04SAAHPCpresentationScalableSystolicArray

26 ghz quad core cpus 24gb ecc ddr3 3 x 1tb sata2 24

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Unformatted text preview: , 250GB SATA2 As 2 GiDEL ProcStar-III PCIe x8 cards, each with 4 Stratix-III E260 FPGAs and 4x4.25 = 17GB RAM 6 compute servers (4U), each with: 2 Xeon E5620 2.4GHz quad-core CPUs 16GB ECC DDR3, 2TB SATA2 4 GiDEL ProcStar-IV PCIe x8 cards, each with 4 Stratix-IV E530 FPGAs and 4x8.5 = 32GB RAM 96 FPG GTX-480 GPU As * Our cluster vendor is Ace Computers Novo-G Annual Growth 2009: 96 top-end Stratix-III FPGAs, each with 4.25GB SDRAM 2010: 96 more Stratix-III FPGAs, each with 4.25GB SDRAM 2011: 96 top-end Stratix-IV FPGAs, each with 8.5GB SDRAM 2012: 96 more Stratix-IV FPGAs, each with 8.5GB SDRAM 11 NovoG ProcStarIII Board (one of 48) Multiboard interconnect to stream apps across two PS-III boards (8 FPGAs) in same server @ speed 120.8 mm JTAG for SignalTap debug 22GB = 4GB DDR2 RAM per FPGA 25.6 Gb /s 110 lin es bi-dire ctional New/ ProcStar-IV added in Novo-G similar / 256MB / DDR2 except56MB 2 E530 FPGAs and DDR2 256MB 2x RAM per FPGA DDR2 110 lin es bi-dire ctional inter-FP GA bandwi Boards dth (24) 110 lin bi-dire es ctional PCIe x8 interface (4GB/s) GiDEL ProcStar-III Board Typical frequencies DMA channels 32 DDR2 module slots 100-325MHz 8 312 mm 256MB DDR2 Altera Stratix-III E260 FPGA 254,400 Logic Elements 768 multipliers (1818) 14,688 Kbits of embedded memory 50% less power than Stratix-II 65nm technology 12 NovoG Energy (each of 24 servers) Power Consumption of Each Novo-G Server 350 300 250 200 163 150 111 100 50 0 Idle Server Loaded Server Loaded Server + Idle RC Boards Idle Server + Loaded RC Boards Loaded Server & RC Boards 327 Smith-Waterman application Quad-core E5520 Xeon CPU 2 GiDEL ProcStar-III boards 8 Stratix-III E260 FPGAs total 40GB (172+6) DDR2/3 RAM 267 210 Watts 156W max. power for 2 boards, 8 FPGAs, 34GB DDR2, fans, et al. @ full load on S-W app (i.e. <20W per FPGA) 13 NovoG Applications Research n Broad range underway in research studies q q q q q q q q q q q q Smith-Waterman (w/ or w/o traceback) Needleman-Wunsch Needle-Distance Information-theoretic adaptive filtering Backprojection Isoformic proteomics BLASTp (collaboration with Boston University) BLASTn and BLAST-wrapped Smith-Waterman (BSW) Heston model for options pricing in comp. finance Molecular dynamics (collaboration with Boston University) Hidden Markov models and Viterbi Other new apps in planning stages 50x to 5000x speedup per...
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