New Zealand Involvement in Solving the SKA Computing Challenges

Transcription

1 New Zealand Involvement in Solving the SKA Computing Challenges D R ANDREW E N S O R D I R ECTO R H P C R ESEARC H L A B O R ATORY/ D I R ECTOR N Z SKA ALLIANCE COMPUTING FO R S K A COLLO Q U I UM FEBRUA RY

2 NZ Background in the SKA NZ was a founding member of the SKA Organisation NZ had joint bid with Australia to host SKA until dual site decision in 2012 First substantial involvement by NZ in a mega-science project SKA Board full member representation by MBIE MBIE desire to focus on computing/software aspects of project NZ SKA Alliance (NZA) formed in 2013 to coordinate NZ s preconstruction contributions to SKA Joined the Central Signal Processor (CSP) and Science Data Processor (SDP) consortia in 2013 Will be longest term multiway academic-industry collaboration Possibly largest NZ involvement in international ICT collaboration

3 NZ SKA Alliance Organisations NZA has seven member organisations, six with contracted design work Currently active in Preconstruction Design Active in part Associated organisations

4 NZA People Over 35 academics and industry partners in NZ working on SKA design for Central Signal Processor and Science Data Processor Numerous NZA people fulltime on SKA Team still grew during 2017 to handle preconstruction workload Includes all of NZ s involvement in SKA1 preconstruction One of largest SKA computing groups worldwide, very strong international collaborations

5 SKA1 Data Flow and International Consortia Teams MID LOW

6 SKA1 Data Rates Biggest BIG data project in the world SKA1 has BIG Data on a scale that ICT Industry will be facing in 5-10 years time SKA2 will be an order of magnitude BIGGER yet Raw data rates Dishes produce around 2 TB/s Antennas produce around 157 TB/s (0.3 TB/s per station) Central Signal Processor Real-time processing of data on the fly All data processed together in correlator, outputs up to 0.7 TB/s Pulsar Search pipeline must sift through data every few minutes to find new candidate pulsars Science Data Processor Processes correlator output to form images of the sky will require approx 260 PetaFLOP machine Mix of real-time and off-line processing, a lot of iterative processing on data

7 Central Signal Processor Correlator Visibility data to SDP Imaging/ Calibration Signal data from Mid dishes/ Low stations Channeliser Pulsar Search Pulsar Search candidates to SDP Beamformer Telescope Manager Local Monitoring and Control Pulsar Timing Pulsar Timing data to SDP

8 CSP Correlators and Beamformers Mid CBF Led by NRC Canada Contributions from NZA (AUT, Massey) and INAF Frequency slice two stages of custom FPGA boards, large data movement challenges NZ involvement in FPGA firmware, ASIC backup design See talks by Will Kamp and Rezaul Hasan CDR documentation submitted, awaiting review in March Low CBF Led by CSIRO Contributions from NZA (AUT) and ASTRON Custom FPGA boards, large data movement challenges NZ involvement in project management, modelling, FPGA firmware See talks by Grant Hampson and David Wilson/Norbert Abel CDR documentation submitted, awaiting review in March

9 CSP Pulsar Search Pulsar Search led by Manchester Contributions from Oxford, Max Planck, NZA (Auckland), INAF, STFC Same design for Mid and Low telescopes Commodity GPU and FPGA boards, large compute challenge and a lot of hardware NZ involvement in FPGA OpenCL software See talk by Oliver Sinnen CDR subelement review passed in Jan 2018

10 CSP Pulsar Timing Pulsar Timing collaboration between Swinburne and AUT Same design for Mid and Low telescopes Commodity GPU, a lot of software but small hardware NZ involvement in project management, algorithm and software design See talk by Willem van Straten CDR subelement review passed in Jan 2018

11 Central Signal Processor Organisations 900 Reported Hours per Month (taken from 2016 but still approximately true) ASTRON CSIRO IANF MPIfR NRC NZA OUX STFC SWINB UMAN NZA is third largest worldwide in CSP

12 Science Data Processor Visibility data from Calibration CSP Correlator gains/ Gridding (Inverse) FFT Cleaning residuals Pulsar Search candidates from CSP Pulsar Timing data from CSP Sky model Candidate Sifting Timing Analysis Degridding FFT Local Monitoring and Control Sky image/ updated model Telescope Manager

13 SDP Imaging Pipeline Contributors include Manchester, NZA (AUT), Cambridge, ASTRON, CSIRO, SKA South Africa Same design for Mid and Low telescopes Extremely large compute and data movement challenges Together with calibration forms bulk of SDP processing NZ involvement in algorithm optimisations on accelerators, modelling, precision analysis See talks by Seth Hall and Anthony Griffin

14 SDP Compute Platform Contributors include Cambridge, Oxford, ASTRON, NZA (AUT, Catalyst, Compucon, Open Parallel), CSIRO, ICRAR, China Same design for Mid and Low telescopes Extremely large amount of hardware, system orchestration, data movement, compute, data buffering NZ involvement in node design, prototyping/benchmarking, middleware, services, OS, security See talks by JC Guzman, Drew Devereaux, Markus Dolensky, TN Chan, Piers Harding, Nicolas Erdody

15 Science Data Processor Organisations Reported hours per month totalled for 2017 NZA is third largest worldwide in SDP

16 Questions? Thank You Andrew Ensor Director HPC Research Laboratory/ Director NZ Alliance