NVIDIA Linux OpenCL CUDA RTX SUPER Compute

NVIDIA GeForce RTX SUPER Linux OpenCL/CUDA GPU compute benchmarks by Michael Larabel for a future article.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 1909299-AS-RTXSUPERC34
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CPU Massive 4 Tests
HPC - High Performance Computing 4 Tests
Machine Learning 3 Tests
NVIDIA GPU Compute 10 Tests
OpenCL 8 Tests

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Result
Identifier
Performance Per
Dollar
Date
Run
  Test
  Duration
GTX 970
September 28 2019
  1 Hour, 51 Minutes
GTX 980
September 28 2019
  1 Hour, 51 Minutes
GTX 980 Ti
September 26 2019
  1 Hour, 46 Minutes
GTX 1060
September 27 2019
  1 Hour, 47 Minutes
GTX 1070
September 28 2019
  1 Hour, 41 Minutes
GTX 1070 Ti
September 27 2019
  1 Hour, 47 Minutes
GTX 1080
September 28 2019
  1 Hour, 37 Minutes
GTX 1080 Ti
September 28 2019
  1 Hour, 27 Minutes
GTX 1660
September 28 2019
  1 Hour, 47 Minutes
GTX 1660 Ti
September 28 2019
  1 Hour, 44 Minutes
RTX 2060
September 27 2019
  1 Hour, 35 Minutes
RTX 2060 SUPER
September 26 2019
  1 Hour, 38 Minutes
RTX 2070
September 27 2019
  1 Hour, 37 Minutes
RTX 2070 SUPER
September 26 2019
  1 Hour, 40 Minutes
RTX 2080
September 27 2019
  1 Hour, 36 Minutes
RTX 2080 SUPER
September 27 2019
  1 Hour, 38 Minutes
RTX 2080 Ti
September 29 2019
  1 Hour, 27 Minutes
TITAN RTX
September 27 2019
  1 Hour, 28 Minutes
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  1 Hour, 40 Minutes

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NVIDIA Linux OpenCL CUDA RTX SUPER ComputeOpenBenchmarking.orgPhoronix Test SuiteIntel Core i9-9900K @ 5.00GHz (8 Cores / 16 Threads)ASUS PRIME Z390-A (0802 BIOS)Intel Cannon Lake PCH16384MBSamsung SSD 970 EVO 250GBeVGA NVIDIA GeForce GTX 970 4GB (1163/3505MHz)NVIDIA GeForce GTX 980 4GB (1126/3505MHz)NVIDIA GeForce GTX 980 Ti 6GB (999/3505MHz)NVIDIA GeForce GTX 1060 6GB (1506/4006MHz)NVIDIA GeForce GTX 1070 8GB (1506/4006MHz)Zotac NVIDIA GeForce GTX 1070 Ti 8GB (1607/4006MHz)NVIDIA GeForce GTX 1080 8GB (1607/5005MHz)NVIDIA GeForce GTX 1080 Ti 11GB (1480/5508MHz)ASUS NVIDIA GeForce GTX 1660 6GB (1530/4001MHz)eVGA NVIDIA GeForce GTX 1660 Ti 6GB (1500/6000MHz)NVIDIA GeForce RTX 2060 6GB (1365/7000MHz)NVIDIA GeForce RTX 2060 SUPER 8GB (1470/7000MHz)ASUS NVIDIA GeForce RTX 2070 8GB (1410/7000MHz)NVIDIA GeForce RTX 2070 SUPER 8GB (1605/7000MHz)Zotac NVIDIA GeForce RTX 2080 8GB (795/810MHz)NVIDIA GeForce RTX 2080 SUPER 8GB (1650/7750MHz)NVIDIA GeForce RTX 2080 Ti 11GB (1350/7000MHz)NVIDIA TITAN RTX 24GB (1350/7000MHz)Realtek ALC1220Acer B286HKIntel I219-VUbuntu 19.045.0.0-29-generic (x86_64)5.3.0-999-generic (x86_64) 20190914GNOME Shell 3.32.2X Server 1.20.4NVIDIA 435.214.6.0GCC 8.3.0ext43840x2160ProcessorMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelsDesktopDisplay ServerDisplay DriverOpenGLCompilerFile-SystemScreen ResolutionNVIDIA Linux OpenCL CUDA RTX SUPER Compute BenchmarksSystem Logs- --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++ --enable-libmpx --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -v - Scaling Governor: intel_pstate performance- GTX 970: GPU Compute Cores: 1664- GTX 980: GPU Compute Cores: 2048- GTX 980 Ti: GPU Compute Cores: 2816- GTX 1060: GPU Compute Cores: 1280- GTX 1070: GPU Compute Cores: 1920- GTX 1070 Ti: GPU Compute Cores: 2432- GTX 1080: GPU Compute Cores: 2560- GTX 1080 Ti: GPU Compute Cores: 3584- GTX 1660: GPU Compute Cores: 1408- GTX 1660 Ti: GPU Compute Cores: 1536- RTX 2060: GPU Compute Cores: 1920- RTX 2060 SUPER: GPU Compute Cores: 2176- RTX 2070: GPU Compute Cores: 2304- RTX 2070 SUPER: GPU Compute Cores: 2560- RTX 2080: GPU Compute Cores: 2944- RTX 2080 SUPER: GPU Compute Cores: 3072- RTX 2080 Ti: GPU Compute Cores: 4352- TITAN RTX: GPU Compute Cores: 4608- GTX 970, GTX 980, GTX 980 Ti, GTX 1060, GTX 1070, GTX 1070 Ti, GTX 1080, GTX 1080 Ti, GTX 1660, GTX 1660 Ti, RTX 2060, RTX 2070, RTX 2070 SUPER, RTX 2080, RTX 2080 SUPER, RTX 2080 Ti, TITAN RTX: Python 2.7.16 + Python 3.7.3 - l1tf: Not affected + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full generic retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling

GTX 970GTX 980GTX 980 TiGTX 1060GTX 1070GTX 1070 TiGTX 1080GTX 1080 TiGTX 1660GTX 1660 TiRTX 2060RTX 2060 SUPERRTX 2070RTX 2070 SUPERRTX 2080RTX 2080 SUPERRTX 2080 TiTITAN RTXLogarithmic Result OverviewPhoronix Test SuiteclpeakSHOC Scalable HeterOgeneous ComputingLuxMarkPlaidMLOctaneBenchcl-memFAHBenchDarktableRodiniaLeelaChessZeroNAMD CUDAJuliaGPUViennaCL

GTX 970GTX 980GTX 980 TiGTX 1060GTX 1070GTX 1070 TiGTX 1080GTX 1080 TiGTX 1660GTX 1660 TiRTX 2060RTX 2060 SUPERRTX 2070RTX 2070 SUPERRTX 2080RTX 2080 SUPERRTX 2080 TiTITAN RTXLogarithmic Per Watt Result OverviewPhoronix Test SuiteclpeakPlaidMLcl-memSHOC Scalable HeterOgeneous ComputingJuliaGPUViennaCLFAHBenchLuxMarkLeelaChessZeroOctaneBenchP.W.G.MP.W.G.MP.W.G.MP.W.G.MP.W.G.MP.W.G.MP.W.G.MP.W.G.MP.W.G.MP.W.G.M

NVIDIA Linux OpenCL CUDA RTX SUPER Computeshoc: OpenCL - MD5 Hashshoc: OpenCL - FFT SPluxmark: GPU - Microphonedarktable: Server Room - OpenCLplaidml: Yes - Inference - Inception V3 - OpenCLplaidml: Yes - Inference - VGG19 - OpenCLplaidml: No - Inference - VGG19 - OpenCLplaidml: Yes - Inference - VGG16 - OpenCLplaidml: No - Inference - VGG16 - OpenCLplaidml: Yes - Inference - NASNer Large - OpenCLcl-mem: Readclpeak: Double-Precision Doubleshoc: OpenCL - Max SP Flopsluxmark: GPU - Luxball HDRplaidml: No - Inference - IMDB LSTM - OpenCLplaidml: Yes - Inference - ResNet 50 - OpenCLcl-mem: Writeluxmark: GPU - Hotelclpeak: Global Memory Bandwidthplaidml: No - Inference - Mobilenet - OpenCLplaidml: No - Inference - Inception V3 - OpenCLclpeak: Single-Precision Floatplaidml: No - Inference - ResNet 50 - OpenCLoctanebench: Total Scoreplaidml: Yes - Inference - Mobilenet - OpenCLplaidml: Yes - Inference - DenseNet 201 - OpenCLfahbench: rodinia: OpenCL Particle Filterdarktable: Boat - OpenCLcl-mem: Copylczero: OpenCLclpeak: Integer Compute INTnamd-cuda: ATPase Simulation - 327,506 Atomsjuliagpu: GPUrodinia: OpenCL Myocytedarktable: Masskrug - OpenCLviennacl: OpenCL LU FactorizationGTX 970GTX 980GTX 980 TiGTX 1060GTX 1070GTX 1070 TiGTX 1080GTX 1080 TiGTX 1660GTX 1660 TiRTX 2060RTX 2060 SUPERRTX 2070RTX 2070 SUPERRTX 2080RTX 2080 SUPERRTX 2080 TiTITAN RTX6.50411.2979853.1688.1639.3447.7049.7660.3221.42142.10137.474362.3111732204.32116.05132.602730143.48671.4994.723888.16181.8795.60841.4879.7191.5312.994.42124.77207.841140.290.36368169258044.9045.485.7856.957.49458.3589143.10101.9243.6353.4955.7068.9524.24164.50159.685052.7313246231.66142.14151.503048164.25759.43105.644476.69203.91109.70973.3992.92102.8611.693.92143.40280.991312.060.33110181882709.7747.385.7459.219.22725.98110961.51116.3156.1368.4771.2687.3930.64265.33196.606213.9716871270.00162.63241.503885263.22990.12135.145538.75247.47142.201202.77111.46116.029.953.27216.83466.841610.280.28675195653728.4752.134.1262.017.26326.6870861.2897.8344.3754.7856.0769.3123.16153.50149.584788.9212245224.89130.64144.572648146.62726.30104.444199.71196.0091.44908.4391.07102.6111.933.65137.20262.411267.890.31789182188318.6734.694.0758.6710.61478.5499831.11141.5563.5676.8980.2797.3233.07205.27223.917115.3917290315.37196.01190.903870196.47987.69147.176269.49276.89132.861288.94127.02140.298.262.89182.00642.121685.050.23957216942144.9335.103.9263.8611.70525.89102591.17147.0473.1290.3492.03114.0335.41205.27242.637715.4216925333.03205.85190.034170197.261009.26153.346770.97294.36141.351371.21130.15138.217.882.93182.70753.692076.930.22269220447755.8738.703.9764.6814.25614.6987161.09173.7983.83101.00106.09128.0540.38228.80297.949407.7513788399.00240.62214.673807222.091123.85184.808314.29337.47147.981544.50143.53155.226.492.72205.931146.752430.740.20978237914974.4034.873.9466.6719.72982.23137211.05228.68115.03138.68145.42175.3756.64337.53414.9613230.7721689523.98333.54340.275649328.901672.73257.5511720.57496.24212.042162.58191.31198.254.962.29283.201886.303301.890.19669262248899.3335.913.9269.0911.87452.8997941.18137.6652.5267.2466.2484.8328.99162.90168.445329.8415162287.68156.50148.873733157.60814.65116.904610.01228.14118.491160.52102.83126.6411.873.35145.37335.864657.790.25031230919642.1330.974.0165.1012.98665.66110031.15161.3358.0373.3573.1892.4534.12250.23185.125893.4116147315.83172.68208.673805234.671002.00140.054793.66259.43132.281394.05114.58139.8110.822.92208.50420.044775.450.23185239300837.6030.674.0266.0616.04818.44137540.83193.7571.0788.0489.55110.9341.11296.20231.447320.7321683389.40220.44241.204833275.861232.47167.875329.07319.25164.521694.07154.19183.418.902.22237.77704.695269.010.20250251925176.9031.113.7367.9218.22971.24185090.75219.7680.82101.17102.58128.2248.96395.67263.118378.8730093440.79250.98333.206148367.921531.01199.437089.50374.71205.231983.82179.51205.207.871.95287.80998.177023.070.19336264172441.4730.423.6869.1718.77976.78184410.75220.9983.56103.89105.60131.5449.94395.70268.328528.7030097446.23251.07322.676150368.961516.96198.037198.64376.73206.881969.50176.49204.717.751.93284.43999.757161.480.19440267086274.5331.643.6769.4121.781088.17204990.80239.6197.82122.32123.20154.6455.24395.67310.279869.3429734499.69283.98319.576565369.111649.17215.858502.71421.58220.762264.97190.01229.126.821.93291.871604.218570.600.19501275868151.1730.763.7170.4524.071100.00199160.80268.33105.54129.58133.20164.0558.47395.70345.8110952.7729164548.83305.76331.506590368.471663.87238.738883.90441.24222.882292.38189.28242.756.221.90289.201879.999660.920.19307280162469.6731.653.7170.9626.561203.57201640.79301.11115.44143.02145.65180.4564.80436.27378.9812015.5030179589.86327.80345.776839405.001762.00259.2610335.50468.70233.562437.48200.38256.835.741.82301.232105.2610404.710.19385286818331.2730.633.6971.4734.911485.73286310.75363.16154.20186.19194.83234.6584.97544.33521.9016656.2042974758.21424.07441.239215506.332335.46343.4913532.74634.09309.042750.57254.45301.894.391.64324.403032.1013609.330.18909299834728.8031.053.6672.7136.391578.29307560.74373.71162.05196.44204.67247.8387.17566.70547.9717334.0046546790.77433.81495.379836528.892466.66347.9314203.87648.36322.762842.38263.13301.934.241.64322.203126.4813841.250.18867303198573.9731.693.6672.96OpenBenchmarking.org

SHOC Scalable HeterOgeneous Computing

OpenBenchmarking.orgGHash/s Per Watt, More Is BetterSHOC Scalable HeterOgeneous Computing 2015-11-10Target: OpenCL - Benchmark: MD5 HashGTX 980 TiGTX 970GTX 980GTX 1060RTX 2060GTX 1080RTX 2070RTX 2080GTX 1660GTX 1660 TiRTX 2070 SUPERRTX 2080 SUPERTITAN RTX0.08330.16660.24990.33320.41650.040.050.080.110.120.150.150.210.260.260.300.320.37

NAMD CUDA

OpenBenchmarking.orgWatts, Fewer Is BetterNAMD CUDA 2.13System Power Consumption MonitorGTX 980 TiGTX 1080 TiGTX 970GTX 1080RTX 2080 TiGTX 980RTX 2080RTX 2060 SUPERRTX 2080 SUPERTITAN RTXGTX 1070RTX 2070GTX 1070 TiGTX 1060RTX 2070 SUPERRTX 2060GTX 1660GTX 1660 Ti70140210280350Min: 55.9 / Avg: 272.91 / Max: 370.3Min: 55.3 / Avg: 266.23 / Max: 380Min: 51.3 / Avg: 258.19 / Max: 306.3Min: 48.6 / Avg: 253.18 / Max: 326.9Min: 53.9 / Avg: 251.92 / Max: 374Min: 52.6 / Avg: 238.95 / Max: 329.4Min: 52.9 / Avg: 238.49 / Max: 342.9Min: 48.4 / Avg: 233.81 / Max: 312Min: 48.8 / Avg: 219.44 / Max: 330.5Min: 54.3 / Avg: 214.96 / Max: 367.7Min: 48.2 / Avg: 206.59 / Max: 286.9Min: 50 / Avg: 202.69 / Max: 321.3Min: 50.3 / Avg: 198.82 / Max: 259.9Min: 45.2 / Avg: 198.8 / Max: 269.5Min: 47.2 / Avg: 198.42 / Max: 323.3Min: 46.1 / Avg: 197.89 / Max: 303.8Min: 44.9 / Avg: 177.54 / Max: 262.4Min: 47.7 / Avg: 177.22 / Max: 273.9

SHOC Scalable HeterOgeneous Computing

OpenBenchmarking.orgWatts, Fewer Is BetterSHOC Scalable HeterOgeneous Computing 2015-11-10System Power Consumption MonitorTITAN RTXRTX 2080 TiGTX 1080 TiGTX 980 TiRTX 2080RTX 2080 SUPERGTX 980GTX 1080RTX 2070 SUPERRTX 2070GTX 970RTX 2060 SUPERRTX 2060GTX 1070GTX 1070 TiGTX 1060GTX 1660 TiGTX 166070140210280350Min: 52 / Avg: 223.03 / Max: 367Min: 51.3 / Avg: 217.17 / Max: 360Min: 49.6 / Avg: 199.67 / Max: 326.6Min: 126.9 / Avg: 193.91 / Max: 298.6Min: 48.7 / Avg: 171.33 / Max: 292.2Min: 47 / Avg: 164.08 / Max: 318.6Min: 97.6 / Avg: 160.93 / Max: 243.5Min: 94 / Avg: 157.13 / Max: 259.6Min: 47.1 / Avg: 150.09 / Max: 265.5Min: 47.9 / Avg: 149.29 / Max: 251.7Min: 80.6 / Avg: 148.92 / Max: 222.7Min: 46.8 / Avg: 148.63 / Max: 238Min: 47 / Avg: 145.37 / Max: 229.5Min: 78 / Avg: 141.46 / Max: 206.4Min: 50.5 / Avg: 125.61 / Max: 179.8Min: 74.8 / Avg: 119.53 / Max: 184.8Min: 46.4 / Avg: 118.75 / Max: 170.7Min: 44.5 / Avg: 106.24 / Max: 161

LeelaChessZero

OpenBenchmarking.orgWatts, Fewer Is BetterLeelaChessZero 0.22.0System Power Consumption MonitorGTX 980 TiGTX 1080 TiTITAN RTXRTX 2070 SUPERRTX 2080RTX 2070RTX 2080 SUPERGTX 970GTX 1080GTX 980GTX 1070RTX 2060 SUPERRTX 2060GTX 1060GTX 1660 TiGTX 1070 TiGTX 166070140210280350Min: 59.1 / Avg: 216.14 / Max: 319.4Min: 106.6 / Avg: 215.46 / Max: 320.5Min: 53.3 / Avg: 197.7 / Max: 371.4Min: 47.2 / Avg: 178.69 / Max: 276Min: 52.8 / Avg: 175.13 / Max: 286.6Min: 48.6 / Avg: 172.95 / Max: 253.7Min: 47.5 / Avg: 170.9 / Max: 315Min: 82.3 / Avg: 164.63 / Max: 252.9Min: 48.8 / Avg: 161.47 / Max: 252.9Min: 51.8 / Avg: 153.94 / Max: 247.5Min: 71.9 / Avg: 152.4 / Max: 214.7Min: 45.5 / Avg: 151.83 / Max: 241.9Min: 49.1 / Avg: 147.07 / Max: 231.4Min: 47.2 / Avg: 138.37 / Max: 187.2Min: 47.9 / Avg: 134.26 / Max: 195.9Min: 52 / Avg: 128.59 / Max: 197.7Min: 46.5 / Avg: 118.46 / Max: 180.4

LuxMark

OpenBenchmarking.orgWatts, Fewer Is BetterLuxMark 3.1System Power Consumption MonitorTITAN RTXRTX 2080 TiGTX 1080 TiRTX 2080GTX 980 TiRTX 2080 SUPERRTX 2070 SUPERRTX 2070RTX 2060 SUPERGTX 980RTX 2060GTX 1080GTX 970GTX 1070GTX 1660 TiGTX 1070 TiGTX 1060GTX 166070140210280350Min: 57.7 / Avg: 358.16 / Max: 371Min: 54.2 / Avg: 341.41 / Max: 361Min: 55.9 / Avg: 282.16 / Max: 295.6Min: 52.6 / Avg: 269.03 / Max: 281.5Min: 57.2 / Avg: 255.39 / Max: 271.7Min: 50.8 / Avg: 249.5 / Max: 264.2Min: 47.6 / Avg: 241.53 / Max: 254.1Min: 51.8 / Avg: 241 / Max: 251.5Min: 47.9 / Avg: 233.07 / Max: 242.2Min: 51.4 / Avg: 215.19 / Max: 226.6Min: 50.4 / Avg: 210.86 / Max: 220.4Min: 47.9 / Avg: 205.71 / Max: 214.4Min: 50.9 / Avg: 198.98 / Max: 206.3Min: 48.8 / Avg: 197.56 / Max: 206Min: 47.2 / Avg: 169.1 / Max: 176.4Min: 51.1 / Avg: 162.66 / Max: 167.9Min: 45.7 / Avg: 155.74 / Max: 161.6Min: 46.7 / Avg: 154.16 / Max: 157.9

PlaidML

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorGTX 980 TiTITAN RTXRTX 2080 TiGTX 1080 TiRTX 2080RTX 2080 SUPERGTX 1080GTX 980GTX 970RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 1070GTX 1070 TiGTX 1060GTX 1660 TiGTX 166060120180240300Min: 119.7 / Avg: 273.57 / Max: 330.8Min: 53.2 / Avg: 260.22 / Max: 361.7Min: 52.9 / Avg: 251.39 / Max: 354Min: 55.7 / Avg: 245.95 / Max: 321.1Min: 49.9 / Avg: 230.45 / Max: 288.2Min: 49.5 / Avg: 224.18 / Max: 302.6Min: 89.9 / Avg: 209.47 / Max: 253.5Min: 55.7 / Avg: 208.34 / Max: 246.7Min: 75.4 / Avg: 201.26 / Max: 220.7Min: 47.5 / Avg: 199.98 / Max: 276.8Min: 49.7 / Avg: 197.21 / Max: 252.5Min: 55 / Avg: 193.52 / Max: 240.6Min: 50.1 / Avg: 192.21 / Max: 230.7Min: 84.2 / Avg: 180.68 / Max: 209.8Min: 52.4 / Avg: 180.41 / Max: 207.7Min: 45.1 / Avg: 170.04 / Max: 188.8Min: 48.3 / Avg: 167.7 / Max: 196.3Min: 46 / Avg: 160.67 / Max: 185.8

OctaneBench

OpenBenchmarking.orgWatts, Fewer Is BetterOctaneBench 4.00cSystem Power Consumption MonitorTITAN RTXRTX 2080 TiRTX 2080GTX 1080 TiRTX 2080 SUPERGTX 980 TiRTX 2070RTX 2070 SUPERRTX 2060 SUPERRTX 2060GTX 980GTX 1080GTX 970GTX 1070GTX 1660 TiGTX 1070 TiGTX 1660GTX 106060120180240300Min: 55.3 / Avg: 326.69 / Max: 357.7Min: 51.7 / Avg: 322.94 / Max: 355.5Min: 50 / Avg: 239.21 / Max: 278.1Min: 130.6 / Avg: 236.94 / Max: 265Min: 47.8 / Avg: 225.1 / Max: 261.8Min: 128.3 / Avg: 220.62 / Max: 240Min: 47.1 / Avg: 215.17 / Max: 242.1Min: 49 / Avg: 211.57 / Max: 245.6Min: 46.5 / Avg: 210.53 / Max: 232.6Min: 49.8 / Avg: 188.5 / Max: 218.2Min: 53.6 / Avg: 178.66 / Max: 203.2Min: 48.3 / Avg: 167.77 / Max: 228.3Min: 50.8 / Avg: 160.22 / Max: 180Min: 86 / Avg: 157.88 / Max: 173.8Min: 47.1 / Avg: 145.79 / Max: 161.1Min: 52.2 / Avg: 132.45 / Max: 182.7Min: 46.3 / Avg: 127.11 / Max: 144.7Min: 44.9 / Avg: 120.33 / Max: 135.2

PlaidML

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorGTX 980 TiTITAN RTXRTX 2080 TiGTX 1080 TiRTX 2080 SUPERGTX 980GTX 1080RTX 2080GTX 970RTX 2070RTX 2070 SUPERRTX 2060 SUPERRTX 2060GTX 1070GTX 1070 TiGTX 1060GTX 1660 TiGTX 166060120180240300Min: 56.5 / Avg: 270.73 / Max: 328.7Min: 52.4 / Avg: 239.94 / Max: 363Min: 52.7 / Avg: 239.16 / Max: 354.3Min: 51.8 / Avg: 234.29 / Max: 318.4Min: 47.7 / Avg: 218.91 / Max: 299.1Min: 90.4 / Avg: 213.83 / Max: 251.4Min: 46.2 / Avg: 209.24 / Max: 254.3Min: 48.9 / Avg: 201.23 / Max: 285.7Min: 94.5 / Avg: 195.88 / Max: 219.3Min: 48.4 / Avg: 193.79 / Max: 250.6Min: 47.2 / Avg: 191.71 / Max: 276.3Min: 53.3 / Avg: 181.51 / Max: 239.5Min: 48.4 / Avg: 179.22 / Max: 228.5Min: 50 / Avg: 172.78 / Max: 208.8Min: 52.3 / Avg: 169.99 / Max: 205.7Min: 69.4 / Avg: 166.46 / Max: 190Min: 46.4 / Avg: 163.81 / Max: 195.7Min: 45.6 / Avg: 146.27 / Max: 182

clpeak

OpenBenchmarking.orgWatts, Fewer Is BetterclpeakSystem Power Consumption MonitorTITAN RTXGTX 1080 TiRTX 2080 SUPERRTX 2070 SUPERRTX 2070GTX 1060RTX 2060 SUPERGTX 1660 Ti70140210280350Min: 52.5 / Avg: 207.88 / Max: 366.7Min: 52.4 / Avg: 199.89 / Max: 328.7Min: 47.9 / Avg: 144.19 / Max: 288.8Min: 47.5 / Avg: 141.91 / Max: 279.4Min: 47.8 / Avg: 135.68 / Max: 254.5Min: 66.2 / Avg: 117.06 / Max: 191Min: 47.4 / Avg: 86.98 / Max: 242.5Min: 46.4 / Avg: 77.81 / Max: 158.1

LuxMark

OpenBenchmarking.orgWatts, Fewer Is BetterLuxMark 3.1System Power Consumption MonitorTITAN RTXRTX 2080 TiGTX 1080 TiRTX 2080GTX 980 TiRTX 2070RTX 2080 SUPERRTX 2060 SUPERRTX 2070 SUPERGTX 980RTX 2060GTX 1070GTX 970GTX 1080GTX 1660 TiGTX 1070 TiGTX 1060GTX 166060120180240300Min: 53.7 / Avg: 338.9 / Max: 360.6Min: 53.9 / Avg: 326.39 / Max: 340.7Min: 107.7 / Avg: 245.73 / Max: 254Min: 52.5 / Avg: 244.9 / Max: 255.3Min: 130.4 / Avg: 238.82 / Max: 247.5Min: 50.1 / Avg: 230.98 / Max: 243.5Min: 49.4 / Avg: 230.52 / Max: 238Min: 47.2 / Avg: 229.14 / Max: 241Min: 47.5 / Avg: 217.27 / Max: 227.7Min: 87.7 / Avg: 195.16 / Max: 205Min: 47.4 / Avg: 192.86 / Max: 200.8Min: 48.6 / Avg: 181.94 / Max: 188.2Min: 52.2 / Avg: 180.29 / Max: 185.6Min: 75.8 / Avg: 180.11 / Max: 185.5Min: 48.2 / Avg: 157.16 / Max: 163.8Min: 52.3 / Avg: 151.74 / Max: 155.9Min: 76 / Avg: 146.92 / Max: 152Min: 45.9 / Avg: 139.49 / Max: 144

PlaidML

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorGTX 980 TiGTX 1080 TiTITAN RTXRTX 2080 TiRTX 2060 SUPERGTX 980RTX 2070 SUPERRTX 2080 SUPERGTX 1080GTX 970RTX 2070RTX 2080RTX 2060GTX 1070GTX 1070 TiGTX 1060GTX 1660 TiGTX 166060120180240300Min: 71.2 / Avg: 244.52 / Max: 316.6Min: 120.6 / Avg: 236.48 / Max: 318.6Min: 52.8 / Avg: 227.24 / Max: 356.3Min: 52.9 / Avg: 210.77 / Max: 350.6Min: 57.1 / Avg: 209.61 / Max: 237.5Min: 53.3 / Avg: 201.25 / Max: 246.9Min: 47.2 / Avg: 198.27 / Max: 271.7Min: 49.1 / Avg: 194.92 / Max: 278.5Min: 91.2 / Avg: 194.23 / Max: 252.2Min: 89.6 / Avg: 193.7 / Max: 220.3Min: 48.7 / Avg: 189.06 / Max: 250.5Min: 52.6 / Avg: 181.66 / Max: 277.7Min: 48.9 / Avg: 179.62 / Max: 228Min: 70.7 / Avg: 170.23 / Max: 208.9Min: 51.9 / Avg: 158.16 / Max: 196.1Min: 45.9 / Avg: 157.15 / Max: 187.3Min: 48.2 / Avg: 154.23 / Max: 191.6Min: 45.5 / Avg: 136.67 / Max: 171.6

LuxMark

OpenBenchmarking.orgWatts, Fewer Is BetterLuxMark 3.1System Power Consumption MonitorTITAN RTXRTX 2080 TiRTX 2080GTX 1080 TiGTX 980 TiRTX 2080 SUPERRTX 2060 SUPERRTX 2070 SUPERRTX 2070GTX 980RTX 2060GTX 970GTX 1080GTX 1070GTX 1660 TiGTX 1070 TiGTX 1060GTX 166060120180240300Min: 60.2 / Avg: 337.98 / Max: 356.9Min: 55.9 / Avg: 318.95 / Max: 337.2Min: 53.8 / Avg: 241.11 / Max: 251.4Min: 52.7 / Avg: 237.89 / Max: 245.4Min: 112.5 / Avg: 234.81 / Max: 244.3Min: 47.8 / Avg: 225.09 / Max: 235.4Min: 49.8 / Avg: 222.76 / Max: 232.3Min: 47.6 / Avg: 220.93 / Max: 232.4Min: 51.5 / Avg: 219.74 / Max: 234.1Min: 51 / Avg: 193.46 / Max: 203.7Min: 48.6 / Avg: 190.73 / Max: 198.4Min: 51.9 / Avg: 177.8 / Max: 184.4Min: 49.1 / Avg: 173.32 / Max: 180.3Min: 49 / Avg: 170.27 / Max: 177.6Min: 48 / Avg: 156.46 / Max: 161.4Min: 50.1 / Avg: 145.89 / Max: 150.4Min: 45.6 / Avg: 138.57 / Max: 144.8Min: 46 / Avg: 137.52 / Max: 142.7

PlaidML

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorGTX 980 TiGTX 1080 TiTITAN RTXGTX 980GTX 1080RTX 2080 TiRTX 2060 SUPERRTX 2070 SUPERGTX 970RTX 2080 SUPERRTX 2070RTX 2080RTX 2060GTX 1070GTX 1070 TiGTX 1060GTX 1660 TiGTX 166060120180240300Min: 55.1 / Avg: 244.29 / Max: 316.2Min: 118 / Avg: 235.58 / Max: 316.5Min: 53.8 / Avg: 216.91 / Max: 353.5Min: 69.1 / Avg: 196.2 / Max: 247.2Min: 88.2 / Avg: 189.28 / Max: 251.8Min: 52.7 / Avg: 188.04 / Max: 345.4Min: 54 / Avg: 187.95 / Max: 233.7Min: 46.7 / Avg: 187.65 / Max: 267.6Min: 51.5 / Avg: 184.27 / Max: 233.4Min: 49.4 / Avg: 181.31 / Max: 274.6Min: 48.1 / Avg: 174.02 / Max: 249.3Min: 54.1 / Avg: 173.35 / Max: 273.1Min: 48.1 / Avg: 163.79 / Max: 226.4Min: 47.7 / Avg: 162.2 / Max: 207.3Min: 95.2 / Avg: 160.1 / Max: 191.4Min: 45.8 / Avg: 152.31 / Max: 187.6Min: 47.3 / Avg: 151.58 / Max: 191.5Min: 45.6 / Avg: 137.8 / Max: 169.2

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorGTX 1080 TiGTX 980 TiTITAN RTXRTX 2080 TiRTX 2080 SUPERGTX 1080RTX 2080GTX 980GTX 970RTX 2060 SUPERRTX 2070RTX 2070 SUPERGTX 1070RTX 2060GTX 1060GTX 1660 TiGTX 1070 TiGTX 166060120180240300Min: 107 / Avg: 238.78 / Max: 315.7Min: 124.3 / Avg: 237.03 / Max: 284.6Min: 51.3 / Avg: 235.38 / Max: 341.7Min: 50.4 / Avg: 231.53 / Max: 336Min: 46.7 / Avg: 204.84 / Max: 277Min: 48.2 / Avg: 203.49 / Max: 246Min: 49.7 / Avg: 201.32 / Max: 272.7Min: 99.4 / Avg: 199.9 / Max: 241.3Min: 94.8 / Avg: 192.64 / Max: 216.8Min: 54.2 / Avg: 192.58 / Max: 235.4Min: 48 / Avg: 190.9 / Max: 247Min: 46.5 / Avg: 184.51 / Max: 249.7Min: 83.7 / Avg: 182.29 / Max: 211.2Min: 48.1 / Avg: 176.3 / Max: 224.1Min: 75.4 / Avg: 157.49 / Max: 178.6Min: 46.5 / Avg: 154.44 / Max: 184.5Min: 51.4 / Avg: 151.49 / Max: 175.5Min: 44.8 / Avg: 135.27 / Max: 159.9

FAHBench

OpenBenchmarking.orgWatts, Fewer Is BetterFAHBench 2.3.2System Power Consumption MonitorTITAN RTXRTX 2080 TiGTX 1080 TiGTX 980 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2060 SUPERGTX 980RTX 2070GTX 1080RTX 2060GTX 970GTX 1070GTX 1660 TiGTX 1070 TiGTX 1060GTX 166060120180240300Min: 52.5 / Avg: 226.18 / Max: 324.2Min: 49.7 / Avg: 218.05 / Max: 323.3Min: 77.6 / Avg: 195.24 / Max: 264.4Min: 56.3 / Avg: 186.17 / Max: 244.4Min: 64 / Avg: 177.55 / Max: 252.2Min: 47.5 / Avg: 176.01 / Max: 263Min: 46.6 / Avg: 161.4 / Max: 230Min: 48.5 / Avg: 161.35 / Max: 226.3Min: 49.8 / Avg: 159.19 / Max: 211.9Min: 46 / Avg: 158.7 / Max: 226.7Min: 44.9 / Avg: 154.62 / Max: 208.2Min: 45.7 / Avg: 151.46 / Max: 214.2Min: 48.8 / Avg: 147.69 / Max: 193Min: 43.8 / Avg: 145.58 / Max: 193.2Min: 47.6 / Avg: 127.19 / Max: 170.3Min: 49.1 / Avg: 125.16 / Max: 155Min: 66.3 / Avg: 124.04 / Max: 159.6Min: 46.5 / Avg: 114.3 / Max: 152.8

PlaidML

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorGTX 980 TiRTX 2080 TiGTX 1080GTX 1080 TiGTX 980GTX 970TITAN RTXRTX 2080RTX 2080 SUPERRTX 2070RTX 2060 SUPERRTX 2070 SUPERRTX 2060GTX 1060GTX 1070GTX 1070 TiGTX 1660 TiGTX 166060120180240300Min: 126.5 / Avg: 220.09 / Max: 281.6Min: 51.8 / Avg: 206.66 / Max: 321.6Min: 84.7 / Avg: 196.13 / Max: 242.5Min: 128 / Avg: 191.53 / Max: 304Min: 56.7 / Avg: 188.31 / Max: 242.7Min: 81.4 / Avg: 182.54 / Max: 219.9Min: 56.2 / Avg: 178.56 / Max: 327.6Min: 49.4 / Avg: 176.08 / Max: 254.9Min: 49.6 / Avg: 170.73 / Max: 255.1Min: 49.8 / Avg: 167.7 / Max: 230.4Min: 54.4 / Avg: 162.79 / Max: 223.8Min: 49.5 / Avg: 161.34 / Max: 234.9Min: 47.6 / Avg: 150.66 / Max: 214.3Min: 46.9 / Avg: 150.12 / Max: 180Min: 84.3 / Avg: 149.15 / Max: 206.1Min: 51.1 / Avg: 141.76 / Max: 172.5Min: 46.3 / Avg: 136.65 / Max: 177.5Min: 46.3 / Avg: 123.06 / Max: 152.7

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorGTX 980 TiGTX 1080 TiGTX 980GTX 970RTX 2080 SUPERGTX 1070GTX 1080RTX 2060RTX 2070 SUPERRTX 2060 SUPERGTX 1660 TiGTX 1070 TiRTX 2080GTX 1060TITAN RTXRTX 2070GTX 166060120180240300Min: 129.1 / Avg: 233.7 / Max: 292Min: 56.4 / Avg: 186.43 / Max: 312.7Min: 53 / Avg: 176.69 / Max: 244.6Min: 83.3 / Avg: 172.91 / Max: 233.2Min: 49.4 / Avg: 162.94 / Max: 270.3Min: 89.6 / Avg: 153.55 / Max: 208.4Min: 48.4 / Avg: 149.71 / Max: 246.6Min: 48.6 / Avg: 147.64 / Max: 221.8Min: 46.8 / Avg: 145.98 / Max: 249.6Min: 55.4 / Avg: 144.71 / Max: 231.4Min: 47.9 / Avg: 141.14 / Max: 182.8Min: 52.2 / Avg: 140.17 / Max: 177.3Min: 52 / Avg: 137.63 / Max: 231.8Min: 45.9 / Avg: 132.6 / Max: 182.3Min: 52.7 / Avg: 128.84 / Max: 167.9Min: 47.5 / Avg: 122.1 / Max: 239.9Min: 46.3 / Avg: 119.8 / Max: 159.7

clpeak

OpenBenchmarking.orgWatts, Fewer Is BetterclpeakSystem Power Consumption MonitorTITAN RTXGTX 980 TiGTX 980GTX 970RTX 2070RTX 2070 SUPERGTX 1660 TiRTX 2060 SUPER60120180240300Min: 50.6 / Avg: 137.09 / Max: 308.7Min: 54.9 / Avg: 131.87 / Max: 194.2Min: 52.5 / Avg: 122.69 / Max: 181.1Min: 51.4 / Avg: 98.78 / Max: 148.8Min: 48.2 / Avg: 96.86 / Max: 180.2Min: 47.5 / Avg: 69.91 / Max: 138.9Min: 45.5 / Avg: 67.18 / Max: 127.1Min: 46.6 / Avg: 63.45 / Max: 103

PlaidML

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorGTX 980 TiGTX 1080 TiGTX 980TITAN RTXRTX 2080 TiGTX 970GTX 1080GTX 1070RTX 2070RTX 2080 SUPERRTX 2060 SUPERRTX 2060RTX 2080RTX 2070 SUPERGTX 1070 TiGTX 1060GTX 1660 TiGTX 166050100150200250Min: 127.5 / Avg: 205.03 / Max: 260.5Min: 55.7 / Avg: 189.84 / Max: 284.9Min: 52.8 / Avg: 183.08 / Max: 228.8Min: 55.6 / Avg: 169.21 / Max: 293Min: 51.5 / Avg: 167.74 / Max: 291.7Min: 81.7 / Avg: 163.48 / Max: 201.2Min: 94.6 / Avg: 159.56 / Max: 227.4Min: 77.9 / Avg: 157.58 / Max: 202.6Min: 49 / Avg: 148.17 / Max: 210.6Min: 48.5 / Avg: 147.96 / Max: 225.2Min: 54.4 / Avg: 144.26 / Max: 207.2Min: 47.9 / Avg: 142.09 / Max: 199.4Min: 50.7 / Avg: 139.72 / Max: 234.8Min: 47.9 / Avg: 135.09 / Max: 211.7Min: 51.5 / Avg: 131.42 / Max: 162.8Min: 68.7 / Avg: 129.36 / Max: 164Min: 47.3 / Avg: 117.8 / Max: 162Min: 44.8 / Avg: 109.89 / Max: 143.5

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorGTX 1080 TiGTX 980 TiTITAN RTXRTX 2080 TiGTX 980GTX 970GTX 1080RTX 2080RTX 2080 SUPERGTX 1070RTX 2060 SUPERRTX 2060RTX 2070RTX 2070 SUPERGTX 1070 TiGTX 1060GTX 1660 TiGTX 166050100150200250Min: 125.6 / Avg: 201.87 / Max: 257Min: 128.3 / Avg: 193.81 / Max: 239.9Min: 51.1 / Avg: 182.86 / Max: 282.6Min: 50.7 / Avg: 178.03 / Max: 280Min: 99.3 / Avg: 168.06 / Max: 211.7Min: 72.9 / Avg: 158.81 / Max: 190.7Min: 84.5 / Avg: 158.48 / Max: 204.6Min: 49 / Avg: 153.24 / Max: 230.1Min: 48.4 / Avg: 151.02 / Max: 226.9Min: 70.5 / Avg: 148.83 / Max: 185.2Min: 53 / Avg: 147.84 / Max: 203.6Min: 48.8 / Avg: 144.1 / Max: 197.4Min: 47.6 / Avg: 141.04 / Max: 207.9Min: 46.6 / Avg: 139.53 / Max: 205.1Min: 51 / Avg: 131.33 / Max: 154.1Min: 55.5 / Avg: 124.66 / Max: 155.7Min: 46.7 / Avg: 122.59 / Max: 164Min: 44.4 / Avg: 112.99 / Max: 143

clpeak

OpenBenchmarking.orgGFLOPS Per Watt, More Is BetterclpeakOpenCL Test: Single-Precision FloatGTX 980GTX 970GTX 980 TiGTX 1070GTX 1660 TiRTX 2070RTX 2080GTX 1070 TiRTX 2080 SUPERGTX 1080TITAN RTXRTX 2060RTX 2060 SUPERRTX 2070 SUPERRTX 2080 Ti5010015020025036.4939.3642.0070.6371.3574.3279.2584.4684.4989.11103.61109.20111.74121.62222.09

PlaidML

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorGTX 1080 TiGTX 980 TiTITAN RTXRTX 2080 TiGTX 980GTX 1080GTX 970RTX 2080RTX 2060 SUPERRTX 2080 SUPERRTX 2070GTX 1070RTX 2060GTX 1070 TiGTX 1060RTX 2070 SUPERGTX 1660 TiGTX 166050100150200250Min: 109.8 / Avg: 203.83 / Max: 255.3Min: 57 / Avg: 191.08 / Max: 247.4Min: 52.7 / Avg: 173.29 / Max: 277.5Min: 52.4 / Avg: 173.16 / Max: 273Min: 53.5 / Avg: 157.67 / Max: 213.1Min: 49.1 / Avg: 151.63 / Max: 200.9Min: 52.1 / Avg: 148.78 / Max: 190.2Min: 51.5 / Avg: 146.49 / Max: 216.5Min: 55.8 / Avg: 142.16 / Max: 204.9Min: 48.8 / Avg: 141.86 / Max: 214.3Min: 51.5 / Avg: 138.71 / Max: 203.8Min: 48.3 / Avg: 135.38 / Max: 188.6Min: 49 / Avg: 134.34 / Max: 190.3Min: 53.5 / Avg: 128.35 / Max: 157.6Min: 45.7 / Avg: 125.77 / Max: 157.6Min: 49.1 / Avg: 124.58 / Max: 203.3Min: 48.2 / Avg: 115.16 / Max: 152Min: 45.8 / Avg: 106.92 / Max: 138.1

clpeak

OpenBenchmarking.orgGBPS Per Watt, More Is BetterclpeakOpenCL Test: Global Memory BandwidthGTX 970GTX 980GTX 1060GTX 1070 TiGTX 980 TiGTX 1660 TiGTX 1080GTX 1070GTX 1080 TiGTX 1660RTX 2070RTX 2080 SUPERRTX 2060 SUPERRTX 2080RTX 2070 SUPERTITAN RTXRTX 2080 Ti36912151.521.651.841.922.022.242.262.632.733.163.334.864.885.095.416.189.15

PlaidML

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorGTX 980 TiRTX 2080 TiGTX 980GTX 970GTX 1080RTX 2080RTX 2060 SUPERRTX 2070 SUPERGTX 1070RTX 2080 SUPERGTX 1070 TiRTX 2060GTX 1060GTX 1660 TiGTX 166050100150200250Min: 57.1 / Avg: 192.1 / Max: 249.1Min: 52.6 / Avg: 166.27 / Max: 275.3Min: 100 / Avg: 162.49 / Max: 218.7Min: 94.4 / Avg: 160.18 / Max: 203.4Min: 48.5 / Avg: 142.23 / Max: 208.8Min: 56.5 / Avg: 138.96 / Max: 215.1Min: 54.9 / Avg: 136.39 / Max: 187.2Min: 49.2 / Avg: 136.18 / Max: 192.6Min: 50.4 / Avg: 132.86 / Max: 187.3Min: 51.8 / Avg: 130.6 / Max: 207.8Min: 52.4 / Avg: 128.8 / Max: 152Min: 49.2 / Avg: 125.65 / Max: 186.5Min: 46.3 / Avg: 122.88 / Max: 159.6Min: 46.6 / Avg: 100.43 / Max: 150.5Min: 46.3 / Avg: 96.5 / Max: 135.8

SHOC Scalable HeterOgeneous Computing

The CUDA and OpenCL version of Vetter's Scalable HeterOgeneous Computing benchmark suite. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGHash/s, More Is BetterSHOC Scalable HeterOgeneous Computing 2015-11-10Target: OpenCL - Benchmark: MD5 HashGTX 970GTX 1060GTX 980GTX 980 TiGTX 1070GTX 1070 TiGTX 1660GTX 1660 TiGTX 1080RTX 2060RTX 2060 SUPERRTX 2070GTX 1080 TiRTX 2070 SUPERRTX 2080RTX 2080 SUPERRTX 2080 TiTITAN RTX816243240SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.02, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.02, N = 3SE +/- 0.03, N = 3SE +/- 0.02, N = 3SE +/- 0.03, N = 3SE +/- 0.04, N = 3SE +/- 0.05, N = 3SE +/- 0.01, N = 3SE +/- 0.02, N = 3SE +/- 0.12, N = 3SE +/- 0.06, N = 36.507.267.499.2210.6111.7011.8712.9814.2516.0418.2218.7719.7221.7824.0726.5634.9136.391. (CXX) g++ options: -O2 -lSHOCCommonMPI -lSHOCCommonOpenCL -lSHOCCommon -lOpenCL -lrt -pthread -lmpi_cxx -lmpi

Rodinia

OpenBenchmarking.orgWatts, Fewer Is BetterRodinia 2.4System Power Consumption MonitorGTX 980 TiGTX 980GTX 970RTX 2060GTX 1060GTX 1660 TiRTX 2070 SUPERGTX 1070 TiGTX 16604080120160200Min: 54.7 / Avg: 167.04 / Max: 233.5Min: 52.6 / Avg: 156.47 / Max: 203.2Min: 50.5 / Avg: 141.83 / Max: 190Min: 47.6 / Avg: 121.91 / Max: 156.6Min: 44.7 / Avg: 111.27 / Max: 154.1Min: 46 / Avg: 107.04 / Max: 129.7Min: 47 / Avg: 103.36 / Max: 166Min: 50.3 / Avg: 101.74 / Max: 149.4Min: 45.1 / Avg: 88.85 / Max: 116.6

clpeak

OpenBenchmarking.orgWatts, Fewer Is BetterclpeakSystem Power Consumption MonitorTITAN RTXRTX 2080 TiGTX 980 TiGTX 1080 TiRTX 2080RTX 2080 SUPERGTX 980RTX 2060 SUPERGTX 970RTX 2070 SUPERRTX 2070GTX 1080RTX 2060GTX 1070GTX 1070 TiGTX 1660 TiGTX 1060GTX 16604080120160200Min: 51.5 / Avg: 203.24 / Max: 225.1Min: 50.3 / Avg: 197 / Max: 217.1Min: 128.4 / Avg: 179.97 / Max: 191.4Min: 51.6 / Avg: 166.5 / Max: 193Min: 49.8 / Avg: 153.89 / Max: 172.5Min: 47.6 / Avg: 151.43 / Max: 166.9Min: 51.6 / Avg: 146.12 / Max: 159.1Min: 47.1 / Avg: 142.14 / Max: 150.8Min: 93.6 / Avg: 140.29 / Max: 146.2Min: 47 / Avg: 137.66 / Max: 150.3Min: 46.9 / Avg: 137.5 / Max: 151.9Min: 46.2 / Avg: 135.52 / Max: 152.6Min: 47.9 / Avg: 126.06 / Max: 143Min: 46 / Avg: 117.77 / Max: 137.1Min: 51 / Avg: 113.26 / Max: 124.1Min: 46.4 / Avg: 107.92 / Max: 119.4Min: 44.7 / Avg: 102.22 / Max: 117.3Min: 43.9 / Avg: 97.25 / Max: 106.6

SHOC Scalable HeterOgeneous Computing

The CUDA and OpenCL version of Vetter's Scalable HeterOgeneous Computing benchmark suite. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGFLOPS, More Is BetterSHOC Scalable HeterOgeneous Computing 2015-11-10Target: OpenCL - Benchmark: FFT SPGTX 1060GTX 970GTX 1660GTX 980GTX 1070GTX 1070 TiGTX 1080GTX 1660 TiGTX 980 TiRTX 2060RTX 2060 SUPERRTX 2070GTX 1080 TiRTX 2070 SUPERRTX 2080RTX 2080 SUPERRTX 2080 TiTITAN RTX30060090012001500SE +/- 3.50, N = 7SE +/- 0.48, N = 3SE +/- 0.27, N = 3SE +/- 1.09, N = 3SE +/- 6.42, N = 4SE +/- 0.19, N = 3SE +/- 3.58, N = 3SE +/- 1.57, N = 3SE +/- 3.01, N = 3SE +/- 0.56, N = 3SE +/- 3.09, N = 3SE +/- 2.90, N = 3SE +/- 1.06, N = 3SE +/- 0.27, N = 3SE +/- 0.39, N = 3SE +/- 0.78, N = 3SE +/- 2.79, N = 3SE +/- 1.38, N = 3326.68411.29452.89458.35478.54525.89614.69665.66725.98818.44971.24976.78982.231088.171100.001203.571485.731578.291. (CXX) g++ options: -O2 -lSHOCCommonMPI -lSHOCCommonOpenCL -lSHOCCommon -lOpenCL -lrt -pthread -lmpi_cxx -lmpi

PlaidML

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: ResNet 50 - Device: OpenCLGTX 970GTX 980 TiGTX 980GTX 1060GTX 1070GTX 1660 TiGTX 1660GTX 1070 TiRTX 2060GTX 1080RTX 2060 SUPERGTX 1080 TiRTX 2070 SUPERRTX 2070RTX 2080 SUPERRTX 2080RTX 2080 TiTITAN RTX1.13182.26363.39544.52725.6591.051.061.151.481.801.841.902.102.162.252.592.662.893.093.183.213.705.03

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: Mobilenet - Device: OpenCLGTX 970GTX 980GTX 980 TiGTX 1060GTX 1080GTX 1660GTX 1070GTX 1080 TiGTX 1660 TiGTX 1070 TiRTX 2060RTX 2060 SUPERRTX 2080RTX 2070RTX 2080 SUPERRTX 2070 SUPERRTX 2080 TiTITAN RTX6121824305.205.536.647.599.359.569.6510.2211.2011.3011.6712.9814.1614.8416.6019.7022.6323.23

SHOC Scalable HeterOgeneous Computing

OpenBenchmarking.orgGFLOPS Per Watt, More Is BetterSHOC Scalable HeterOgeneous Computing 2015-11-10Target: OpenCL - Benchmark: FFT SPGTX 1060GTX 970GTX 980GTX 1660GTX 1070GTX 1070 TiGTX 980 TiGTX 1080GTX 1080 TiRTX 2070RTX 2080 TiGTX 1660 TiRTX 2060RTX 2080RTX 2070 SUPERRTX 2060 SUPER481216204.005.125.455.706.236.366.927.877.978.6711.5412.2513.2315.4615.5817.59

LuxMark

LuxMark is a multi-platform OpenGL benchmark using LuxRender. LuxMark supports targeting different OpenCL devices and has multiple scenes available for rendering. LuxMark is a fully open-source OpenCL program with real-world rendering examples. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgScore, More Is BetterLuxMark 3.1OpenCL Device: GPU - Scene: MicrophoneGTX 1060GTX 970GTX 1080GTX 980GTX 1660GTX 1070GTX 1070 TiGTX 1660 TiGTX 980 TiGTX 1080 TiRTX 2060RTX 2070RTX 2060 SUPERRTX 2080RTX 2080 SUPERRTX 2070 SUPERRTX 2080 TiTITAN RTX7K14K21K28K35KSE +/- 1.53, N = 3SE +/- 2.00, N = 3SE +/- 1.20, N = 3SE +/- 18.25, N = 3SE +/- 1.33, N = 3SE +/- 4.91, N = 3SE +/- 15.50, N = 3SE +/- 2.33, N = 3SE +/- 49.74, N = 3SE +/- 19.33, N = 3SE +/- 3.84, N = 3SE +/- 26.44, N = 3SE +/- 43.34, N = 3SE +/- 11.68, N = 3SE +/- 108.17, N = 3SE +/- 16.84, N = 3SE +/- 21.50, N = 3SE +/- 168.12, N = 3708679858716891497949983102591100311096137211375418441185091991620164204992863130756

Darktable

Darktable is an open-source photography / workflow application this will use any system-installed Darktable program or on Windows will automatically download the pre-built binary from the project. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterDarktable 2.6.0Test: Server Room - Acceleration: OpenCLGTX 970GTX 980GTX 980 TiGTX 1060GTX 1660GTX 1070 TiGTX 1660 TiGTX 1070GTX 1080GTX 1080 TiRTX 2060RTX 2080RTX 2070 SUPERRTX 2080 SUPERRTX 2080 TiRTX 2070RTX 2060 SUPERTITAN RTX0.7111.4222.1332.8443.555SE +/- 0.01, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 4SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 8SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 33.163.101.511.281.181.171.151.111.091.050.830.800.800.790.750.750.750.74

PlaidML

This test profile uses PlaidML deep learning framework developed by Intel for offering up various benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: Inception V3 - Device: OpenCLGTX 970GTX 1060GTX 980GTX 980 TiGTX 1660GTX 1070GTX 1070 TiGTX 1660 TiGTX 1080RTX 2060RTX 2060 SUPERRTX 2070GTX 1080 TiRTX 2070 SUPERRTX 2080RTX 2080 SUPERRTX 2080 TiTITAN RTX80160240320400SE +/- 0.01, N = 3SE +/- 0.20, N = 3SE +/- 0.27, N = 3SE +/- 0.26, N = 3SE +/- 0.27, N = 3SE +/- 0.18, N = 3SE +/- 0.06, N = 3SE +/- 0.05, N = 3SE +/- 0.30, N = 3SE +/- 0.37, N = 3SE +/- 0.44, N = 3SE +/- 0.43, N = 3SE +/- 0.21, N = 3SE +/- 0.10, N = 3SE +/- 0.59, N = 3SE +/- 0.23, N = 3SE +/- 0.44, N = 3SE +/- 0.48, N = 388.1697.83101.92116.31137.66141.55147.04161.33173.79193.75219.76220.99228.68239.61268.33301.11363.16373.71

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: VGG19 - Device: OpenCLGTX 970GTX 980GTX 1060GTX 1660GTX 980 TiGTX 1660 TiGTX 1070RTX 2060GTX 1070 TiRTX 2060 SUPERRTX 2070GTX 1080RTX 2070 SUPERRTX 2080GTX 1080 TiRTX 2080 SUPERRTX 2080 TiTITAN RTX4080120160200SE +/- 0.18, N = 3SE +/- 0.62, N = 4SE +/- 0.12, N = 3SE +/- 0.08, N = 3SE +/- 0.77, N = 3SE +/- 0.12, N = 3SE +/- 0.19, N = 3SE +/- 0.19, N = 3SE +/- 0.03, N = 3SE +/- 0.23, N = 3SE +/- 0.35, N = 3SE +/- 0.28, N = 3SE +/- 0.16, N = 3SE +/- 0.44, N = 3SE +/- 0.44, N = 3SE +/- 0.21, N = 3SE +/- 0.36, N = 3SE +/- 0.48, N = 339.3443.6344.3752.5256.1358.0363.5671.0773.1280.8283.5683.8397.82105.54115.03115.44154.20162.05

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: VGG19 - Device: OpenCLGTX 970GTX 980GTX 1060GTX 1660GTX 980 TiGTX 1660 TiGTX 1070RTX 2060GTX 1070 TiGTX 1080RTX 2060 SUPERRTX 2070RTX 2070 SUPERRTX 2080GTX 1080 TiRTX 2080 SUPERRTX 2080 TiTITAN RTX4080120160200SE +/- 0.01, N = 3SE +/- 0.47, N = 3SE +/- 0.08, N = 3SE +/- 0.17, N = 3SE +/- 0.65, N = 3SE +/- 0.12, N = 3SE +/- 0.11, N = 3SE +/- 0.17, N = 3SE +/- 0.06, N = 3SE +/- 0.16, N = 3SE +/- 0.19, N = 3SE +/- 0.25, N = 3SE +/- 0.23, N = 3SE +/- 0.42, N = 3SE +/- 0.35, N = 3SE +/- 0.22, N = 3SE +/- 0.41, N = 3SE +/- 0.54, N = 347.7053.4954.7867.2468.4773.3576.8988.0490.34101.00101.17103.89122.32129.58138.68143.02186.19196.44

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: VGG16 - Device: OpenCLGTX 970GTX 980GTX 1060GTX 1660GTX 980 TiGTX 1660 TiGTX 1070RTX 2060GTX 1070 TiRTX 2060 SUPERRTX 2070GTX 1080RTX 2070 SUPERRTX 2080GTX 1080 TiRTX 2080 SUPERRTX 2080 TiTITAN RTX4080120160200SE +/- 0.21, N = 3SE +/- 0.83, N = 4SE +/- 0.18, N = 3SE +/- 0.17, N = 3SE +/- 1.12, N = 3SE +/- 0.14, N = 3SE +/- 0.30, N = 3SE +/- 0.23, N = 3SE +/- 0.08, N = 3SE +/- 0.35, N = 3SE +/- 0.39, N = 3SE +/- 0.40, N = 3SE +/- 0.28, N = 3SE +/- 0.57, N = 3SE +/- 0.62, N = 3SE +/- 0.29, N = 3SE +/- 0.51, N = 3SE +/- 0.57, N = 349.7655.7056.0766.2471.2673.1880.2789.5592.03102.58105.60106.09123.20133.20145.42145.65194.83204.67

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: VGG16 - Device: OpenCLGTX 970GTX 980GTX 1060GTX 1660GTX 980 TiGTX 1660 TiGTX 1070RTX 2060GTX 1070 TiGTX 1080RTX 2060 SUPERRTX 2070RTX 2070 SUPERRTX 2080GTX 1080 TiRTX 2080 SUPERRTX 2080 TiTITAN RTX50100150200250SE +/- 0.05, N = 3SE +/- 0.79, N = 3SE +/- 0.12, N = 3SE +/- 0.21, N = 3SE +/- 1.36, N = 3SE +/- 0.24, N = 3SE +/- 0.17, N = 3SE +/- 0.32, N = 3SE +/- 0.06, N = 3SE +/- 0.38, N = 3SE +/- 0.34, N = 3SE +/- 0.43, N = 3SE +/- 0.29, N = 3SE +/- 0.73, N = 3SE +/- 0.62, N = 3SE +/- 0.28, N = 3SE +/- 0.50, N = 3SE +/- 0.40, N = 360.3268.9569.3184.8387.3992.4597.32110.93114.03128.05128.22131.54154.64164.05175.37180.45234.65247.83

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: NASNer Large - Device: OpenCLGTX 970GTX 1060GTX 980GTX 1660GTX 980 TiGTX 1070GTX 1660 TiGTX 1070 TiGTX 1080RTX 2060RTX 2060 SUPERRTX 2070RTX 2070 SUPERGTX 1080 TiRTX 2080RTX 2080 SUPERRTX 2080 TiTITAN RTX20406080100SE +/- 0.03, N = 3SE +/- 0.03, N = 3SE +/- 0.15, N = 3SE +/- 0.03, N = 3SE +/- 0.10, N = 3SE +/- 0.05, N = 3SE +/- 0.03, N = 3SE +/- 0.02, N = 3SE +/- 0.08, N = 3SE +/- 0.08, N = 3SE +/- 0.14, N = 3SE +/- 0.13, N = 3SE +/- 0.05, N = 3SE +/- 0.11, N = 3SE +/- 0.15, N = 3SE +/- 0.08, N = 3SE +/- 0.21, N = 3SE +/- 0.25, N = 321.4223.1624.2428.9930.6433.0734.1235.4140.3841.1148.9649.9455.2456.6458.4764.8084.9787.17

cl-mem

A basic OpenCL memory benchmark. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGB/s, More Is Bettercl-mem 2017-01-13Benchmark: ReadGTX 970GTX 1060GTX 1660GTX 980GTX 1070GTX 1070 TiGTX 1080GTX 1660 TiGTX 980 TiRTX 2060GTX 1080 TiRTX 2060 SUPERRTX 2070 SUPERRTX 2070RTX 2080RTX 2080 SUPERRTX 2080 TiTITAN RTX120240360480600SE +/- 1.50, N = 8SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.10, N = 3SE +/- 0.03, N = 3SE +/- 0.07, N = 3SE +/- 0.12, N = 3SE +/- 0.07, N = 3SE +/- 0.12, N = 3SE +/- 0.20, N = 3SE +/- 0.20, N = 3SE +/- 0.22, N = 3SE +/- 0.22, N = 3SE +/- 0.25, N = 3SE +/- 0.25, N = 3SE +/- 0.27, N = 3SE +/- 0.38, N = 3SE +/- 0.40, N = 3142.10153.50162.90164.50205.27205.27228.80250.23265.33296.20337.53395.67395.67395.70395.70436.27544.33566.701. (CC) gcc options: -O2 -flto -lOpenCL

clpeak

Clpeak is designed to test the peak capabilities of OpenCL devices. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGFLOPS, More Is BetterclpeakOpenCL Test: Double-Precision DoubleGTX 970GTX 1060GTX 980GTX 1660GTX 1660 TiGTX 980 TiGTX 1070RTX 2060GTX 1070 TiRTX 2060 SUPERRTX 2070GTX 1080RTX 2070 SUPERRTX 2080RTX 2080 SUPERGTX 1080 TiRTX 2080 TiTITAN RTX120240360480600SE +/- 0.03, N = 3SE +/- 0.14, N = 3SE +/- 0.07, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.35, N = 3SE +/- 0.71, N = 3SE +/- 0.01, N = 3SE +/- 0.02, N = 3SE +/- 0.71, N = 3SE +/- 0.81, N = 3SE +/- 0.76, N = 3SE +/- 0.77, N = 3SE +/- 0.92, N = 3SE +/- 0.03, N = 3SE +/- 1.14, N = 3SE +/- 1.46, N = 3SE +/- 1.16, N = 3137.47149.58159.68168.44185.12196.60223.91231.44242.63263.11268.32297.94310.27345.81378.98414.96521.90547.971. (CXX) g++ options: -O3 -rdynamic -lOpenCL

PlaidML

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: IMDB LSTM - Device: OpenCLGTX 970GTX 980 TiGTX 980GTX 1060GTX 1070GTX 1070 TiGTX 1080GTX 1660GTX 1080 TiRTX 2060GTX 1660 TiRTX 2060 SUPERRTX 2070 SUPERRTX 2070RTX 2080RTX 2080 SUPERRTX 2080 TiTITAN RTX1.14532.29063.43594.58125.72651.281.411.431.832.372.592.812.983.003.103.143.233.673.683.954.524.565.09

SHOC Scalable HeterOgeneous Computing

The CUDA and OpenCL version of Vetter's Scalable HeterOgeneous Computing benchmark suite. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGFLOPS, More Is BetterSHOC Scalable HeterOgeneous Computing 2015-11-10Target: OpenCL - Benchmark: Max SP FlopsGTX 970GTX 1060GTX 980GTX 1660GTX 1660 TiGTX 980 TiGTX 1070RTX 2060GTX 1070 TiRTX 2060 SUPERRTX 2070GTX 1080RTX 2070 SUPERRTX 2080RTX 2080 SUPERGTX 1080 TiRTX 2080 TiTITAN RTX4K8K12K16K20KSE +/- 0.74, N = 3SE +/- 6.34, N = 3SE +/- 3.92, N = 3SE +/- 13.79, N = 3SE +/- 0.04, N = 3SE +/- 11.70, N = 3SE +/- 1.89, N = 3SE +/- 19.13, N = 3SE +/- 0.84, N = 3SE +/- 27.40, N = 3SE +/- 45.97, N = 3SE +/- 3.00, N = 3SE +/- 51.02, N = 3SE +/- 29.32, N = 3SE +/- 61.30, N = 3SE +/- 3.93, N = 3SE +/- 87.95, N = 3SE +/- 91.95, N = 34362.314788.925052.735329.845893.416213.977115.397320.737715.428378.878528.709407.759869.3410952.7712015.5013230.7716656.2017334.001. (CXX) g++ options: -O2 -lSHOCCommonMPI -lSHOCCommonOpenCL -lSHOCCommon -lOpenCL -lrt -pthread -lmpi_cxx -lmpi

LuxMark

LuxMark is a multi-platform OpenGL benchmark using LuxRender. LuxMark supports targeting different OpenCL devices and has multiple scenes available for rendering. LuxMark is a fully open-source OpenCL program with real-world rendering examples. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgScore, More Is BetterLuxMark 3.1OpenCL Device: GPU - Scene: Luxball HDRGTX 970GTX 1060GTX 980GTX 1080GTX 1660GTX 1660 TiGTX 980 TiGTX 1070 TiGTX 1070RTX 2060GTX 1080 TiRTX 2080RTX 2070 SUPERRTX 2060 SUPERRTX 2070RTX 2080 SUPERRTX 2080 TiTITAN RTX10K20K30K40K50KSE +/- 6.23, N = 3SE +/- 4.00, N = 3SE +/- 26.16, N = 3SE +/- 17.98, N = 3SE +/- 35.04, N = 3SE +/- 19.86, N = 3SE +/- 39.15, N = 3SE +/- 36.50, N = 3SE +/- 1.00, N = 3SE +/- 0.67, N = 3SE +/- 7.67, N = 3SE +/- 7.51, N = 3SE +/- 98.93, N = 3SE +/- 4.93, N = 3SE +/- 7.54, N = 3SE +/- 0.88, N = 3SE +/- 166.33, N = 3SE +/- 20.92, N = 3117321224513246137881516216147168711692517290216832168929164297343009330097301794297446546

PlaidML

This test profile uses PlaidML deep learning framework developed by Intel for offering up various benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: IMDB LSTM - Device: OpenCLGTX 970GTX 1060GTX 980GTX 980 TiGTX 1660GTX 1070GTX 1660 TiGTX 1070 TiRTX 2060GTX 1080RTX 2060 SUPERRTX 2070RTX 2070 SUPERGTX 1080 TiRTX 2080RTX 2080 SUPERRTX 2080 TiTITAN RTX2004006008001000SE +/- 0.03, N = 3SE +/- 0.17, N = 3SE +/- 0.50, N = 3SE +/- 0.56, N = 3SE +/- 0.01, N = 3SE +/- 0.13, N = 3SE +/- 0.15, N = 3SE +/- 0.49, N = 3SE +/- 0.37, N = 3SE +/- 0.31, N = 3SE +/- 0.31, N = 3SE +/- 0.21, N = 3SE +/- 0.67, N = 3SE +/- 0.74, N = 3SE +/- 1.63, N = 3SE +/- 1.47, N = 3SE +/- 1.01, N = 3SE +/- 2.25, N = 3204.32224.89231.66270.00287.68315.37315.83333.03389.40399.00440.79446.23499.69523.98548.83589.86758.21790.77

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: VGG16 - Device: OpenCLGTX 970GTX 980GTX 980 TiGTX 1060GTX 1660GTX 1660 TiGTX 1070RTX 2060RTX 2060 SUPERGTX 1080GTX 1070 TiRTX 2070GTX 1080 TiRTX 2070 SUPERRTX 2080RTX 2080 SUPERTITAN RTXRTX 2080 Ti0.2340.4680.7020.9361.170.270.280.290.370.480.480.490.550.550.560.570.610.620.660.770.800.941.04

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: Mobilenet - Device: OpenCLGTX 970GTX 980GTX 980 TiGTX 1060GTX 1070GTX 1080GTX 1070 TiGTX 1660GTX 1080 TiGTX 1660 TiRTX 2060RTX 2060 SUPERRTX 2070TITAN RTXRTX 2070 SUPERRTX 2080 SUPERRTX 2080RTX 2080 Ti6121824306.987.177.679.5712.3514.0214.1614.7915.2116.0618.2020.6821.3522.1924.7525.0626.2126.71

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: Inception V3 - Device: OpenCLGTX 970GTX 980GTX 980 TiGTX 1060GTX 1080GTX 1660GTX 1070GTX 1660 TiGTX 1070 TiRTX 2060RTX 2070RTX 2060 SUPERGTX 1080 TiRTX 2070 SUPERRTX 2080RTX 2080 SUPERRTX 2080 TiTITAN RTX0.43880.87761.31641.75522.1940.520.560.610.700.940.950.991.021.081.111.181.231.341.341.361.521.661.95

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: ResNet 50 - Device: OpenCLGTX 970GTX 1060GTX 980GTX 1660GTX 980 TiGTX 1660 TiGTX 1070GTX 1070 TiRTX 2060GTX 1080RTX 2060 SUPERRTX 2070RTX 2070 SUPERRTX 2080RTX 2080 SUPERGTX 1080 TiRTX 2080 TiTITAN RTX90180270360450SE +/- 0.00, N = 3SE +/- 0.16, N = 3SE +/- 0.26, N = 3SE +/- 0.31, N = 3SE +/- 0.06, N = 3SE +/- 0.06, N = 3SE +/- 0.28, N = 3SE +/- 0.08, N = 3SE +/- 0.16, N = 3SE +/- 0.11, N = 3SE +/- 0.48, N = 3SE +/- 0.53, N = 3SE +/- 0.71, N = 3SE +/- 0.60, N = 3SE +/- 0.12, N = 3SE +/- 0.42, N = 3SE +/- 1.04, N = 3SE +/- 0.70, N = 3116.05130.64142.14156.50162.63172.68196.01205.85220.44240.62250.98251.07283.98305.76327.80333.54424.07433.81

cl-mem

A basic OpenCL memory benchmark. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGB/s, More Is Bettercl-mem 2017-01-13Benchmark: WriteGTX 970GTX 1060GTX 1660GTX 980GTX 1070 TiGTX 1070GTX 1660 TiGTX 1080RTX 2060GTX 980 TiRTX 2070 SUPERRTX 2070RTX 2080RTX 2060 SUPERGTX 1080 TiRTX 2080 SUPERRTX 2080 TiTITAN RTX110220330440550SE +/- 0.00, N = 3SE +/- 0.03, N = 3SE +/- 0.03, N = 3SE +/- 0.00, N = 3SE +/- 0.03, N = 3SE +/- 0.00, N = 3SE +/- 0.12, N = 3SE +/- 0.03, N = 3SE +/- 0.40, N = 3SE +/- 0.06, N = 3SE +/- 0.43, N = 3SE +/- 1.00, N = 3SE +/- 0.15, N = 3SE +/- 0.82, N = 3SE +/- 0.28, N = 3SE +/- 0.54, N = 3SE +/- 0.35, N = 3SE +/- 1.39, N = 3132.60144.57148.87151.50190.03190.90208.67214.67241.20241.50319.57322.67331.50333.20340.27345.77441.23495.371. (CC) gcc options: -O2 -flto -lOpenCL

Rodinia

OpenBenchmarking.orgWatts, Fewer Is BetterRodinia 2.4System Power Consumption MonitorTITAN RTXGTX 980 TiRTX 2080 TiGTX 1080 TiRTX 2080RTX 2080 SUPERRTX 2070RTX 2060 SUPERGTX 980GTX 970RTX 2070 SUPERGTX 1080RTX 2060GTX 1070GTX 1070 TiGTX 1660 TiGTX 1060GTX 1660306090120150Min: 51.9 / Avg: 158.82 / Max: 169.5Min: 110.1 / Avg: 153.24 / Max: 157.4Min: 51.1 / Avg: 152.87 / Max: 162.6Min: 53.3 / Avg: 137.65 / Max: 146.3Min: 49.5 / Avg: 131.08 / Max: 142Min: 46.6 / Avg: 123.16 / Max: 135.3Min: 48.1 / Avg: 122.39 / Max: 128.3Min: 46.3 / Avg: 122.27 / Max: 129.5Min: 88.8 / Avg: 119.77 / Max: 124.7Min: 85.4 / Avg: 117.57 / Max: 120.9Min: 46.4 / Avg: 116.19 / Max: 128.7Min: 47.4 / Avg: 113.6 / Max: 118.7Min: 46.6 / Avg: 112.18 / Max: 123.5Min: 70.9 / Avg: 107.97 / Max: 112.9Min: 49.1 / Avg: 105.1 / Max: 108.7Min: 45.9 / Avg: 98.53 / Max: 104.6Min: 62.8 / Avg: 97.17 / Max: 100.8Min: 45.5 / Avg: 90.35 / Max: 95.7

LuxMark

LuxMark is a multi-platform OpenGL benchmark using LuxRender. LuxMark supports targeting different OpenCL devices and has multiple scenes available for rendering. LuxMark is a fully open-source OpenCL program with real-world rendering examples. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgScore, More Is BetterLuxMark 3.1OpenCL Device: GPU - Scene: HotelGTX 1060GTX 970GTX 980GTX 1660GTX 1660 TiGTX 1080GTX 1070GTX 980 TiGTX 1070 TiRTX 2060GTX 1080 TiRTX 2060 SUPERRTX 2070RTX 2070 SUPERRTX 2080RTX 2080 SUPERRTX 2080 TiTITAN RTX2K4K6K8K10KSE +/- 3.76, N = 3SE +/- 1.86, N = 3SE +/- 2.73, N = 3SE +/- 0.58, N = 3SE +/- 0.67, N = 3SE +/- 1.20, N = 3SE +/- 8.00, N = 3SE +/- 3.51, N = 3SE +/- 0.67, N = 3SE +/- 7.09, N = 3SE +/- 0.67, N = 3SE +/- 1.86, N = 3SE +/- 0.88, N = 3SE +/- 0.58, N = 3SE +/- 4.37, N = 3SE +/- 1.73, N = 3264827303048373338053807387038854170483356496148615065656590683992159836

clpeak

Clpeak is designed to test the peak capabilities of OpenCL devices. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGBPS, More Is BetterclpeakOpenCL Test: Global Memory BandwidthGTX 970GTX 1060GTX 1660GTX 980GTX 1070GTX 1070 TiGTX 1080GTX 1660 TiGTX 980 TiRTX 2060GTX 1080 TiRTX 2060 SUPERRTX 2080RTX 2070RTX 2070 SUPERRTX 2080 SUPERRTX 2080 TiTITAN RTX110220330440550SE +/- 0.06, N = 3SE +/- 0.06, N = 3SE +/- 0.00, N = 3SE +/- 0.03, N = 3SE +/- 0.18, N = 3SE +/- 0.00, N = 3SE +/- 0.09, N = 3SE +/- 0.17, N = 3SE +/- 0.52, N = 3SE +/- 0.24, N = 3SE +/- 0.71, N = 3SE +/- 0.11, N = 3SE +/- 0.22, N = 3SE +/- 0.07, N = 3SE +/- 0.33, N = 3SE +/- 0.08, N = 3SE +/- 0.44, N = 3SE +/- 0.66, N = 3143.48146.62157.60164.25196.47197.26222.09234.67263.22275.86328.90367.92368.47368.96369.11405.00506.33528.891. (CXX) g++ options: -O3 -rdynamic -lOpenCL

PlaidML

This test profile uses PlaidML deep learning framework developed by Intel for offering up various benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: Mobilenet - Device: OpenCLGTX 970GTX 1060GTX 980GTX 1660GTX 1070GTX 980 TiGTX 1660 TiGTX 1070 TiGTX 1080RTX 2060RTX 2070RTX 2060 SUPERRTX 2070 SUPERRTX 2080GTX 1080 TiRTX 2080 SUPERRTX 2080 TiTITAN RTX5001000150020002500SE +/- 0.75, N = 3SE +/- 0.63, N = 3SE +/- 0.24, N = 3SE +/- 1.38, N = 3SE +/- 1.57, N = 3SE +/- 0.07, N = 3SE +/- 0.86, N = 3SE +/- 0.73, N = 3SE +/- 1.27, N = 3SE +/- 2.11, N = 3SE +/- 1.46, N = 3SE +/- 1.59, N = 3SE +/- 1.25, N = 3SE +/- 4.17, N = 3SE +/- 5.20, N = 3SE +/- 2.80, N = 3SE +/- 6.28, N = 3SE +/- 13.68, N = 3671.49726.30759.43814.65987.69990.121002.001009.261123.851232.471516.961531.011649.171663.871672.731762.002335.462466.66

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: Inception V3 - Device: OpenCLGTX 970GTX 1060GTX 980GTX 1660GTX 980 TiGTX 1660 TiGTX 1070GTX 1070 TiRTX 2060GTX 1080RTX 2070RTX 2060 SUPERRTX 2070 SUPERRTX 2080GTX 1080 TiRTX 2080 SUPERRTX 2080 TiTITAN RTX80160240320400SE +/- 0.16, N = 3SE +/- 0.10, N = 3SE +/- 0.17, N = 3SE +/- 0.12, N = 3SE +/- 0.07, N = 3SE +/- 0.23, N = 3SE +/- 0.09, N = 3SE +/- 0.06, N = 3SE +/- 0.23, N = 3SE +/- 0.38, N = 3SE +/- 0.29, N = 3SE +/- 0.25, N = 3SE +/- 0.07, N = 3SE +/- 0.57, N = 3SE +/- 0.14, N = 3SE +/- 0.10, N = 3SE +/- 0.38, N = 3SE +/- 0.42, N = 394.72104.44105.64116.90135.14140.05147.17153.34167.87184.80198.03199.43215.85238.73257.55259.26343.49347.93

cl-mem

OpenBenchmarking.orgGB/s Per Watt, More Is Bettercl-mem 2017-01-13Benchmark: ReadGTX 970GTX 980GTX 1060GTX 1070GTX 1660GTX 980 TiGTX 1070 TiGTX 1080GTX 1080 TiGTX 1660 TiRTX 2060RTX 2060 SUPERRTX 2080RTX 2070TITAN RTXRTX 2080 TiRTX 2070 SUPERRTX 2080 SUPER0.86631.73262.59893.46524.33151.051.191.341.681.691.761.861.902.102.672.763.093.263.283.373.383.473.85

clpeak

Clpeak is designed to test the peak capabilities of OpenCL devices. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGFLOPS, More Is BetterclpeakOpenCL Test: Single-Precision FloatGTX 970GTX 1060GTX 980GTX 1660GTX 1660 TiRTX 2060GTX 980 TiGTX 1070GTX 1070 TiRTX 2060 SUPERRTX 2070GTX 1080RTX 2070 SUPERRTX 2080RTX 2080 SUPERGTX 1080 TiRTX 2080 TiTITAN RTX3K6K9K12K15KSE +/- 40.24, N = 15SE +/- 1.88, N = 3SE +/- 46.38, N = 8SE +/- 7.83, N = 3SE +/- 61.47, N = 15SE +/- 77.72, N = 3SE +/- 44.36, N = 15SE +/- 3.03, N = 3SE +/- 7.63, N = 3SE +/- 84.87, N = 15SE +/- 81.15, N = 15SE +/- 3.14, N = 3SE +/- 76.18, N = 15SE +/- 7.41, N = 3SE +/- 124.22, N = 3SE +/- 5.50, N = 3SE +/- 207.30, N = 3SE +/- 228.75, N = 153888.164199.714476.694610.014793.665329.075538.756269.496770.977089.507198.648314.298502.718883.9010335.5011720.5713532.7414203.871. (CXX) g++ options: -O3 -rdynamic -lOpenCL

PlaidML

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: VGG19 - Device: OpenCLGTX 970GTX 980GTX 980 TiGTX 1060GTX 1070GTX 1660GTX 1660 TiRTX 2060 SUPERRTX 2060GTX 1080RTX 2070GTX 1070 TiGTX 1080 TiRTX 2070 SUPERRTX 2080RTX 2080 SUPERTITAN RTXRTX 2080 Ti0.16430.32860.49290.65720.82150.200.220.230.280.370.380.380.390.400.430.440.460.490.490.580.590.710.73

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: Inception V3 - Device: OpenCLGTX 970GTX 980 TiGTX 980GTX 1060GTX 1070GTX 1080GTX 1070 TiGTX 1080 TiGTX 1660GTX 1660 TiRTX 2060RTX 2060 SUPERRTX 2070RTX 2070 SUPERRTX 2080RTX 2080 SUPERRTX 2080 TiTITAN RTX0.4590.9181.3771.8362.2950.560.600.610.780.951.101.121.131.221.321.341.491.571.721.751.992.042.04

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: ResNet 50 - Device: OpenCLGTX 970GTX 980GTX 980 TiGTX 1060GTX 1070GTX 1660GTX 1660 TiGTX 1080RTX 2060GTX 1070 TiRTX 2070RTX 2060 SUPERGTX 1080 TiRTX 2070 SUPERRTX 2080RTX 2080 SUPERRTX 2080 TiTITAN RTX0.5761.1521.7282.3042.880.710.780.791.011.241.421.471.511.551.571.691.741.762.102.192.222.532.56

cl-mem

OpenBenchmarking.orgGB/s Per Watt, More Is Bettercl-mem 2017-01-13Benchmark: WriteGTX 980GTX 970GTX 1060GTX 980 TiGTX 1070GTX 1660GTX 1080GTX 1070 TiGTX 1080 TiRTX 2060GTX 1660 TiRTX 2070 SUPERRTX 2060 SUPERRTX 2080RTX 2080 SUPERTITAN RTXRTX 2080 TiRTX 20700.83481.66962.50443.33924.1741.031.071.441.481.541.611.641.762.022.242.332.602.612.742.853.133.463.71

PlaidML

This test profile uses PlaidML deep learning framework developed by Intel for offering up various benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: ResNet 50 - Device: OpenCLGTX 970GTX 1060GTX 980GTX 1660GTX 980 TiGTX 1660 TiGTX 1070GTX 1070 TiRTX 2060GTX 1080RTX 2060 SUPERRTX 2070RTX 2070 SUPERRTX 2080RTX 2080 SUPERGTX 1080 TiRTX 2080 TiTITAN RTX140280420560700SE +/- 0.06, N = 3SE +/- 0.07, N = 3SE +/- 0.02, N = 3SE +/- 0.16, N = 3SE +/- 0.58, N = 3SE +/- 0.47, N = 3SE +/- 0.15, N = 3SE +/- 0.09, N = 3SE +/- 0.39, N = 3SE +/- 0.32, N = 3SE +/- 0.53, N = 3SE +/- 0.27, N = 3SE +/- 0.19, N = 3SE +/- 0.25, N = 3SE +/- 0.61, N = 3SE +/- 0.72, N = 3SE +/- 0.63, N = 3SE +/- 0.75, N = 3181.87196.00203.91228.14247.47259.43276.89294.36319.25337.47374.71376.73421.58441.24468.70496.24634.09648.36

OctaneBench

OctaneBench is a test of the OctaneRender on the GPU and requires the use of NVIDIA CUDA. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgScore, More Is BetterOctaneBench 4.00cTotal ScoreGTX 1060GTX 970GTX 980GTX 1660GTX 1660 TiGTX 1070GTX 1070 TiGTX 980 TiGTX 1080RTX 2060RTX 2060 SUPERRTX 2070GTX 1080 TiRTX 2070 SUPERRTX 2080RTX 2080 SUPERRTX 2080 TiTITAN RTX7014021028035091.4495.60109.70118.49132.28132.86141.35142.20147.98164.52205.23206.88212.04220.76222.88233.56309.04322.76

PlaidML

This test profile uses PlaidML deep learning framework developed by Intel for offering up various benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: Mobilenet - Device: OpenCLGTX 970GTX 1060GTX 980GTX 1660GTX 980 TiGTX 1070GTX 1070 TiGTX 1660 TiGTX 1080RTX 2060RTX 2070RTX 2060 SUPERGTX 1080 TiRTX 2070 SUPERRTX 2080RTX 2080 SUPERRTX 2080 TiTITAN RTX6001200180024003000SE +/- 1.43, N = 3SE +/- 2.37, N = 3SE +/- 2.37, N = 3SE +/- 1.34, N = 3SE +/- 1.24, N = 3SE +/- 4.57, N = 3SE +/- 0.80, N = 3SE +/- 2.77, N = 3SE +/- 4.27, N = 3SE +/- 3.62, N = 3SE +/- 5.21, N = 3SE +/- 10.89, N = 3SE +/- 7.35, N = 3SE +/- 4.73, N = 3SE +/- 4.68, N = 3SE +/- 6.75, N = 3SE +/- 13.82, N = 3SE +/- 4.02, N = 3841.48908.43973.391160.521202.771288.941371.211394.051544.501694.071969.501983.822162.582264.972292.382437.482750.572842.38

cl-mem

OpenBenchmarking.orgGB/s Per Watt, More Is Bettercl-mem 2017-01-13Benchmark: CopyGTX 970GTX 980GTX 1060GTX 1070GTX 980 TiGTX 1070 TiGTX 1660GTX 1080 TiGTX 1080GTX 1660 TiTITAN RTXRTX 2080RTX 2060 SUPERRTX 2070RTX 2060RTX 2070 SUPERRTX 2080 SUPERRTX 2080 Ti0.72681.45362.18042.90723.6340.961.041.251.351.451.531.581.621.651.962.172.282.432.442.662.822.833.23

PlaidML

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: NASNer Large - Device: OpenCLGTX 970GTX 980GTX 980 TiGTX 1060GTX 1070GTX 1080GTX 1660GTX 1660 TiGTX 1070 TiRTX 2060GTX 1080 TiRTX 2060 SUPERRTX 2070RTX 2080RTX 2070 SUPERRTX 2080 SUPERRTX 2080 TiTITAN RTX0.08330.16660.24990.33320.41650.110.120.130.150.180.200.210.220.230.230.240.250.260.290.300.320.370.37

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: VGG16 - Device: OpenCLGTX 970GTX 980GTX 980 TiGTX 1060GTX 1070GTX 1660 TiGTX 1660GTX 1080RTX 2060GTX 1070 TiRTX 2070RTX 2060 SUPERGTX 1080 TiRTX 2070 SUPERRTX 2080RTX 2080 SUPERRTX 2080 TiTITAN RTX0.23180.46360.69540.92721.1590.310.320.320.420.560.560.580.610.620.670.680.710.750.810.820.820.981.03

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: DenseNet 201 - Device: OpenCLGTX 970GTX 1060GTX 980GTX 1660GTX 980 TiGTX 1660 TiGTX 1070GTX 1070 TiGTX 1080RTX 2060RTX 2070RTX 2060 SUPERRTX 2080RTX 2070 SUPERGTX 1080 TiRTX 2080 SUPERRTX 2080 TiTITAN RTX60120180240300SE +/- 0.01, N = 3SE +/- 0.15, N = 3SE +/- 0.12, N = 3SE +/- 0.10, N = 3SE +/- 0.18, N = 3SE +/- 0.03, N = 3SE +/- 0.05, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.05, N = 3SE +/- 0.22, N = 3SE +/- 0.03, N = 3SE +/- 0.17, N = 3SE +/- 0.14, N = 3SE +/- 0.03, N = 3SE +/- 0.07, N = 3SE +/- 0.10, N = 3SE +/- 0.18, N = 379.7191.0792.92102.83111.46114.58127.02130.15143.53154.19176.49179.51189.28190.01191.31200.38254.45263.13

FAHBench

FAHBench is a Folding@Home benchmark on the GPU. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgNs Per Day, More Is BetterFAHBench 2.3.2GTX 970GTX 1060GTX 980GTX 980 TiGTX 1660GTX 1070 TiGTX 1660 TiGTX 1070GTX 1080RTX 2060GTX 1080 TiRTX 2070RTX 2060 SUPERRTX 2070 SUPERRTX 2080RTX 2080 SUPERRTX 2080 TiTITAN RTX70140210280350SE +/- 0.03, N = 3SE +/- 0.17, N = 3SE +/- 0.08, N = 3SE +/- 0.04, N = 3SE +/- 0.27, N = 3SE +/- 0.05, N = 3SE +/- 0.15, N = 3SE +/- 0.43, N = 3SE +/- 0.53, N = 3SE +/- 0.61, N = 3SE +/- 0.43, N = 3SE +/- 0.64, N = 3SE +/- 0.34, N = 3SE +/- 0.60, N = 3SE +/- 0.99, N = 3SE +/- 0.78, N = 3SE +/- 0.90, N = 3SE +/- 0.71, N = 391.53102.61102.86116.02126.64138.21139.81140.29155.22183.41198.25204.71205.20229.12242.75256.83301.89301.93

PlaidML

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: VGG19 - Device: OpenCLGTX 970GTX 980 TiGTX 980GTX 1060GTX 1660GTX 1070GTX 1660 TiRTX 2060GTX 1080GTX 1070 TiRTX 2060 SUPERRTX 2070GTX 1080 TiRTX 2080RTX 2070 SUPERRTX 2080 SUPERRTX 2080 TiTITAN RTX0.16880.33760.50640.67520.8440.240.250.260.320.420.430.440.460.480.500.520.530.560.560.610.640.740.75

Rodinia

Rodinia is a suite focused upon accelerating compute-intensive applications with accelerators. CUDA, OpenMP, and OpenCL parallel models are supported by the included applications. This profile utilizes the OpenCL and OpenMP test binaries at the moment. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterRodinia 2.4Test: OpenCL Particle FilterGTX 970GTX 1060GTX 1660GTX 980GTX 1660 TiGTX 980 TiRTX 2060GTX 1070GTX 1070 TiRTX 2060 SUPERRTX 2070RTX 2070 SUPERGTX 1080RTX 2080RTX 2080 SUPERGTX 1080 TiRTX 2080 TiTITAN RTX3691215SE +/- 0.02, N = 3SE +/- 0.02, N = 3SE +/- 0.01, N = 3SE +/- 0.07, N = 3SE +/- 0.02, N = 3SE +/- 0.04, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 3SE +/- 0.07, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.07, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.02, N = 3SE +/- 0.02, N = 3SE +/- 0.01, N = 312.9911.9311.8711.6910.829.958.908.267.887.877.756.826.496.225.744.964.394.241. (CXX) g++ options: -O2 -lOpenCL

PlaidML

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: DenseNet 201 - Device: OpenCLGTX 970GTX 980 TiGTX 980GTX 1060GTX 1070GTX 1080 TiGTX 1080GTX 1660GTX 1660 TiGTX 1070 TiRTX 2060RTX 2060 SUPERRTX 2070RTX 2080RTX 2080 SUPERRTX 2080 TiTITAN RTXRTX 2070 SUPER0.34430.68861.03291.37721.72150.540.580.590.720.940.940.950.960.991.011.151.261.271.291.411.471.521.53

clpeak

OpenBenchmarking.orgGFLOPS Per Watt, More Is BetterclpeakOpenCL Test: Double-Precision DoubleGTX 970GTX 980GTX 980 TiGTX 1060GTX 1660 TiGTX 1660RTX 2060RTX 2060 SUPERGTX 1070RTX 2070GTX 1070 TiGTX 1080RTX 2070 SUPERRTX 2080GTX 1080 TiRTX 2080 SUPERRTX 2080 TiTITAN RTX0.60751.2151.82252.433.03750.981.091.091.461.721.731.841.851.901.952.142.202.252.252.492.502.652.70

Darktable

Darktable is an open-source photography / workflow application this will use any system-installed Darktable program or on Windows will automatically download the pre-built binary from the project. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterDarktable 2.6.0Test: Boat - Acceleration: OpenCLGTX 970GTX 980GTX 1060GTX 1660GTX 980 TiGTX 1070 TiGTX 1660 TiGTX 1070GTX 1080GTX 1080 TiRTX 2060RTX 2060 SUPERRTX 2070 SUPERRTX 2070RTX 2080RTX 2080 SUPERTITAN RTXRTX 2080 Ti0.99451.9892.98353.9784.9725SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.02, N = 3SE +/- 0.00, N = 34.423.923.653.353.272.932.922.892.722.292.221.951.931.931.901.821.641.64

SHOC Scalable HeterOgeneous Computing

OpenBenchmarking.orgGFLOPS Per Watt, More Is BetterSHOC Scalable HeterOgeneous Computing 2015-11-10Target: OpenCL - Benchmark: Max SP FlopsGTX 970GTX 980GTX 980 TiGTX 1060GTX 1660 TiGTX 1660GTX 1070RTX 2060RTX 2060 SUPERRTX 2070GTX 1080GTX 1070 TiRTX 2080RTX 2070 SUPERGTX 1080 TiRTX 2080 SUPERRTX 2080 TiTITAN RTX2040608010029.2931.4032.0540.0649.6350.1750.3050.3656.3857.1359.8761.4363.9365.7666.2673.2376.6977.72

JuliaGPU

OpenBenchmarking.orgSamples/sec Per Watt, More Is BetterJuliaGPU 1.2pts1OpenCL Device: GPUGTX 980 TiGTX 970GTX 980GTX 1060GTX 1080 TiGTX 1070GTX 1080RTX 2080 TiTITAN RTXGTX 1070 TiRTX 2070RTX 2080 SUPERRTX 2060RTX 2070 SUPERRTX 2060 SUPERRTX 2080GTX 1660GTX 1660 Ti600K1200K1800K2400K3000K1099178.251275493.931325997.881658141.691682592.711809790.271906369.991910018.661923116.672260229.902271141.792379445.262469451.172632329.692670026.702691799.292790569.692880366.36

cl-mem

A basic OpenCL memory benchmark. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGB/s, More Is Bettercl-mem 2017-01-13Benchmark: CopyGTX 970GTX 1060GTX 980GTX 1660GTX 1070GTX 1070 TiGTX 1080GTX 1660 TiGTX 980 TiRTX 2060GTX 1080 TiRTX 2070RTX 2060 SUPERRTX 2080RTX 2070 SUPERRTX 2080 SUPERTITAN RTXRTX 2080 Ti70140210280350SE +/- 0.03, N = 3SE +/- 0.06, N = 3SE +/- 0.00, N = 3SE +/- 0.03, N = 3SE +/- 0.06, N = 3SE +/- 0.00, N = 3SE +/- 0.03, N = 3SE +/- 0.15, N = 3SE +/- 0.17, N = 3SE +/- 0.12, N = 3SE +/- 0.25, N = 3SE +/- 0.24, N = 3SE +/- 0.31, N = 3SE +/- 0.15, N = 3SE +/- 0.17, N = 3SE +/- 0.13, N = 3SE +/- 0.67, N = 3SE +/- 0.40, N = 3124.77137.20143.40145.37182.00182.70205.93208.50216.83237.77283.20284.43287.80289.20291.87301.23322.20324.401. (CC) gcc options: -O2 -flto -lOpenCL

ViennaCL

OpenBenchmarking.orgGFLOPS Per Watt, More Is BetterViennaCL 1.4.2OpenCL LU FactorizationGTX 1080 TiGTX 980 TiGTX 970GTX 1080GTX 1070 TiRTX 2080RTX 2060GTX 980GTX 1070RTX 2070 SUPERGTX 1060GTX 1660GTX 1660 TiRTX 2080 SUPERRTX 2080 TiRTX 2070TITAN RTXRTX 2060 SUPER0.3150.630.9451.261.5750.590.600.660.700.710.710.730.790.800.901.001.081.101.181.311.351.351.40

FAHBench

OpenBenchmarking.orgNs Per Day Per Watt, More Is BetterFAHBench 2.3.2GTX 970GTX 980 TiGTX 980GTX 1060GTX 1070GTX 1080GTX 1080 TiGTX 1070 TiGTX 1660 TiGTX 1660RTX 2060RTX 2060 SUPERRTX 2070TITAN RTXRTX 2080RTX 2080 TiRTX 2070 SUPERRTX 2080 SUPER0.32630.65260.97891.30521.63150.620.620.650.830.961.001.021.101.101.111.211.271.291.331.381.381.421.45

LuxMark

OpenBenchmarking.orgScore Per Watt, More Is BetterLuxMark 3.1OpenCL Device: GPU - Scene: Luxball HDRGTX 970GTX 980GTX 980 TiGTX 1080GTX 1060GTX 1080 TiGTX 1070GTX 1660 TiGTX 1660GTX 1070 TiRTX 2060RTX 2080RTX 2070RTX 2080 SUPERRTX 2060 SUPERRTX 2080 TiRTX 2070 SUPERTITAN RTX30609012015065.0767.8770.6476.5583.3488.2695.03102.75108.70111.54112.43119.09130.30130.92131.33131.66136.85137.34

OpenBenchmarking.orgScore Per Watt, More Is BetterLuxMark 3.1OpenCL Device: GPU - Scene: MicrophoneGTX 970GTX 980GTX 980 TiGTX 1080GTX 1060GTX 1080 TiGTX 1070GTX 1070 TiGTX 1660 TiGTX 1660RTX 2060RTX 2080RTX 2060 SUPERRTX 2070RTX 2080 SUPERRTX 2080 TiTITAN RTXRTX 2070 SUPER2040608010044.9146.0847.2550.2951.1457.6858.6370.3270.3371.2272.1182.6083.0983.9289.5889.7791.0092.78

OpenBenchmarking.orgScore Per Watt, More Is BetterLuxMark 3.1OpenCL Device: GPU - Scene: HotelGTX 970GTX 980GTX 980 TiGTX 1060GTX 1080GTX 1070GTX 1080 TiGTX 1660 TiRTX 2060GTX 1660RTX 2080RTX 2070GTX 1070 TiRTX 2060 SUPERRTX 2080 TiRTX 2070 SUPERRTX 2080 SUPERTITAN RTX61218243013.7214.1615.2117.0018.5119.5920.0222.5022.9224.2224.5025.5225.6426.3826.9927.1827.4127.46

LeelaChessZero

LeelaChessZero (lc0 / lczero) is a chess engine automated vian neural networks. This test profile can be used for OpenCL, CUDA + cuDNN, and BLAS (CPU-based) benchmarking. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgNodes Per Second, More Is BetterLeelaChessZero 0.22.0Backend: OpenCLGTX 970GTX 1060GTX 980GTX 1660GTX 1660 TiGTX 980 TiGTX 1070RTX 2060GTX 1070 TiRTX 2060 SUPERRTX 2070GTX 1080RTX 2070 SUPERRTX 2080GTX 1080 TiRTX 2080 SUPERRTX 2080 TiTITAN RTX7001400210028003500SE +/- 1.93, N = 15SE +/- 3.68, N = 4SE +/- 2.79, N = 3SE +/- 4.05, N = 15SE +/- 5.83, N = 15SE +/- 5.67, N = 15SE +/- 12.32, N = 15SE +/- 1.84, N = 3SE +/- 8.69, N = 6SE +/- 18.12, N = 15SE +/- 16.93, N = 15SE +/- 14.70, N = 3SE +/- 17.64, N = 7SE +/- 21.60, N = 3SE +/- 32.29, N = 3SE +/- 29.82, N = 3SE +/- 8.77, N = 3SE +/- 28.21, N = 3207.84262.41280.99335.86420.04466.84642.12704.69753.69998.17999.751146.751604.211879.991886.302105.263032.103126.481. (CXX) g++ options: -lpthread

clpeak

OpenBenchmarking.orgGIOPS Per Watt, More Is BetterclpeakOpenCL Test: Integer Compute INTGTX 980GTX 980 TiGTX 970GTX 1060GTX 1080 TiGTX 1070GTX 1070 TiGTX 1080RTX 2070RTX 2080 TiRTX 2070 SUPERGTX 1660 TiRTX 2060TITAN RTXRTX 2080 SUPERGTX 1660RTX 2060 SUPERRTX 20803060901201508.449.009.1910.8316.5223.8925.5926.8252.7854.7660.3961.3863.2566.5872.1679.9480.74123.07

LeelaChessZero

OpenBenchmarking.orgNodes Per Second Per Watt, More Is BetterLeelaChessZero 0.22.0Backend: OpenCLGTX 970GTX 980GTX 1060GTX 980 TiGTX 1660GTX 1660 TiGTX 1070RTX 2060RTX 2070GTX 1070 TiRTX 2060 SUPERGTX 1080GTX 1080 TiRTX 2070 SUPERRTX 2080RTX 2080 SUPERRTX 2080 TiTITAN RTX481216201.261.831.902.162.843.134.214.795.785.866.577.108.758.9810.7312.3214.0015.81

clpeak

Clpeak is designed to test the peak capabilities of OpenCL devices. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGIOPS, More Is BetterclpeakOpenCL Test: Integer Compute INTGTX 970GTX 1060GTX 980GTX 980 TiGTX 1070GTX 1070 TiGTX 1080GTX 1080 TiGTX 1660GTX 1660 TiRTX 2060RTX 2060 SUPERRTX 2070RTX 2070 SUPERRTX 2080RTX 2080 SUPERRTX 2080 TiTITAN RTX3K6K9K12K15KSE +/- 19.67, N = 3SE +/- 13.36, N = 15SE +/- 0.38, N = 3SE +/- 23.09, N = 3SE +/- 24.36, N = 3SE +/- 0.72, N = 3SE +/- 26.46, N = 3SE +/- 29.87, N = 15SE +/- 32.97, N = 3SE +/- 64.34, N = 15SE +/- 63.11, N = 3SE +/- 76.65, N = 15SE +/- 84.78, N = 15SE +/- 81.60, N = 15SE +/- 4.11, N = 3SE +/- 83.79, N = 15SE +/- 57.62, N = 3SE +/- 156.59, N = 151140.291267.891312.061610.281685.052076.932430.743301.894657.794775.455269.017023.077161.488570.609660.9210404.7113609.3313841.251. (CXX) g++ options: -O3 -rdynamic -lOpenCL

NAMD CUDA

NAMD is a parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems. NAMD was developed by the Theoretical and Computational Biophysics Group in the Beckman Institute for Advanced Science and Technology at the University of Illinois at Urbana-Champaign. This version of the NAMD test profile uses CUDA GPU acceleration. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgdays/ns, Fewer Is BetterNAMD CUDA 2.13ATPase Simulation - 327,506 AtomsGTX 970GTX 980GTX 1060GTX 980 TiGTX 1660GTX 1070GTX 1660 TiGTX 1070 TiGTX 1080RTX 2060GTX 1080 TiRTX 2070 SUPERRTX 2070RTX 2080 SUPERRTX 2060 SUPERRTX 2080RTX 2080 TiTITAN RTX0.08180.16360.24540.32720.409SE +/- 0.00026, N = 4SE +/- 0.00159, N = 3SE +/- 0.00303, N = 3SE +/- 0.00105, N = 3SE +/- 0.00287, N = 3SE +/- 0.00195, N = 3SE +/- 0.00192, N = 3SE +/- 0.00075, N = 6SE +/- 0.00088, N = 5SE +/- 0.00147, N = 4SE +/- 0.00044, N = 3SE +/- 0.00245, N = 3SE +/- 0.00250, N = 3SE +/- 0.00233, N = 3SE +/- 0.00245, N = 3SE +/- 0.00199, N = 3SE +/- 0.00238, N = 3SE +/- 0.00297, N = 30.363680.331100.317890.286750.250310.239570.231850.222690.209780.202500.196690.195010.194400.193850.193360.193070.189090.18867

JuliaGPU

JuliaGPU is an OpenCL benchmark with this version containing various PTS-specific enhancements. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSamples/sec, More Is BetterJuliaGPU 1.2pts1OpenCL Device: GPUGTX 970GTX 980GTX 1060GTX 980 TiGTX 1070GTX 1070 TiGTX 1660GTX 1080GTX 1660 TiRTX 2060GTX 1080 TiRTX 2060 SUPERRTX 2070RTX 2070 SUPERRTX 2080RTX 2080 SUPERRTX 2080 TiTITAN RTX60M120M180M240M300MSE +/- 383961.59, N = 3SE +/- 52667.10, N = 3SE +/- 137674.47, N = 3SE +/- 78142.08, N = 3SE +/- 76295.47, N = 3SE +/- 97519.45, N = 3SE +/- 197521.26, N = 3SE +/- 341457.11, N = 3SE +/- 495295.96, N = 3SE +/- 121354.48, N = 3SE +/- 540298.84, N = 3SE +/- 369711.60, N = 3SE +/- 633693.84, N = 3SE +/- 389272.10, N = 3SE +/- 169596.23, N = 3SE +/- 1165562.77, N = 3SE +/- 78810.54, N = 3SE +/- 489061.14, N = 3169258044.90181882709.77182188318.67195653728.47216942144.93220447755.87230919642.13237914974.40239300837.60251925176.90262248899.33264172441.47267086274.53275868151.17280162469.67286818331.27299834728.80303198573.971. (CC) gcc options: -O3 -march=native -ftree-vectorize -funroll-loops -lglut -lOpenCL -lGL -lm

OctaneBench

OpenBenchmarking.orgScore Per Watt, More Is BetterOctaneBench 4.00cTotal ScoreGTX 970GTX 980GTX 980 TiGTX 1060GTX 1070RTX 2060GTX 1080GTX 1080 TiGTX 1660 TiGTX 1660RTX 2080RTX 2070RTX 2080 TiRTX 2060 SUPERTITAN RTXRTX 2070 SUPERRTX 2080 SUPERGTX 1070 Ti0.24080.48160.72240.96321.2040.600.610.640.760.840.870.880.890.910.930.930.960.960.970.991.041.041.07

Rodinia

Rodinia is a suite focused upon accelerating compute-intensive applications with accelerators. CUDA, OpenMP, and OpenCL parallel models are supported by the included applications. This profile utilizes the OpenCL and OpenMP test binaries at the moment. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterRodinia 2.4Test: OpenCL MyocyteGTX 980 TiGTX 980GTX 970GTX 1070 TiGTX 1080 TiGTX 1070GTX 1080GTX 1060TITAN RTXRTX 2080RTX 2070RTX 2060RTX 2080 TiGTX 1660RTX 2070 SUPERGTX 1660 TiRTX 2080 SUPERRTX 2060 SUPER1224364860SE +/- 0.18, N = 3SE +/- 0.05, N = 3SE +/- 0.06, N = 3SE +/- 0.14, N = 3SE +/- 0.03, N = 3SE +/- 0.08, N = 3SE +/- 0.04, N = 3SE +/- 0.10, N = 3SE +/- 0.04, N = 3SE +/- 0.04, N = 3SE +/- 0.03, N = 3SE +/- 0.05, N = 3SE +/- 0.07, N = 3SE +/- 0.08, N = 3SE +/- 0.15, N = 3SE +/- 0.05, N = 3SE +/- 0.04, N = 3SE +/- 0.04, N = 352.1347.3845.4838.7035.9135.1034.8734.6931.6931.6531.6431.1131.0530.9730.7630.6730.6330.421. (CXX) g++ options: -O2 -lOpenCL

Darktable

Darktable is an open-source photography / workflow application this will use any system-installed Darktable program or on Windows will automatically download the pre-built binary from the project. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterDarktable 2.6.0Test: Masskrug - Acceleration: OpenCLGTX 970GTX 980GTX 980 TiGTX 1060GTX 1660 TiGTX 1660GTX 1070 TiGTX 1080GTX 1080 TiGTX 1070RTX 2060RTX 2080RTX 2070 SUPERRTX 2080 SUPERRTX 2060 SUPERRTX 2070TITAN RTXRTX 2080 Ti1.30052.6013.90155.2026.5025SE +/- 0.03, N = 3SE +/- 0.02, N = 3SE +/- 0.01, N = 3SE +/- 0.02, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.02, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.02, N = 3SE +/- 0.01, N = 35.785.744.124.074.024.013.973.943.923.923.733.713.713.693.683.673.663.66

ViennaCL

ViennaCL is an open-source linear algebra library written in C++ and with support for OpenCL and OpenMP. This test profile uses ViennaCL OpenCL support and runs the included computational benchmark. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGFLOPS, More Is BetterViennaCL 1.4.2OpenCL LU FactorizationGTX 970GTX 1060GTX 980GTX 980 TiGTX 1070GTX 1070 TiGTX 1660GTX 1660 TiGTX 1080RTX 2060GTX 1080 TiRTX 2060 SUPERRTX 2070RTX 2070 SUPERRTX 2080RTX 2080 SUPERRTX 2080 TiTITAN RTX1632486480SE +/- 0.11, N = 3SE +/- 0.05, N = 3SE +/- 0.04, N = 3SE +/- 0.02, N = 3SE +/- 0.03, N = 3SE +/- 0.01, N = 3SE +/- 0.02, N = 3SE +/- 0.05, N = 3SE +/- 0.20, N = 3SE +/- 0.21, N = 3SE +/- 0.31, N = 3SE +/- 0.06, N = 3SE +/- 0.03, N = 3SE +/- 0.05, N = 3SE +/- 0.07, N = 3SE +/- 0.26, N = 3SE +/- 0.72, N = 3SE +/- 0.60, N = 356.9558.6759.2162.0163.8664.6865.1066.0666.6767.9269.0969.1769.4170.4570.9671.4772.7172.961. (CXX) g++ options: -rdynamic -lOpenCL

System Power Consumption Monitor

OpenBenchmarking.orgWattsSystem Power Consumption MonitorPhoronix Test Suite System MonitoringTITAN RTXRTX 2080 TiGTX 1080 TiGTX 980 TiRTX 2080RTX 2080 SUPERGTX 980RTX 2070GTX 1080RTX 2060 SUPERGTX 970RTX 2060GTX 1070RTX 2070 SUPERGTX 1070 TiGTX 1060GTX 1660 TiGTX 166070140210280350Min: 50.6 / Avg: 227.86 / Max: 371.4Min: 49.7 / Avg: 227.4 / Max: 374Min: 49.6 / Avg: 207.86 / Max: 380Min: 53.6 / Avg: 199.07 / Max: 370.3Min: 47.5 / Avg: 181.54 / Max: 342.9Min: 46 / Avg: 173.42 / Max: 330.5Min: 49.8 / Avg: 167.77 / Max: 329.4Min: 46 / Avg: 164.53 / Max: 321.3Min: 44.9 / Avg: 162.99 / Max: 328.3Min: 45.4 / Avg: 158.95 / Max: 312Min: 48.8 / Avg: 157.71 / Max: 306.3Min: 46.1 / Avg: 153.75 / Max: 303.8Min: 43.8 / Avg: 150.54 / Max: 286.9Min: 45.5 / Avg: 134.05 / Max: 323.3Min: 48.6 / Avg: 131.89 / Max: 259.9Min: 44.3 / Avg: 128.45 / Max: 269.5Min: 45.4 / Avg: 127.55 / Max: 273.9Min: 43.1 / Avg: 115.15 / Max: 262.4

GPU Temperature Monitor

OpenBenchmarking.orgCelsiusGPU Temperature MonitorPhoronix Test Suite System MonitoringGTX 980 TiGTX 980GTX 1080 TiRTX 2080GTX 1080TITAN RTXGTX 1070RTX 2080 TiRTX 2070GTX 1060RTX 2060GTX 1660RTX 2060 SUPERRTX 2080 SUPERGTX 970GTX 1660 TiGTX 1070 TiRTX 2070 SUPER1632486480Min: 36 / Avg: 71.62 / Max: 85Min: 29 / Avg: 68.53 / Max: 81Min: 34 / Avg: 67.92 / Max: 84Min: 30 / Avg: 66.02 / Max: 83Min: 30 / Avg: 63.66 / Max: 77Min: 37 / Avg: 62.01 / Max: 80Min: 28 / Avg: 61.94 / Max: 76Min: 31 / Avg: 60.94 / Max: 77Min: 28 / Avg: 58.64 / Max: 77Min: 30 / Avg: 58.15 / Max: 74Min: 32 / Avg: 57.94 / Max: 72Min: 28 / Avg: 56.71 / Max: 77Min: 29 / Avg: 54.33 / Max: 75Min: 34 / Avg: 53.35 / Max: 70Min: 28 / Avg: 52.34 / Max: 68Min: 30 / Avg: 50.73 / Max: 65Min: 39 / Avg: 48.41 / Max: 61Min: 27 / Avg: 43.67 / Max: 69

94 Results Shown

SHOC Scalable HeterOgeneous Computing:
  OpenCL - MD5 Hash
  System Power Consumption Monitor
  System Power Consumption Monitor
  System Power Consumption Monitor
  System Power Consumption Monitor
  System Power Consumption Monitor
  System Power Consumption Monitor
  System Power Consumption Monitor
  System Power Consumption Monitor
  System Power Consumption Monitor
  System Power Consumption Monitor
  System Power Consumption Monitor
  System Power Consumption Monitor
  System Power Consumption Monitor
  System Power Consumption Monitor
  System Power Consumption Monitor
  System Power Consumption Monitor
  System Power Consumption Monitor
  System Power Consumption Monitor
  System Power Consumption Monitor
  Single-Precision Float
  System Power Consumption Monitor
  Global Memory Bandwidth
  System Power Consumption Monitor
SHOC Scalable HeterOgeneous Computing
Rodinia:
  System Power Consumption Monitor:
    Watts
    Watts
SHOC Scalable HeterOgeneous Computing
PlaidML:
  No - Inference - ResNet 50 - OpenCL
  No - Inference - Mobilenet - OpenCL
  OpenCL - FFT SP
LuxMark
Darktable
PlaidML:
  Yes - Inference - Inception V3 - OpenCL
  Yes - Inference - VGG19 - OpenCL
  No - Inference - VGG19 - OpenCL
  Yes - Inference - VGG16 - OpenCL
  No - Inference - VGG16 - OpenCL
  Yes - Inference - NASNer Large - OpenCL
cl-mem
clpeak
PlaidML
SHOC Scalable HeterOgeneous Computing
LuxMark
PlaidML
PlaidML:
  Yes - Inference - VGG16 - OpenCL
  Yes - Inference - Mobilenet - OpenCL
  No - Inference - Inception V3 - OpenCL
PlaidML
cl-mem
Rodinia
LuxMark
clpeak
PlaidML:
  No - Inference - Mobilenet - OpenCL
  No - Inference - Inception V3 - OpenCL
cl-mem
clpeak
PlaidML:
  Yes - Inference - VGG19 - OpenCL
  Yes - Inference - Inception V3 - OpenCL
  Yes - Inference - ResNet 50 - OpenCL
  Write
PlaidML
OctaneBench
PlaidML
cl-mem:
  Copy
  Yes - Inference - NASNer Large - OpenCL
  No - Inference - VGG16 - OpenCL
PlaidML
FAHBench
PlaidML
Rodinia
PlaidML:
  Yes - Inference - DenseNet 201 - OpenCL
  Double-Precision Double
Darktable
SHOC Scalable HeterOgeneous Computing:
  OpenCL - Max SP Flops
  GPU
cl-mem
ViennaCL:
  OpenCL LU Factorization
 
  GPU - Luxball HDR
  GPU - Microphone
  GPU - Hotel
LeelaChessZero
clpeak:
  Integer Compute INT
  OpenCL
clpeak
NAMD CUDA
JuliaGPU
OctaneBench
Rodinia
Darktable
ViennaCL
System Power Consumption Monitor:
  Phoronix Test Suite System Monitoring:
    Watts
    Celsius