EPCC: KT in novel computing

1. EPCC: KT in novel computing

2.   leading Europe • mission - “to be the premier European computational science centre” • the European equivalent of one of the big US centres, eg NCSA, University of Chicago • think globally, act locally

3. European leadership R&D excellence Training Partnerships Industry + Academia HPC facilities+skills Dbase + Grid expertise building the vision • Vital statistics: • 75 staff • £4.5 M turnover (almost) all from external sources • Multidisciplinary and multi-funded • ... with a large spectrum of activities • … and a critical mass of expertise • Supports and undertakes research at UoE through: • access to facilities • training (MSc and some undergraduate) • HPC-Europa visitor programme • collaborative research (eg NAIS, RealityGrid … )

4. HECToR • 4th generation national facility managed by Edinburgh • HPCx + HECToR = £150M • HECToR 250 Tflops peak • Most powerful computer in UK academia • shortly to be upgraded to 350 Tflops • … used for a wide variety of physical, engineering, environmental and biological projects • … opportunities for industry involvement • through facility access, or direct collaboration

6. win-win-win

7. Many-core era Massively parallel applications 100 Multi-core era Scalar and parallel applications Increasing HW Threads Per Socket 10 HT 1 2003 2005 2007 2009 2011 2013 the second age of parallelism • the end of Moore’s law at the core level multi-core chips ← parallelism → very many processors • … today’s top-end HPC techniques will have widespread applicability tomorrow • the same parallel techniques used to get performance on Blue Gene could be required everywhere

8. Academic R&D ` Commercial exploitation making an economic impact • projects based on delivering business benefit • not pushing a particular technology • based within the University we have access to a wide range of leading-edge expertise • … on time, on budget and to specification • we now need to diversify from bespoke consultancy • EPCC Industry Hub to be launched in 2009 • use ISV’s to target wider markets • make facilities available as a paying service • seeking SE and industry support

9. The challenges • the end of (not) Moore’s Law • levels of parallelism may increase, but can we use it? • will, say, MPI scale to Exascale? • how can we create fault-tolerant applications? • is there really an economic basis for HPC based on commodity components? • escalating infrastructure costs • power, space, cooling … • verification of results • rigorous testing of QCD has shown numerous hardware problems • choosing appropriate algorithms essential • widespread training required if computational science can truly stand alongside theory and experiment

10. … and our response • Exascale Technology Centre • funded by the University in collaboration with Cray to investigate key scalability problems • hybrid programming models • PGAS languages • GPU-based architectures • Numerical Algorithms & Intelligent Software (NAIS) • collaboration with Numerical Analysts and Computer Scientists • 5-year project to develop new algorithms designed to be parallel • written to be WORA (Write-Once, Run-Anywhere) • … with increased information to aid the compiler to generate highly-efficient code • high-impact demonstrators • eg. real-time simulation of fire spread in the Olympic Stadium

11. the need for partnership • the Exascale challenge is beyond any one institution • … perhaps even beyond any one country • so, there is a clear desire to collaborate • G8 funding call a clear opportunity to build on the Tsukuba- Edinburgh • the scale may be small, but it will grow … collaborationhttp://www.dfg.de/en/research_funding/international_cooperation/research_collaboration/g8-initiative/index.html