A PILOT INITIATIVE for EGI-XSEDE COLLABORATION Laganà A

A PILOT INITIATIVE FOR EGI-XSEDE COLLABORATION Laganà A. Dept of Chemistry, Biology & Biotechnologies, PG, IT A PROPOSAL FROM THE CMMST (Chemistry, Molecular, Materials Science and Technologies) COMMUNITY: implement a Synergistic High- Throughput&Performance Universal Molecular Simulator as a service for scientists and technologists

1 EGI-InSPIRE RI-261323 www.egi.eu The goals of the EGI-CMMST community THE GOALS wImplement a SYNERGISTIC (collaborative/competitive) HW, SW, MW work-model for molecular sciences & technologies computing wOffer a SERVICE for new discoveries by means of extremely accurate (quantum), efficient and versatile multiscale real-like SIMULATOR operating on distributed platforms

FOR THIS PURPOSE IN EGI WE ARE STRUCTURING theEuropean CMMST (Chemistry, Molecular, Materials Sciences & Techno-logies) VRC (Virtual Research Community) based on: - EGI National Grid infrastructures, resources and operations - EGI and COMMUNITY user support, tools and services

2 EGI-InSPIRE RI-261323 www.egi.eu 1st target: A WORLDWIDE DISTRIBUTED PLATFORM

• CONNECT EGI distributed operations platform to XSEDE (PRACE, etc.) network and consortia of resource providers by placing allocation requests in an appropriate form

3 EGI-InSPIRE RI-261323 www.egi.eu 2nd TARGET: A WORLDWIDE RESEARCH FEDERATION

• FEDERATE CMMST communities around the world (EU, US, CANADA, PACIFIC ASIA, …) for reciprocal collaboration, support and servicing

4 EGI-InSPIRE RI-261323 www.egi.eu 3rd TARGET: QUALITY

EVALUATION • IMPLEMENT proper quality evaluation criteria in order to - select HTC, HPC, specialized HW - chain in workflows programs, packages, data - specialize portals and gateways - reward active users providing shareable software - build a shared governance for the community - standardize (at least de facto) molecular data

5 EGI-InSPIRE RI-261323 www.egi.eu THE STARTING COMMUNITY AND PARTNERS

• VIRTUAL ORGANIZATIONS: COMPCHEM, CHEM.VO.IBERGRID, GAUSSIAN • PROJECTS: MoSGRID and SCALALIFE • ASSOCIATIONS: Virtual Education Community of ECTN (150 Chemistry Departments), EUCHEMS Computational chemistry division (1000 users)

• TECHNICAL PARTNERS: IGI-UNIPG, MTA-SZTAKI, UB, MoSGRID • NGIs: IGI, IBERGRID, PL-GRID, MetaCentrum, NGI-HU, NGI-LT, GRNET • RESOURCE PROVIDERS: CINECA, CESGA, XSEDE

• SME CLUSTER: MASTER-UP srl (Perugia, IT), Krebbs srl (Vienna, A), Exact lab (Trieste, IT), Arctur (Nova Gorica, SL), Polymechanon (Thessaloniki, GR)

6 EGI-InSPIRE RI-261323 www.egi.eu DATA AND WORKFLOW OF THE SIMULATOR System input

Q5Cost Interaction

D5Cost Dynamics

various Statistics

Virtual Monitors

EGI-InSPIRE RI-261323 www.egi.eu THE SIMULATOR WORKFLOW

NO NO NO Are ab initio Are ab initio INTERACTION Is there a suitable PES? calculations calculations available? feasible? YES YES YES SUPSIM

Are NO Take Force fields from dynamics FITTING databases Import the calculations PES routine direct? YES YES

DYNAMICS

NO NO Exact NO Approximate Semiclassical quantum quantum calculations? calculations? calculations?

YES YES YES

QDYN APPROXIMATE SEMICLASSICAL QUASI- TD / TI QDYN SC_IVR CLASSICAL

OBSERVABLES

NO NO NO Fixed Fixed J and Energy Fixed Temperature Energy

YES YES YES

Scalar and vector Thermal Cross-sections Thermodynamic properties EGI-InSPIRE RI-261323 correlations Rate coefficients www.egi.eu THE UNSUSPECTED KILLER

WHY TRAJECTORIES FAIL TO PREDICT HIGH REACTIVITY OF M + M’H → MM’ + H AT LOW TEMPERATURE? (Astrochemistry, cold fusion, drugs action, etc.)

EGI-InSPIRE RI-261323 www.egi.eu Long range The Grid distribution model interactions and THE SIMULATOR reactivity of

HC N+N2

r BC SRampinoetal r HA AB HB Fukuoka GEMS’ Dyn module ICCSA 2010 Distribute AI runs and get the PES Outline q5 ! q5 q5 q5 q5 q5 q5 using the TI ABC program Motivation d5 Interaction module ! each ﬁxed-E calculation is Anewpotential energy surface independent Theory and ! computing details distribute and gather results to The A + BC reaction J-shifting get observables Grid distribution

Distribute scattering E’s and get reactive P’s ML4LJ dynamics Dynamics module and kinetics E On a grid of 160 ’s Acknowledgments ! 10 E’s per CE’s References Observables module ! speed up of about 16

EGI-InSPIRE RI-261323 www.egi.eu 10 Antonio Lagan`aand Sergio Rampino

Quantum dynamics vs experiment Li + FH (v=0, j) -> LiF + H 12 Li + FH (v = 0, j) → LiF + H 10 A. Laganà et al, Lecture j=0, J-shifting j=0, exact Notes in Computer Science, exp June 2014 8

σ (A2) 6 Both exact and J-shifting results conirm the experimental trend 4 suggesting an ininite cross section at vanishing 2 scattering energies 0 0 0.02 0.04 0.06 0.08 0.1 Etr (eV) EGI-InSPIRE RI-261323 www.egi.eu

Fig. 2. v =0,j =0(solidline)J-shifting excitation function plotted as a function of translation energy. Experimental data of Ref. [15] scaled to quantum values calculated around 0.08 eV are given as black circles. For comparison the value of the exact quantum (v =0,j = 0) cross section obtained including calculations at J<5 at a very low translational energy (empty squares at 0.00387 and 0.01000 eV) is also shown. A grid empowered virtual versus real experiment for the reaction Li + FH 9 THE SMOKING GUN

Li + FH (v=0, j) -> LiF + H

1 j=0

0.8

0.6 j = 0 Li + FH (v = 0, j) → LiF + H 0.4 0.2

0 1 j=1

0.8 0.6 j = 1 0.4

0.2 At j=0 here is no threshold to reaction: 0 1 j=2 the reaction occurs also at no collision 0.8 0.6

energy and behaves, therefore, as 0.4 Probability j = 2 barrier-less 0.2 0 1 j=1.4

0.8

0.6 0.4 j = 1.4 0.2 exp

0 0 0.02 0.04 0.06 0.08 0.1

Etr (eV)

EGI-InSPIRE RI-261323 Fig. 1. J =0,v =0,j =0(toppanel),j = 1 (higher central panel),www.egi.euj =2(lower central panel) state-speciﬁc reactive probabilities plotted as a function of translation energy. Values for ¯j =1.4 (bottom panel) corresponding to the model treatment of Ref. [15] are also shown. THE PROPOSED ROADMAP

XSEDE – EGI-CMMST SET a joint Virtual Team with the mandate of defining a workplan for: • Establishing links among continental CMMST subcommunities (EU, US, ASIA, …..) • Establishing reciprocal access to the compute resources • Developping QoS redirection of jobs to the most proper machines • Activate quality schemes for rewarding active users

13 EGI- InSPIRE RI-261323 www.egi.eu A XRAS procedure for CMMST • developing a XRAS procedure for community accesses from EGI-CMMST - CMMST has already identified 2 US PI and can find more if needed - EGI-CMMST can guarantee definition of resources, authentication, allocation policies - EGI-CMMST can provide local accounting, custom submission UI, integration with OPEN XDMODE and certification of local users’ publications

14 EGI-InSPIRE RI-261323 www.egi.eu THE END

if you wish to know more about the quality parameters there are more slides to follow

7/17/14 15 EGI-InSPIRE RI-261323 www.egi.eu AB INITIO PACKAGES

• CADPAC Acad Fortran GTO • COLUMBUS Acad Fortran GTO • CRYSTAL Acad Fortran GTO • DALTON Acad Fortran GTO • DFT++ GPL C++ PW/Wavelet • DIRAC Acad F77, 90, C GTO • GAMESS Acad/Comm Fortran GTO • GAUSSIAN Comm Fortran GTO • MOLCAS Comm Fortran GTO • MOLPRO Comm Fortran GTO • NWChem ECLv2 F77/C GTO, PW • TERACHEM Comm C/CUDA GTO

EGI-InSPIRE RI-261323 www.egi.eu QoS PARAMETERS

• Accessibility • Integrity • Performance • Reliability • Security

7/17/14 17 EGI-InSPIRE RI-261323 www.egi.eu QoU PARAMETERS

• Number of succesful compilations • Number of results retrieved • Grid efficiency • Number of feedbacks produced • ….

7/17/14 18 EGI-InSPIRE RI-261323 www.egi.eu For each job or subjob

• 1. Username owning the job 2. Grid service name (wrapper) 3. Grid site name used 4. Job Type (e.g. Single, Parameter Study or Workflow) 5. Submission date 6. Ending date 7. Program name (if custom) 8. Input provided (if any)

7/17/14 19 EGI-InSPIRE RI-261323 www.egi.eu For each job or subjob

• 9. Results address (e.g. Storage Element) 10. Computing Element address (e.g. queue name used for run) 11. Computing Element Exit status (e.g. 0 -> done with success; 1 -> CE error) 12. Cpu time 13. Wall time 14. Memory consumed 15. Additional job info

7/17/14 20 EGI-InSPIRE RI-261323 www.egi.eu For each Grid service

• 16. Name 17. Description 18. Grid site name location 19. Maintainer / Manager 20. Number of Functions (e.g. # of Web Services composing the Grid Service) 21. Number of Errors 22. Elapsed (averaged) time for satisfying (initiating) a call

7/17/14 21 EGI-InSPIRE RI-261323 www.egi.eu For each Grid service

• 23. Elapsed (averaged) TTR (Time-to- Repair) for repairing an error 24. QoS (calculated by us) 25. Cost (assigned by us) 26. Additional service info

7/17/14 22 EGI-InSPIRE RI-261323 www.egi.eu For each user

• 27. Number of runs corresponding to those applications already made available by the Framework; 28. Number of runs corresponding to new programs provided by the user (if any); • 29. Number of results generated from 27) 30. Number of results generated from 28) 31. Number of results accessed from 27) 32. Number of results accessed from 28)

7/17/14 23 EGI-InSPIRE RI-261323 www.egi.eu For each user

• 33. Average cpu time elapsed for runs generating results 34. Average cpu time elapsed for runs having results accessed • 35. Average wall time elapsed for runs generating results 36. Average wall time elapsed for runs having results accessed • 37. Average memory consumed for runs generating results

7/17/14 24 EGI-InSPIRE RI-261323 www.egi.eu For each user

• 38. Average memory consumed for runs having results accessed • 39. Number of positive feedbacks 40. Number of neutral feedbacks 41. Number of negative feedbacks 42. QoU (calculated by us) 43. Credits (assigned by us) 44. Additional user info

7/17/14 25 EGI-InSPIRE RI-261323 www.egi.eu For each compute element

• 45. Queue name 46. Ranking evaluation (position) 47. Last used (date) or new 48. Performance 49. Average Latency 50. Additional ranking info (e.g. Round robin strategy flag)

7/17/14 26 EGI-InSPIRE RI-261323 www.egi.eu