The Hartree Centre

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The Hartree Centre Andrew Gargett AI team lead | STFC Hartree Centre Our mission Transforming UK industry by accelerating the adoption of high performance computing, big data and cognitive technologies. Our platforms Intel platforms Accelerated & emerging tech Bull Sequana X1000 Maxeler FPGA system Lenovo NeX tScale | 8,192 cores ARM 64-bit platform Lenovo System x iDataPlex system | 2048 cores Clustervision novel cooling demonstrator Intel Xeon Phi | Knight's Corner IBM big data analytics cluster | 288TB IBM data centric platforms IBM Power8 + NVL ink + Tesla P100 IBM Power8 + Nvidia K80 Our people − Engineers − Chemists − Software − Life Scientists Developers − Mathematicians − Data Scientists Project examples • Engineering & Manufacturing – Vehicle Design & Testing – Consumer Electronics Design – Consumer Packaged Goods Products and Packaging • Environment – Weather modeling • Life Sciences – Genomics for better crop yields – Disease mapping • Energy – Advanced Battery Cell Design – Efficient Well Head Oil extraction • Financial Services – Risk Management – Service Modelling • Transport – Network simulation Case study | Building the cognitive hospital Collaborative R&D Transforming the patient experience using cognitive technology and data analytics “Helping our patients and their families prepare properly for coming into hospital will really reduce their anxiety and could mean they spend more meaningful time with doctors so we are able to get them better faster.” − Iain Hennessey, Alder Hey Children’s Hospital LCR 4.0: CiiVSOFT CiiVSOFT build software tools which automate recruiting tasks, save costs, time and improve the efficiency of recruitment processes. Problem : Wanted to explore the potential of using social media analytics to optimise matching candidates to roles. Solution : Hartree Centre developed a working prototype application that integrates social media data into the candidate selection pipeline. Uses IBM Watson personality insights to profile employees and candidates to assess suitability. Hartree Centre AI team • Combining NLP and ML to facilitate the engineering of cutting edge knowledge resources • Examples of current projects: • Information extraction pipelines • Re-implementing standard NLP techniques within Big Data setting • NLP for interactive machine learning • Mapping and merging knowledge bases A bit about myself- − Initial studies. /niversity of 0estern Australia Started out in Engineering, then discovered Linguistics – ended up with a Masters in Linguistics, combined with Computer Science − hD. 1ings College London Formal and computational linguistics − ostgraduate period • Postdoc in Natural Language Generation & AI [Germany] • Asst. Prof. teaching Phonetics, Lang. Testing, Natural Language Processing [UAEU] − Marie Curie Senior Researcher. /niversity of Birmingham Generating and understanding metaphor in natural language, using AI and data driven approaches − Research Scientist. 2artree Centre. STFC AI team lead Thank you Andrew Gargett [email protected] [email protected] .

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High-Performance Computing and Big Data Challenge Dr Violeta Holmes Matthew Newall The University of Huddersfield Outline • High-Performance Computing – E-Infrastructure – Top500 -Tianhe-II – UoH experience: HPC resources and applications • Big Data – Hadoop – Case study: Close Call • Summary High-Performance Computing • The HPC and Big Data are new technologies vital for the advancement in science, business and industry. • ”High Performance Computing (HPC) and e- infrastructure in general are drivers of economic growth and societal well-being. They are also vital for maintaining international competitiveness in the generation of knowledge and its application.”(Kenway, Coveney, McGuire, Parchment, & Parsons, 2012) Where we were 50s-early 80s • Centralised computing facilities • Dummy Terminals • Punch cards • Batch Processing μ Processors • Allowed users to have “intelligent” machines under their table – Seen as an expensive typewriter – Few organisations and educational institutions had them • These machines were quickly overtaking Mainframes in price-performance factors, and later overtaking them in performance. 90s – early 2000 • Information on Demand - For the first time sharing and communicating became easy and quick. Where we are now • Efficient Multitasking Desktops • Capable Workstations • Mobile Devices – less capable Through the use of middlewares: • Clusters • Grids The 5th Utility Utility Computing/Cloud Computing/On- Demand Computing/Service Computing • The concept of just plugging in your problem into a computer system and getting results. • Defined as: “A large-scale distributed computing paradigm that is driven by economies of scale, in which a pool of abstracted virtualised, dynamically-scalable, managed computing power, storage, platforms and services are delivered on demand to external customers over the internet.” (Foster et al.
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