GPU 1 2, 3 GPU Newton GPU CPU Energy Consumption and Acceleration of GPU of Molecular Dynamics Simulation TAKURO UDAGAWA 1 and MASAKAZU SEKIJIMA 2, 3 Molecular dynamics simulations are widely used for simulating the motion of molecules in order to gain a deeper understanding of chemical reactions, fluid flow, phase transitions, and other physical phenomena due to molecular interactions. However, these simulations require huge computer resources. In addition, the problem of energy consumption must be solved. Recently, GPGPU has attracted attention as a possible solution to these problems. In this paper, we performed molecular dynamics simulations on a CPU and GPU, and compare calculation time, power consumption and energy consumption results between them. 1 Department of Computer Science, Tokyo Institute of Technology 2 Global Scientific Information and Computing Center, Tokyo Institute of Technology 3 Department of Computer Science, Tokyo Institute of Technology 1. (Molecular Dynamics; MD) Newton 1)2) MD femto nano micro MD MD 4)3) GPU(Graphics processing units) GPU GPU GPGPU(general purpose computation on graphics processing units) GPU 6) 7) 8) GPU Nebulae NVIDIA GPU Tesla C2050 2010 6 TOP500 2 10) 2010 11 TSUBAME2.0 NVIDIA Tesla M2050 GPU IT 5) GPU 1 c 2010 Information Processing Society of Japan
CPU CPU 2. femto ( 1 ) ( 2 ) ( 3 ) ( 4 ) 1-3 ( 5 ) ( 6 ) ( 7 ) 1-6 (1) [ ( ) 12 ( ) ] 6 σ σ ϕ(r ij) = 4ε r ij r ij ij r ij i j ε σ Verlet Verlet (2)(3) r i(t +) = 2r i(t) r i(t ) + a i(t)( t) 2 (2) v i(t) = 1 [ri(t+) ri(t )] (3) 2 t (4) (5) (6) Φ = ϕ(r ij ) (4) i<j (1) K = 1 2 miv2 i (5) T = 2K (6) 3k B N m i i v i i k B N 3. GPU 3.1 NVIDIA CUDA GPU Brook+ 9),ATI Stream 11) C NVIDIA CUDA CUDA NVIDIA GPU G80 GT200 Fermi NVIDIA GPU SM(Streaming Multiprocessor) SM CUDA SM GPU SM GPU Fermi GTX480 15 SM SM 32 CUDA 480 CUDA CUDA CPU C GPU GPU GPU CPU GPU CPU GPU GPU CUDA ( 1) CUDA SM SM 32 14) 2 c 2010 Information Processing Society of Japan
potential energy kinetic energy kernel function2 1 CUDA memory (atoms data) 3.2 GPU GPU CPU GPU GPU GPU Mahsan Rofouei separate convolutions LEAP-Server GPU GPU 12) GPU 1 Nebulae TOP500 2 Nebulae 2010 6 Green500 4 13) Green500 MFLOPS/watt TOP500 1 Jugar Green500 56 4. CUDA CUDA ( 1 ) GPU ( 2 ) CPU GPU ( 3 ) ( 4 ) ( 5 ) GPU CPU ( 6 ) 2 5 3 GPU kernel function1 th.1 th.2 th.3 th.n 2 GPU ( 2) CPU 100 5. CPU Intel Core i7-860 2.80GHz CPU 4 256KB L2 8MB L3 GB DDR3 SDRAM GPU NVIDIA GT240 GT240 96 CUDA OS Ubuntu9.04 CUDA 3.0 3 c 2010 Information Processing Society of Japan
MD CPU GPU SYSTEM ARTWARE WATT-HOUR METER SHW3A 8 64 128 512 1024 4096 8192 32768 65536 NEV 6. 1, 3 4 CPU 8 CPU 0.003 GPU 0.0089 CPU-GPU GPU 64 GPU CPU MD GPU 1 results atoms value CPU GPU 8 64 512 65536 sec 0.0030 0.0089 watt 92.5 114 joule 0.2775 1.015 sec 0.160 0.038121 watt 94.3 115 joule 15.088 4.384 sec 8.280 0.2941 watt 94.8 121 joule 784.944 35.59 sec 106508 1554.98 watt 98.5 136 joule 10491038 211477 GPU CPU elapsed calculation time energy consumption(j) 5000 4000 3000 2000 1000 500000 400000 300000 200000 100000 0 0 10000 20000 30000 40000 50000 60000 70000 3 number of atoms CPU GPU CPU GPU 0 0 10000 20000 30000 40000 50000 60000 70000 number of atoms 4 4 c 2010 Information Processing Society of Japan
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