 41 Project TitleCFDMECHDiscoveryDark Matter Comparative genomics pap056 molecular dynamicsHPC for fluid dynamics and of post-AGB stars and planetaryThe heavy element composition nebulae Deakin University Gao, Weimin Institution Lead CI, CSIRO Papanicolaou, Alexie Monash University Csaba, Balazs University of NSW Barber, Tracie 51 52 51 55 BEC manipulation through pulse sequences and quantum BEC manipulation through feedback control of hydrogen storage materialsImproving capacity and stability metal/semi-conductor/bulk metallic Multiscale mechanics of University of NSW Judy Hart, lubrication and graphene-polymer mixed glass (BMG) systems, composite Electron beam induced etching and depositionAnnular Mode changes over the the drivers of Southern Testing last millennium Atomistic Modelling of Carbon Nanostructures 50 Waythe Milky Scintillation and the structure of turbulent gas in SydneyTechnology, University of Mike Ford, Structure-function analysis of PfL-M17 for the discovery of anti- University of Sydney Paul Hancock, Analysis of DNA Repair Enzyme MutS malarial drugs/ MD 50 Self-assembly of Polyphiles via Espresso SimulationsTechnology Curtin University of Nigel Marks, Australian climate variability and Understanding the drivers of change 50 50 emitting devicesDFT study of Diamond/AlN heterojunctions for UV UniversityAustralian National Stephen Hyde, University of NSW Francois Ladouceur, Molecular Potential Energy Surfaces by Interpolation 50 intermediates and Theoretical calculations on reactive molecules, prebiotic chemistry pathways 50 reactionsAccurate activation energies for aqueous CO2/amine Multiscale Simulations of Polymeric Systems CSIRO Jim Smitham, Analysis Simulation of Nanoparticle Films Self-Assembly for Breath and Non-Invasive Medical Diagnosis Investigation of nanoporous materials for carbon dioxide capture and catalysis Modelling the interactions and influences of organic compounds in zinc-bromine redox flow battery systems University of Sydney Ahmad Jabbarzadeh, Nonlinear Dynamics of Ocean Currents 47 Insulin-IR complex 46 Fluid-structure Interactions and Complex Flows in Biological and Biomedical Systems ADFA Andrew Kiss, 43

60 60 60 Total Total (kSU) Allocation Seth Olsen, University of QueenslandSeth Olsen, Monash UniversityJason Beringer, 79 National UniversityAustralian Riyan Cheng, 75 70 Murdoch UniversityDavid Henry, University of SydneyJeffrey Reimers, University of SydneyNicolas Flament, 70 68 Australian National University Peter Gill, 67 65 Monash University Swamy, Varghese Monash UniversityYan, Wenyi 62 Western University of Elena Pasternak, Australia 61 Australian National Peter COMP3320, University University of MelbourneWille, Uta Australian National Johannes Zuegg, University 60 Monash UniversityWebb, Geoffrey 56

Project Title Institution Lead CI, Computational Electronic Structure of Animal Pigment Molecules Animal Pigment Electronic Structure of Computational Importance of Strategic National Machine Learning for Computer VisionMachine Learning for Computer and Dioxides Titanium First-Principles Modeling of Functional Hybrid Metalorganic Perovskites structures Deformation and failure of constrained fragmented National UniversityAustralian Stephen Gould, 63 Landsat Dynamic Land Cover Scientific Analysis and Optimization of Large-scale Performance Simulations Australia Geoscience Leo Lymburner, 60 Molecular Dynamics Study of Gas Storage and Transport in CoalsTransport and Study of Gas Storage Molecular Dynamics CSIRO Junfang Zhang, meso-scale models the role of urban Urban areas in regional and change and adaptation/mitigations climate parameterizations, strategies biomolecular systemsComputer simulations of approach for novel genetic A powerful mixed effect model of multiple complex traits discoveries using joint analysis ChemistryComputational Quantum 76 From Catalysts Nanoscale Interactions: Nanoscale materials and Wollongong University of Yu, Haibo through to Hydrophobic Soils SupplyWater Climate Change Impact on Southeast Queensland to protein Application of quantum electronic-structure methods CSIRO Cai, Wenju crystallography and photosynthetic function large-scale Understanding the deep driving forces of Earth's 73 topography through time Monash University Alan Chaffee, Solid Oxide Fuel CellsDevelopment and application of new quantum chemistry algorithms Electrochemical Conversion of CO2 and N2 70 69 Optimization and structural analysis for additive manufacturing and maintenance Monash UniversityAzofra, Luis Miguel SkyMapper and the Southern Sky Survey University of Newcastle Kennedy, Eric AustraliaEpeirogeny and basin dynamics of 63 65 Australian National University Brian Schmidt, A Computational Study of Dual Orbital Interactions in Radical Addition Reactions Cyclization and 60 Australia Geoscience Karol Czarnota, Theoretical Study of Perovskite Solar CellsModulating the function and structures of bio-macromolecules by small molecules Vicsek ModelsInformation flow in 60 Learning from big data with generative and discriminative strategies University of Melbourne Zhou, Yecheng 60 Charles Sturt University Bossomaier, Terry 59

84 6 Annual Report 2014/15 87 28 25 20 Total Total (kSU) Allocation Matthew Arnold, University of Technology, University Matthew Arnold, of Technology, Sydney Gregory Wilson, GregoryCSIRO Wilson, Nuclear Science Australian Greg Doherty, Organisation and Technology Australian National University Liang, Weifa 26 25 Monash UniversityAmin Heidarpour, 23 University of New EnglandCedric Gondro, 20 Griffith UniversityEvan Gray, Australia University of South Gujie Qian, Geoscience AustraliaJohn Wilford, 20 20 Australian National Nicolas Cherbuin, University 20 Project Title and metamaterials of plasmonic nanoantennas Optimization Institution Lead CI, Electronic Structure of Organic/Inorganic Dyes for Photovoltaic Dyes for Photovoltaic of Organic/Inorganic Electronic Structure Applications cosmogenic berylliumHigh resolution studies of (10Be isotopes Antarctica cores, and 7Be) in Law Dome ice Australian Grid for the Least cost energy pathways Influential Communities in Large- Algorithms for Finding Efficient Scale Networks into the CICE/ACCESS modelIntegration of wave-ice interactions Adelaide of University University of Melbourne Luke Bennetts, Roger Dargaville, Bulk Metallic GlassesMaterials Design for Self-toughening of Hollow Fabricated Columns with High The Structural Behaviour and Double Skin Concrete-Filled Columns Tubes Strength Steel University of SydneyTang, Chunguang with Corrugated Steel Skins 25 24 TurbulenceQuantum ApplicationsAdvanced Photovoltaic Nanostructures for 24 compositesNacre inspired structures based on ceramic/polymer Monash University Andrey Molotnikov, Automation Group Modelling and Transportation University of Sydney Ross McPhedran, Kinematic study of Galactic bulge planetary nebulaeMolecular dynamics simulation of polymers 21 Australian Landsat-MODIS Blending InfrastructureDeveloping an 22 ADFA Abbass, Hussein CSIRO McVicar, Tim Macquarie University Quentin Parker, Selection and Estimation of Polygenic Epistatic Networks Evolution, Traits in Quantitative Monash University Simula, Tapio ionsInvestigating the structures and energetics of molecular materials DFT studies of structure-function relationships in of NSW University Saeed Masoumi, containing hydrogen 21 University of Melbourne Evan Bieske, Analysis for Brain MRI imagesAutomatic Corpus Callosum Shape University of Canberra Girija Chetty, 22 Effect of Na and K on solar cell absorber materials Cu(In1-x,Gax) 21 A first-principles study Se2: 21 21 20 Data mining and geostatistical modelling for geoscience applications Modelling of micro-flows in micro-devices 20 An investigation of ageing brain structure in health and disease Spherical geometry in chemistry and physicsQuantum Chemical Modelling of Biomolecular SystemsAssimilationRegional Data ADFA Jong-Leng Liow, ACCSP and PACCSPAustralia University of South Thilagam Lohe, Australian National University Pierre Loos, 20 20 20 CSIRO Chaojiao Sun, Tasmania University of Michael Grose, 18 18

40 40 40 30 Total Total (kSU) Allocation Shibo Kuang, University of NSWShibo Kuang, Monash UniversityDouglas MacFarlane, 41 Australian National Andrey Sukhorukov, University Australian National Brendan McKay, 40 University University Griffith Debra Bernhardt, University of QueenslandHuilin Xing, 40 40 Australian National University Matthew Hole, 40 CSIROThomas Poulet, Australian Research Other Xuming He, Institute 40 University of NSWWen, Wei Australian National Cedric Simenel, University 31 University of MelbourneKenneth Crozier, Wollongong University of Stephen Blanksby, 30 30

Project Title Institution Lead CI, The structure of the MACPF/CDC giant pores association heritability and genome-wide A project on voxelwise, of human brain structure and function study (vGWAS) Monash University Michelle Dunstone, 31 Numerical study of transport, separation, and chemical reaction of and chemical separation, of transport, Numerical study flow systems particles in multiphase EQRMApplications in Equilibrium and Instabilities of Computational Advanced Plasma Confinement Geometries Space weather modellingAustralia Geoscience Mark Leonard, 40 Microscopic and Macroscopic Studies for Nuclear Reactions Bureau of MeteorologyTerkildsen, Michael 31 The catalytic oxidation of ammoniaThe catalytic oxidation of the Towards to sustainable chemistryComputational approaches prediction of electrochemistry media and reaction kinetics in ionic University of Sydney Alejandro Montoya, 40 redshift galaxiesAlpha and stellar emission from high Lyman University of Sydney Luke Barnes, 40 Electronic Structure of High Oxidation State Complexes University of Queensland Mark Riley, Catalysis and Organometallic Chemistry 32 Tasmania University of Allan Canty, 30 Studying the Dynamics of Multiple PlanetaryStudying the Systems University of NSWWittenmyer, Robert Photonic Nanostructures Active Control of Light in Extremal graph theory 41 and dehydrogenation of complex Mechanisms for hydrogenation borohydrides aluminium hydrides and Dynamics Massively Parallel Computing for Coupled Fluid Flow using LBM Measuring the laws of Nature across the Universe University of NSWWebb, John Potential Field Modelling in Spherical Coordinates with multiphysics the unconventional resources challenge Tackling simulations Video Large-scale Holistic Scene Understanding in 40 Australia Geoscience Ross Brodie, AEM dataInversion 40 Computational Studies for Intelligent Organic Reaction Design Monash UniversityThompson, Christopher CSIRO Alan Ley, Subtle quantum mechanical forces of ions in solution 30 Nanophotonic devices based on semiconductor and plasmonic materials Computational Investigation of the Chemistry of Reactive Australian National University Parsons, Drew Intermediates Simulation of Photonic Nanostructures 30 37 Australian National University Choi, DukYong 30

86 6 Annual Report 2014/15 89 10 10 Total Total (kSU) Allocation Bogdan Dlugogorski, Murdoch University Murdoch Bogdan Dlugogorski, University Macquarie Damian Moran, 10 Technology of Curtin University James Hane, 10 10 Technology, of University Michael Cortie, Sydney Peter Scarth, University of Queensland University Peter Scarth, CSIRORobert Bell, 10 Australian National Steve Blackburn, University CSIRO Ziehn, Tilo Monash UniversityYan, Wenyi 10 10 10 University of SydneySascha Brune, 8 University of SydneyAbbas El-zein, ADFA Annemieke Mulders, 6 Monash UniversityEhsan Bafekrpour, 6 6 riculturally important plants, pathogen pathogen riculturally important plants, Project Title and on Metal-oxide and in the Gas Phase Catalytic Reactions Surfaces Metal-chloride Assimilation eMast Model-Data Structure Computations to the Solution Applications of Electronic Problems of Molecular-Scale ag Bioinformatic analysis of and pests remodeling and deacetylase complexStructure of the nucleosome of Sydney University Joel Mackay, with model surfacesInteraction of wood extractives Alloys for advanced nuclear Investigation of High Entropy applications CSIRO Barrett, Damian Institution Lead CI, Tasmania of University Karen Stack, 10 10 10 Monitoring Landscape Scale Vegetation State and Trend from Trend State and Vegetation Monitoring Landscape Scale archives ALOS Landsat and and Trends Rainfall Australian Aerosols in Quantifying the Role of Rainfall Variability ACTA Flood Mapping Framework for the High performance runtime and X10 programming language: scientific applications Australian and Southern Ocean Investigating Carbon Cycling in the Region Advanced Composite Optimising the Damage Resistance of Aerostructures Subjected to Impact Loading AnalysisIntegration Site Australian National University VanDrie, Rudy Defects in Germanium and Silicon 10 OpenSeesDevelopment of earthquake fragility model using Australian Continental Carbon BudgetThe Australia Geoscience Hyeuk Ryu, The role of mantle convection for present day lithosphere dynamics Particle PhysicsQuantum Lattice Models in Condensed Matter and University of NSW Chris Hamer, Computational design of dehalogenase enzymesADFA Timmers, Heiko Modeling of sea level change and variability in the Pacific Macquarie University Shoba Ranganathan, CSIRO Haverd, Vanessa 8 Theory for Thermo-Hydro-Mechanical An Experimentally-Validated Geosynthetic Composite Lining Systems under Low Pressure and High Temperature CSIRO Xuebin Zhang, 10 CSIRO Peat, Tom 7 X-Ray BurstsInvestigation of the electronic structure of highly correlated electronic systems especially of novel multiferroics by density functional methods 8 Simulation of Underground Coal Mines and Mineral Grinding 8 Static and dynamic analysis of Z-machine reinforced non- pneumatic tires with high energy efficiency CSIRO Chandana Jayasundara, Agents from Natural ProductsAntioxidant Development of 7 7 Intersect Joachim Mai, 6 Monash University Alexander Heger, 6 6

15 14 10 Total Total (kSU) Allocation Tony Vo, Monash University Monash Vo, Tony Wollongong of University Nicholas Jones, 16 18 of NSW University Ajami, Hoori Australian National University Dijk, Van Albert Australian Shankar Kalyanasundaram, National University 15 15 Australian National Kylie Catchpole, University Monash UniversityWong, Bob 12 University of SydneyAbbas El-zein, CSIRODewi Kirono, University of SydneyLuming Shen, 11 Macquarie UniversitySammy Diasinos, 11 Swinburne University of Todd, Billy 11 Technology 11 ies for Rural Livelihoods in Nusa

Project Title Institution Lead CI, 4D Numerical Models of Lithospheric and Mantle Interaction Solar Trough Wind Engineering Effects of Parabolic CFD Study of Collectors Monash University Rebecca Farrington, 12 Finite-element and discrete study of pipe belt conveyors and discrete study of Finite-element vortex elucidating shear- hexagon to Earth's polar From Saturn's in rotating flows layer instability Monash University Qijun Zheng, 18 GlazingVacuum Insulating New Generation High Strength Hydrologic Models for On the Performance of Integrated Fluxes Under Scenarios of Climate and Simulating Land Surface Land Cover Change University of Sydney Marcela Bilek, 15 Nanoplasmonic Solar Cells Modelling Porous Breakwaters using SPH method Gambusia The transcriptome of the Eastern mosquitofish, holbrooki Monash UniversityValizadeh, Alireza diodes)Small molecules for OLEDS (organic light emitting CSIRO Melissa Skidmore, 12 12 General Share for User Code Development and Testing Development and General Share for User Code CSIRO Bell, Robert Spectroscopy of gas-phase ions 16 ESG CMIP5 data processing pipelineWollongong University of Stephen Blanksby, ApplicationsData Cube Rangelands and Crop Mapping 15 CSIRO Erwin, Tim CSIRO Matt Paget, 13 12 Computer Simulation of Nanofluidic Systems Water property rights in regulated riversWater 3-D chemical transport modelling to The use of state-of-the-art chemistryunravel the effects of atmospheric on climate Earth Observation and InformaticsAustralian National University Rupert Grafton, 17 assimilation and The next generation of environmental model-data forecasting systems CSIROWoodcock, Robert Finite Element Modelling of Engineering Systems CyclonesTropical WRF simulations of DesignTax Theory to Tax Applications of Optimal Advanced 16 of Sydney University Apps, Patricia Macquarie University Thomas Loridan, Plasmonic based components for Nanotechnology 15 14 Monash University Malin Premaratne, Climate Adaptation Strateg Indonesia Barat Province, Tenggara 12 Multiscale Simulation of Unsaturated Soil Response to Impact Loading Bayesian risk forecasting with flexible volatility models weight saving alternative for aircraft flaps and slats A novel, utilizing no moving components Multiscale simulation of particle flows University of Sydney Richard Gerlach, 11 SydneyWestern University of Haiping Zhu, 10

88 6 Annual Report 2014/15 91 3 2 2 1 Total Total (kSU) Allocation Ronald Cox, University of NSW University Ronald Cox, National UniversityAustralian Stephen Sagar, 4 University of NSWThomas, Torsten 4 4 Australian National Michael Hutchinson, University University of NSWClaudio Cazorla, 3 CSIROJorgen Frederiksen, University of MelbourneNaida Lacevic, Australian National William Roberts, University 2 Australian National Giampiero Iaffaldano, University 2 University of NSWMoninya Roughan, 1 University of Southern Bradley Carter, Queensland Project Title GCM output for IPCCCSIRO Mk3.6 Theoryand Lattice Gauge of Condensed Matter Lattice Models ASTER satellite imagery University of NSW Bursill, Robert wave hindcast dataset for southeastern A high-resolution 60-year Australia BathymetryWater Retrieval Shallow Parallel Implementation of from Earth Observation Imagery Science LaboratoryWeather Climate and CSIRO Robert Bell, 4 sequencing data for microbial Assembly of next-generation metagenomes Atomic PhenomenaTheories in of Unification Tests Institution Lead CI, Conformational Stability in Neurodegenerative Diseases CSIROWoodcock, Robert Thermochemical Properties of Small MoleculesSpectroscopic and Bureau of Meteorology Pugh, Tim University of Sydney George Bacskay, and Surface Analysis and Modelling of National Scale Landscape of NSW University Victor Flambaum, CSIRO Vidana Epa, Climate Data 4 Simulation fluid flow through NFR energy Rational design of novel multiferroic materials for harvesting and energy efficiency 4 4 4 Analysis of Land Surface models Protocol for the 4 ApplicationsAeronautical Fluid-Structure Interaction for AnalysisCSIRO ICT Social Media 4 Transformationq-Hypergeometric function University of NSWAbramowitz, Gab University of SydneyVio, Gareth University of NSW Abdul Shaik, and Changing Variability Attribution and Projection of Climate Systems Weather in nanosensors Elucidating molecular origin of energy dissipation large-scale molecular dynamics simulations via high-fidelity, Genomics Eucalyptus Woodland 3 2 Australian National University Gary Bosnjak, Wide Field Spectrograph 3 CSIRO Milne, David Numerical simulations of the coupled plates/mantle dynamics 2 Photocatalysis of transition metal doped substrates Australian Current Advancing dynamical understanding in the East Optimising the ocean observationprediction effort and MD simulation for DEJ Lab University of New EnglandAndrew, Rose CSIRO Lambropoulos, Nicholas Quantum mechanical modelling of molecular structures of inulinAustralia University of South Andrea Gerson, Sparse Sieve Density Estimation 2 in Planetary Systems Weather 2 Space 1 Annuities in Entrepreneurship Model and Tax Estate 1 University of Sydney Rima Chaudhuri, Australian National University Cagri Kumru, University of Sydney Artem Prokhorov, 1 1 1

5 5 Total Total (kSU) Allocation Jorgen Frederiksen, CSIROJorgen Frederiksen, University of NSWMichael Banner, 4 4 Jing Fou, Monash University Jing Fou, of Sydney University Thomas Balle, Australian National Benjamin Schwessinger, University National UniversityAustralian Charles Miller, 6 6 5 National Australian Manab Sharma, University Southern Cross UniversityAndrew Rose, 4

Project Title Institution Lead CI, Climate projections and SST driversAtmospheric and Dynamical Subgrid-scale Parameterisations for Oceanic Models Statistical Image Processing of Remotely Sensed Data CSIROWatterson, Ian CSIRO Peter Caccetta, 4 4 Constructing a Coupled Economic-Climate System Model CSIRO Ian Harman, - HYSPLIT IntegrationTAPPAS shallow water Computational study of 3D breaking deep water, and shoaling water waves Numerical simulation of multi-material flows 4 CSIRO Petar Liovic, CSIRO Kerryne Graham, 4 4 Modelling sea level extremes in response to global warmingTasmania University of Frank Colberg, 4 Improving hydrological processes in CABLE land surface scheme CSIRO Francis Chiew, 4 Remote Sensing of Inland Water QualityWater Remote Sensing of Inland CSIRO Erin Hestir, 4 Spectral Wind-Wave DevelopmentWind-Wave Spectral Network-free stochastic kinetic From molecules to minerals: modelling of iron oxide formation in aquatic environments University of NSW Russel Morison, WIRADA 2.2 Gridded Foundation Data Sets 4 CSIRO Edward King, 4 The AUStralian project (AURA) community ocean model ReAnalysis The CSIRO OKane, Terry ICTIS science support project 5 Australia Geoscience Duncan Gray, 4 Machine Learning and Natural Language Understanding and Natural Language Machine Learning interactions based and modelling of cell-material Reconstruction electron imaging on high resolution Macquarie University Mark Johnson, 6 Monash Partner Share Management Project Monash University Paul Bonnington, Modelling oxidative degradation of natural products 5 CSIROWinkler, Dave 4 Bluelink III bonding situations through Interrogation of novel Metal-boron computational chemistry Syntax-aware Language Modelling University Macquarie Matthew Honnibal, Wind and Solar Energy SourcesSimulation of CSIRO Graham Symonds, 5 CSIRO Christopher Russell, 5 4 Computational modeling of allosteric binding sites in nicotinic Computational modeling acetylcholine receptors virulence The Evolution of stripe rust war fighters? Evidence from two What makes states good centuries of military engagements Natural Resource InformationVentilationDecadal Changes in Southern Ocean Australia Geoscience Chris Inskeep, University of NSW Mark Holzer, HPCLarge geospatial national wide data processing with 5 5 CSIRO Chen Hoofa, 4

90 6 Total Project Title Lead CI, Institution Allocation 6 (kSU) Gait generator for humanoid robots Chao Chen, Monash University 1

Koala genome project, genome annotation Denis O'Meally, University of Sydney 1

Direct geothermal systems ground heat exchangers modelling Guillermo Narsilio, University of Melbourne 1

Engineering Materials simulation Hamid Valipour, University of NSW 1 Delivering real-time water management information and regional crop water use productivity benchmarking across the cotton Jamie Vleeshouwer, CSIRO 1 industry using IrriSAT Aboriginal Child Language Acquisition Jane Simpson, Australian National University 1

Population genomics of psyllid-induced eucalypt dieback Markus Riegler, University of Western Sydney 1 Electronic & Thermodynamic Properties of Hybrid Organic- Nicholas Lambropoulos, CSIRO 1 Inorganic Nanostructures Fire activity modelling for use in smoke predictions Sean Walsh, University of Melbourne 1 Molecular dynamics simulation of interphase precipitation in metal Weimin Gao, Deakin University 1 alloys Quark Gluon Plasma in Lattice QCD: From Big Bang to Small Bang Mushtaq Loan, Australian National University 0.8

Control Strategies of Surface Quality of Stainless Steels Zhengyi Jiang, University of Wollongong 0.8 Understanding the nature of abrupt regional shifts in a changing Roger Jones, Victoria University 0.7 climate The Nonlinear Dynamics of gait Analysis David Miron, University of New England 0.6

Calculation of social network centrality measures using R Jenny Jiang, University of NSW 0.6 The hunt for Ribonucleic Acid riboswitches and genetic sensors of Christopher Cazzonelli, University of Western 0.5 metabolic flux in plants Sydney Computer-intensive statistical methods Hanlin Shang, Australian National University 0.5

De novo genome assembly using pacbio long reads James Hane, Curtin University of Technology 0.5

NeuRA bipolar test project Janice Fullerton, University of NSW 0.5 Effective implementation of payments for environmental services Jeff Bennett, Australian National University 0.5 in Lao PDR Determination of potential satellite calibration sites by analysis of Michael Caccetta, CSIRO 0.5 the Australian Landsat data archive (or alternatively GA Datacube) Implementation of IDL Virtual Machines for satellite-image Petra Heil, University of Tasmania 0.5 processing Structure and Reactivity of Coinage Metal Nanoclusters Richard O'Hair, University of Melbourne 0.5

ACCESS UM Modelling Martin Dix, CSIRO 0.4 Theoretical Study on Chlorophyll Modification and Its Spectral Min Chen, University of Sydney 0.3 Extension in Oxygenic Photosynthesis Uncertainty quantification algorithms for acoustic and Stuart Hawkins, Macquarie University 0.3 electromagnetic models Brendan Mackey, Australian National WildCountry Science Project 0.1 University