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We have made significant progress over the past couple of years working with scientists around the world helping them to accelerate scientific discovery - using Nvidia Tesla GPU and CUDA computing
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World’s Fastest Molecular Dynamics Simulation
Sustained Performance of 1.87 Petaflops/s Institute of Process Engineering (IPE)
Chinese Academy of Sciences (CAS)
Simula'on for Crystalline Silicon Used for Photovoltaic cells & Semiconductors
Used all 7168 Tesla GPUs on Tianhe-‐1A GPU Supercomputer
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World’s First Whole H1N1 Virus Simulation
More accurate & complete model
Furthers understanding of drug interactions
Mole-8.5 GPU Supercomputer
at CAS-IPE
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ASUCA TeraFlop Scaling (Weather Modeling)
3990 Tesla M2050s
145.0 Tflops SP
76.1 Tflops DP
Simulation on Tsubame 2.0, TiTech Supercomputer
After GPUs
Before GPUs
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2011 Gordon Bell Prize Winner Tsubame 2.0 GPU Supercomputer
“Peta-scale Phase-Field Simulation for Dendritic Solidification on the TSUBAME 2.0 Supercomputer”
-- Shimokawabe et. al. Science Impact
Developing lightweight material for fuel efficient cars
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Forecasting Heart Attacks Tsubame 2.0 GPU Supercomputer
Plaque rupture leads to heart attack Forecast where/when plaques form
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Metagenomics Tsubame 2.0 GPU Supercomputer
BLASTX: Standard CPU Software GHOSTM: GPU-based Software compatible with BLASTX
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LAMMPS: Billion Atoms Simulation
Test Pla)orm: NCSA Lincoln Cluster with S1070 1U GPU servers a?ached CPU-‐only Cluster-‐ Cray XT5
Billion Atom Lennard-‐Jones Benchmark
29 Seconds
103 Seconds
288 GPUs + CPUs 1920 x86 CPUs
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Protein-DNA Docking
Dr. Bo Hong, George Tech Dr. Juntao Guo, UNC Charlotte
Improving Prediction Accuracy of Protein-DNA Docking with GPU Computing, Best Paper Award, IEEE BIBM 2011
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Strong Scaling LQCD: Chroma & MILC 256 GPUs outperform 8K CPU cores
Chroma 3.41.0 using GCR-DD solver MILC 7.6.3 using mixed-precision CG solver
Guochun Shi (NCSA), Balint Joo (Jefferson Labs), Ron Babich (BU), Mike Clark (Harvard), Rich Brower (BU), Steve Gottlieb (Indiana), “Scaling Lattice QCD beyond 100 GPUs,” SC11, ACM (Nov 2011)
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Computational Fluid Dynamics Scaling on GPUs
Boise State Univeristy, Jacobsen, Thibault, Senocak 48th AIAA Aerospace Sciences Meeting, January 4-7, 2010
Incompressible Flow Computations, Navier-Stokes 64 Compute nodes with 128 M1060 GPUs
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102
228
428
854
1478
2432
20
200
2000
1 2 4 8 16 32 64 128
GFL
OPS
(lo
gari
thm
ic)
Number of GPUs
2.4 Tflops
128 GPUs
11x Speedup with GPUs
Navier Stokes (Weak Scaling) in GFLOPS
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Titan at Oak Ridge World’s Top Open Science Computing Research Facility
2x Faster, 3x More Energy Efficient than Current #1 (K Computer)
18,000 Tesla GPUs
20+ PetaFlops
~90% of flops from GPUs
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NCSA Mixes GPUs into Blue Waters
NCSA is excited about the inclusion of NVIDIA's Tesla GPUs in Blue Waters. GPUs provide extraordinary capabiliWes for numerically-‐intensive computaWons and a cost-‐effecWve, energy-‐efficient way to build tomorrow's petascale supercomputers.
“
” Thom Dunning Director, NCSA