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CALIM2009 report on Computing Hardware

CALIM2009 report on Computing Hardware. Editor: Tim Cornwell Presenter: Chris Broekema. Attendees. Chris Broekema Tim Cornwell Danielle Fenech Panos Lampropoulos Simon Ratcliffe Note that we had a small number of people for a Red topic. Relevant talks. Chris: LOFAR CP Panos: LOFAR EOR

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CALIM2009 report on Computing Hardware

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  1. CALIM2009 report on Computing Hardware Editor: Tim Cornwell Presenter: Chris Broekema

  2. Attendees • Chris Broekema • Tim Cornwell • Danielle Fenech • Panos Lampropoulos • Simon Ratcliffe • Note that we had a small number of people for a Red topic

  3. Relevant talks • Chris: LOFAR CP • Panos: LOFAR EOR • Pandey: MSSS pipeline • Miguel: Software holography (MOFF) • Aaron: PAPER • Tim: ASKAP • Bill: Multi-core • Simon: Stream processing

  4. Inventory: Software correlators • Small scale off line • Standard now, many groups • Large scale real time • Blue Gene • High efficiency • Required lots of work to get data flow right • Lots of research into: • Other hardware e.g. Cell, GPU, i7 • Single Digital Backend • Data rates are main challenge • Important long term implications • New concepts • MOFF • Limited applicability?

  5. Inventory: Hardware correlators • WIDAR • EVLA and eMERLIN • Packet switched + FPGA • E.g. CASPER implementation • Flexibility • Route to hybridization • FPGA/Custom ASICS/Modular ASICS • Convergence with Software Correlators

  6. Inventory: Calibration and Imaging • Hardware solutions • Simple clusters • Accelerators: FPGA, Cell, GPUs • Limitations • Large diversity in algorithms • Getting data to the processor • Multiple, fluid, programming models • Matching algorithms and hardware • Coarse e.g. Efficient cross-node parallelization • Fine e.g. efficient use of multi- and many-cores • Many (n>>8) cores • Scaling to e.g. 10000 cores • Accommodating very large data flows

  7. Unresolved issues: Scaling • Factors • Data handling • Computing • Memory • Bandwidth • Green power • Reliability • Algorithms • All scale differently with time • Algorithms scale differently

  8. Unresolved issues: Other • Resources required for long term development? • Hardware engineering • Software engineering to map algorithms • Involvement with industry? • Computing and networking • Models for collaboration? • Between research groups • With industry

  9. Relevance to SKA • Hardware requirements and priorities very uncertain • Needs continuous re-evaluation • All hardware issues are on the critical path for SKA • Risk management vital • Community maturity to get close to top of Top 500 • Very limited experience of HPC compared to LHC • Lack of urgency and resources

  10. Relevance to SKA • LOFAR demonstrated Teraflop-range real-time correlation on computer • SDB tests large scale computing beyond LOFAR • LOFAR EOR and ASKAP major drivers at 100 Tflops level • Many diverse approaches • LOFAR, MeerKAT, ASKAP, MWA

  11. Recommendations • Foster and facilitate collaborations • Track activities, hold topic meetings • SPDO add capability to track HPC • Increase HPC involvement in CALIM • Coordinate attendance at meetings

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