Computational Chemistry Benchmarks - Nvidia

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GAMESS Partnership Overview Mark Gordon and Andrey Asadchev, key developers of GAMESS, in collaboration with NVIDIA. Mark Gordon is a recipient of a NVIDIA Professor Partnership Award. Quantum <strong>Chemistry</strong> one of major consumers of CPU cycles at national supercomputer centers NVIDIA developer resources fully allocated to GAMESS code “ We like to push the envelope as much as we can in the direction of highly scalable efficient codes. GPU technology seems like a good way to achieve this goal. Also, since we are associated with a DOE Laboratory, energy efficiency is important, and this is another reason to explore quantum chemistry on GPUs. Prof. Mark Gordon Distinguished Professor, Department of <strong>Chemistry</strong>, Iowa State University and ” Director, Applied Mathematical Sciences Program, AMES Laboratory 84
GAMESS Aug. 2011 Release Relative Performance for Two Small Molecules GAMESS August 2011 GPU Performance First GPU supported GAMESS release via "libqc", a library for fast quantum chemistry on multiple NVIDIA GPUs in multiple nodes, with CUDA software 2e- AO integrals and their assembly into a closed shell Fock matrix 2.0 4x E5640 CPUs 4x E5640 CPUs + 4x Tesla C2070s 1.0 0.0 Ginkgolide (53 atoms) Vancomycin (176 atoms)
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update Updated: February 4, 2013
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New/Additional MD Applications Ramp
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Quantum Chemistry Applications Appl
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Quantum Chemistry Applications Appl
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Bioinformatics Applications Applica
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Molecular Dynamics (MD) Application
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Built from Ground Up for GPUs Compu
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Nanoseconds / Day Kepler - Our Fast
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Speedup Compared to CPU Only K20 Ac
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Nanoseconds / Day K10 Strong Scalin
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Nanoseconds / Day K10 Extreme Perfo
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Replace 8 Nodes with 1 K20 GPU 90.0
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Nanoseconds / Day 1 CPU 2 GPUs 2 CP
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Recommended GPU Node Configuration
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NAMD 2.9
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Speedup Compared to CPU Only Accele
Page 34 and 35: Nanoseconds / Day Outstanding Stron
Page 36 and 37: Energy Expended (kJ) K20 - Greener:
Page 38 and 39: Recommended GPU Node Configuration
Page 40 and 41: LAMMPS, Jan. 2013 or later
Page 42 and 43: Speedup Relative to CPU Alone K20X,
Page 44 and 45: Loop Time (seconds) Excellent Stron
Page 46 and 47: Energy Expended (kJ) 140 Faster, Gr
Page 48 and 49: Time (s) Time (s) Time (s) Time (s)
Page 50 and 51: Early Titan XK6/XK7 Benchmarks 18 1
Page 52 and 53: GROMACS 4.6 Final, Pre-Beta and 4.6
Page 54 and 55: Nanoseconds / Day Great Scaling in
Page 56 and 57: Replace 3 Nodes with 2 GPUs 9 8 7 6
Page 58 and 59: The Power of Kepler 140 RNase Solva
Page 60 and 61: K20X, the Fastest Yet Nanoseconds /
Page 62 and 63: CHARMM Release C37b1
Page 64 and 65: More Bang for your Buck Scaled Perf
Page 66 and 67: www.acellera.com 470 ns/day on 1 GP
Page 69 and 70: Quantum Chemistry Applications Appl
Page 71 and 72: Quantum Chemistry Applications Appl
Page 73: BigDFT
Page 78 and 79: Performance Relative to CPU Only Ke
Page 80 and 81: Energy Expended (kJ) Kepler, keepin
Page 82 and 83: Gaussian Key quantum chemistry code
Page 86 and 87: Upcoming GAMESS Q4 2012 Release Mul
Page 88 and 89: GPAW
Page 98 and 99: NWChem
Page 100 and 101: Quantum Espresso/PWscf
Page 102 and 103: Scaled to CPU Only Extreme Performa
Page 104 and 105: Elapsed Time (minutes) Replace 72 C
Page 106 and 107: Power Consumption [kW/h] NVIDIA GPU
Page 108 and 109: Time (s) QE/PWscf - More Powerful S
Page 110 and 111: Time (Seconds) TeraChem Supercomput
Page 112 and 113: Seconds Seconds Kepler’s Even Bet
Page 114 and 115: FastROCS OpenEye Japan Hideyuki Sat
Page 116 and 117: Shape Overlays per Second Riding Mo
Page 118 and 119: Benefits of GPU Accelerated Computi
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Computational Chemistry Benchmarks - Nvidia

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