AMD/ATI Radeon HD 5870 GPU DEGIMA LINPACK HD 5870 GPU DEGIMA LINPACK GFlops/Watt GFlops/Watt Abstract GPU Computing has lately attracted
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1 DEGIMA LINPACK Energy Performance for LINPACK Benchmark on DEGIMA 1
2 AMD/ATI Radeon HD 5870 GPU DEGIMA LINPACK HD 5870 GPU DEGIMA LINPACK GFlops/Watt GFlops/Watt Abstract GPU Computing has lately attracted for energy efficiency. Most of GPU computing system are using for coarse-grained optimization for power-consumption and not for energy efficiency. In this paper, we propose an fine-grained optimization method for enegy efficient GPU computing. We use AMD/ATI Radeon HD 5870 GPU system and introduce its power consumption model in relation between energy-efficiency(flops/watt) and system parameters such as GPU frecuency and voltage. We implement an enegy controllable library with our power consumption model and apply it to the LINPACK benchmark. We found that the energy efficiency improved from 1.47 GFlops/Watt to GFlops/Watt using our method for LINPACK banchmark. 2
3 1. High Performance Computing GPU High Performance Computing(HPC) TOP500 2 TOP500 TOP500 LIN- PACK 1) 1.1 HPC TOP ) 2 GPU DEGIMA(DEstination for GPU Intensive MAchine) LINPACK benchmark (Rmax) (Rpeak) 1 1 DEGIMA 1 DEGIMA GPU, GPU 1 TOP500 DEGIMA 1 K computer, TSUBAME2, T2K-tsukuba R max, R peak 3
4 1.2 TOP500 GPU GPU TOP500 GPU TOP ( 2 AMD GPU 2 Cell Nvidia GPU 3) ) 3 GPU GPU DEGIMA 1 TOP500 GPU 1.3 Green500 Green500 TOP500 (Flops/W) TOP ) 60% GPU GPU Green500 GPU 2500 MFlops/W Blue Gene/Q(IBM) GPU Cluster DEGIMA(Nagasaki Univ) TSUBAME(Tokyo Tec) K Computer(RIKEN) Rank Green ( ) ( ) GPU ( ) ( ) 4
5 K-computer LINPACK benchmark 10 PFlops( ) TOP a 1EFlops 100PFlops 10PFlops 1PFlops 100TFlops 10TFlops 1TFlops 100GFlops 10GFlops TOP500 TOP500#1 R max ) a TOP500 1 K-computer LINPACK 11.28PFlops MW Flops/W K- computer MW ) 4 Green MW (= MW 100/
6 K-computer 3 Flops/W Green500 No.1 year 2. AMD/ATI Radeon 5870 DEGIMA AMD/ATI Radeon 5870 GPU 2.1 AMD/ATI Radeon 5870 AMD/ATI Radeon ) Engine clock speed MHz Processing power( ) 2.72 TFlops Processing power( ) 544 GFlops Memory clock speed 1.2GHz Memory bandwidth GHz 1 ATI Radeon AMD/ATI Radeon 5870 GPU Tesla M2090 Radeon Radeon 5870 Tesla M
7 Radeon 5870 Tesla C2070 Tesla M2090 GTX 580 Process Technology 40(nm) 40(nm) 40(nm) 40(nm) ( ) 2.72TFlops 1.03TFlops 1.33TFlops 1.581TFlops ( ) 544GFlops 515GFlops 665GFlops 198GFlops 188W 215W 225W 244W ( ) ( ) 20.94MFlops/ 2.42MFlops/ 1.45MFlops/ 5.00MFlops/ ( ) 2.894GFlops/W 2.395GFlops/W 2.956GFlops/W 0.81GFlops/W 2 GPU. (TDP: Thermal Design Power) )9)10)11)12)13)14) 2.2 AMD GPU 3 AMD/ATI GPU 3 GPU AMD Display Library(ADL) AMD Display Library(ADL) AMD/ATI GPU C 15) AMD Radeon 5870 ADL GPU 80 MHz 1200 MHz 5 MHz GPU 150 MHz 1400 MHz 5 MHz GPU V V 5 mv 3 GPU 2.3 AMD GPU AMD Radeon 5870 GPU 7
8 Level Engine frequency(mhz) Memory frequency(mhz) Core voltage(v) ATI Radeon GPU 5 LINPACK Active Percent GPU ADL GPU 5 LINPACK (25 ) Activity Percent Current lvl temp 20 0 GPU Call (sec) LINPACK Radeon 5870 GPU GPU (Active Percent) (temp) (Current lvl) LINPACK GPU (GPU Call) (25 ) 5 LINPACK GPU 25 5 GPU (Current lvl) GPU (temp) GPU (Active Percent) GPU (GPU Call) LINPACK GPU 8
9 GPU CPU 5 GPU (GPU Call) ON/OFF 5 GPU (temp) GPU Call GPU Call GPU GPU Call GPU 5 GPU Call ( GPU Call 100 ) GPU- GPU (Current lvl) 5 LINPACK 25 2 LINPACK 0 2 LINPACK 2 0 AMD GPU 6 LINPACK ADL Radeon ADL % LINPACK 21.4% 27.7% % 3. AMD/ATI GPU AMD/ATI GPU 9
10 default this work 200 watt idle high low Radeon 5870 GPU (idle) LINPACK (high) LINPACK (low) default 200 Watt 100 change parameter sec 5 ( ) ( ) AMD/ATI GPU API API GPU 2 10
11 GPU Call API GPU 3.2 API API (1) (2) API C EL SetHighestAutomatic API EL SetLowestAutomatic API EL DEVICE API Radeon 5870 EL Init API 8 int main() { EL_DEVICE dev = EL_Init(EN_DEVICE_TYPE_HD5870); // EnergyLibrary Initialization... host part.. EL_SetHighestAutomatic(dev); // EnergyLibrary API... GPU part.. EL_SetLowestAutomatic(dev); // EnergyLibrary API... host part.. } API API C API GPU 2 EL SetLowestAutomatic GPU GPU EL SetHighestAutomatic GPU 3 11
12 4. LINPACK API GPU GPU DGEMM LINPACK 2 DGEMM(Double-precision General Matrix Multiply) LINPACK AMD Radeon 5870 GPU AC105V Digital Multimeter 500Wmax Power Unit log recorder(pc) DC 3.3~12V Host computer CPU: Intel Core i5-2500t 16GB DDR GPU: AMD HD DGEMM DGEMM GPU DGEMM N=42000 GPU 1.062V 1.212(V ) V=1.062(V) V=1.137(V) V=1.212(V) GPU 12
13 10 MHz MHz MHz 10 GPU DGEMM:N=M=42000, V=1.062(V) GFlops DGEMM:N=M=42000, V=1.137(V) GFlops DGEMM:N=M=42000, V=1.212(V) GFlops DGEMM DGEMM N=42000 GPU ( ) ( ) GPU ( V=1.062(V) V=1.137(V) V=1.212(V)) (GFlops) ( ) ( ) GPU 11 GPU GPU
14 DGEMM:N=M=42000, V=1.062(V) Watt DGEMM:N=M=42000, V=1.137(V) Watt DGEMM:N=M=42000, V=1.212(V) Watt DGEMM DGEMM N=42000 GPU ( ) ( ) GPU ( V=1.062(V) V=1.137(V) V=1.212(V)) (Watt) ( ) ( ) 12 GPU GPU GPU 770MHz MHz 1.062V 4.3 LINPACK LINPACK GPU LINPACK N=39680 NB=1280 GPU V=1.062(V) GPU 14
15 情報処理学会研究報告 DGEMM:N=M=42000, V=1.062(V) GFlops/W DGEMM:N=M=42000, V=1.137(V) GFlops/W DGEMM:N=M=42000, V=1.212(V) GFlops/W DGEMM DGEMM N=42000 GPU ( ) ( ) GPU ( V=1.062(V) V=1.137(V) V=1.212(V)) (GFlops/W) ( ) ( ) 13 DGEMM GPU DGEMM LINPACK GPU GPU 14 DGEMM GPU DGEMM LINPACK GPU DGEMM 15
16 LINPACK:N=39680, NB=1280 GFlops LINPACK LINPACK N=39680 NB=1280 GPU V=1.062(V) GPU ( ) ( ) (GFlops) ( ) ( ) LINPACK:N=39680, NB=1280 Watt LINPACK LINPACK N=39680 NB=1280 GPU V=1.062(V) GPU ( ) ( ) (Watt) ( ) ( ) GPU GPU DGEMM LINPACK GPU 770MHz MHz 1.062V 5. DGEMM 16
17 LINPACK:N=39680, NB=1280 GFlops/W LINPACK LINPACK N=39680 NB=1280 GPU V=1.062(V) GPU ( ) ( ) (GFlops/W) ( ) ( ) 5.1 DGEMM ( ) DGEMM ( ) MHz 930MHz 1.062V f(f eng, f mem ) = f 4 eng f 4 mem f 3 eng f mem f eng f 3 mem f 2 eng f 2 mem f e f 3 mem f 2 eng f mem f eng f mem f 2 eng f 2 mem f eng f mem f eng f mem ( W eng W mem f V W host 17
18 DGEMM:N=M=42000 GFlops/W DGEMM N=42000 ( 12) Host computer W in Power Unit W out GPU GPU Engine GPU Memory W host W powerunit 17 W eng W mem GPU GPU GPU GPU 7 8 W powerunit = W in W out (2) W out = W eng + W mem + W host (3) W eng = k eng f eng V 2 (4) W mem = k mem f mem V 2 (5) W host = Const (6) S( f) = S(f eng, f mem ) (7) E = S( f) W in ( f, V ) (8) 18
19 W_out(W) 情報処理学会研究報告 MHz 920MHz 1.062V f(f eng, f mem ) = f 4 eng f 4 mem f 3 eng f mem f eng f 3 mem f 2 eng f 2 mem f e f 3 mem f 2 eng f mem f eng f m f 2 eng f 2 mem f eng f mem f eng f mem (9 DGEMM:N=M=42000 GFlops s(x,y) (DGEMM N=42000) 280 W out = f eng f mem (10) W_in(W) ( ) 16) W in W out DGEMM 19
20 180 情報処理学会研究報告 00 DGEMM:N=M= Watt 185 w(x,y) DGEMM N=42000 ( 11) 3 ( ) ( ) DGEMM:N=M=42000 GFlops/W DGEMM N= ( ) ( ) Relative Error MHz MHz 1.062V LINPACK LINPACK GPU AMD/ATI Radeon
21 1200 Normal This work sec AMD/ATI Radeon 5870 (Normal) (This work) GPU 6.2 AMD/ATI Radeon LINPACK W W 27.8% 770MHz MHz 1.062V 765MHz 930MHz 1.062V 765MHz 920MHz 1.062V 4 ( 12) ( 16 21) 6.3 DGEMM 4 21
22 情報処理学会研究報告 350 normal 10 9 normal this work 7 this work W 200 Wh w sec wh LINPACK AMD (normal) (this work) (this work normal) sec LINPACK AMD/ATI Radeon5870 LINPACK 1,4698Gflops/W Gflops/W 33.7% LINPACK Gflops W Gflops/W Gflops W Gflops/W Gflops W Gflops/W Gflops W Gflops/W 5 LINPACK. (N=39680, NB=1280). 22
23 GFlops Watt GFlops/W GFlops/W default thiswork thiswork thiswork (with model1) (with model2) LINPACK. (N=39680, NB=1280). (GFlops) (Watt) (GFlops/W) 7. GPU LINPACK DGEMM DGEMM 2 3 DGEMM LINPACK Gflops/W Gflops/W Green500 References 1) J.Dongarra, LINPACK: users guide, ser. Miscellaneous Bks. Society for Industrial and Applied Mathematics, [Online]. Available: 2) Top 500 countries share for 11/2011, [Online]. Available: 3) Top 500 press release, [Online]. Available: 23
24 4) The green500 list november 2011, [Online]. Available: 5) Top500 performance development, [Online]. Available: development 6), [Online]. Available: 7) Ati radeon hd 5870 graphics specifications, [Online]. Available: /hd-5870/Pages/ati-radeon-hd-5870-overview.aspx#2 8) Nvidia tesla c2050 / c2070 gpu, [Online]. Available: tesla C2050 C2070 jp.html 9) Next io vcore extreme -, [Online]. Available: extreme/index.html 10) G.Chen, L.Chacón, and D.C. Barnes, An efficient mixed-precision, hybrid CPU-GPU implementation of a fully implicit particle-in-cell algorithm, ArXiv e-prints, Nov ).com eah5870/2dis/1gd5/v2 (pciexp 1gb), [Online]. Available: 12) Nvidia tesla c2070 [pciexp 6gb], [Online]. Available: kakakuitem title 13) Ntt-x store, [Online]. Available: II HP ) Giada gtx580-ddr5 [pciexp 1.5gb], [Online]. Available: kakakuitem title 15) Amd display library (adl) sdk, [Online]. Available: 16) 80 plus verification and testing report, [Online]. Available: PC6024 W Report.pdf 24
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