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 250GBNVIDIA GeForce RTX 2070 SUPER 8GB (1605/7000MHz)NVIDIA GeForce RTX 2060 SUPER 8GB (1470/7000MHz)NVIDIA GeForce GTX 980 Ti 6GB (999/3505MHz)NVIDIA GeForce RTX 2080 SUPER 8GB (1650/7750MHz)NVIDIA TITAN RTX 24GB (1350/7000MHz)ASUS NVIDIA GeForce RTX 2070 8GB (1410/7000MHz)Zotac NVIDIA GeForce GTX 1070 Ti 8GB (1607/4006MHz)Zotac NVIDIA GeForce RTX 2080 8GB (795/810MHz)NVIDIA GeForce RTX 2060 6GB (1365/7000MHz)NVIDIA GeForce GTX 1060 6GB (1506/4006MHz)NVIDIA GeForce GTX 1080 8GB (1607/5005MHz)NVIDIA GeForce GTX 1080 Ti 11GB (1480/5508MHz)eVGA NVIDIA GeForce GTX 1660 Ti 6GB (1500/6000MHz)NVIDIA GeForce GTX 980 4GB (1126/3505MHz)ASUS NVIDIA GeForce GTX 1660 6GB (1530/4001MHz)NVIDIA GeForce GTX 1070 8GB (1506/4006MHz)eVGA NVIDIA GeForce GTX 970 4GB (1163/3505MHz)NVIDIA GeForce RTX 2080 Ti 11GB (1350/7000MHz)Realtek ALC1220Acer B286HKIntel I219-VUbuntu 19.045.3.0-999-generic (x86_64) 201909145.0.0-29-generic (x86_64)GNOME 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- RTX 2070 SUPER: GPU Compute Cores: 2560- RTX 2060 SUPER: GPU Compute Cores: 2176- GTX 980 Ti: GPU Compute Cores: 2816- RTX 2080 SUPER: GPU Compute Cores: 3072- TITAN RTX: GPU Compute Cores: 4608- RTX 2070: GPU Compute Cores: 2304- GTX 1070 Ti: GPU Compute Cores: 2432- RTX 2080: GPU Compute Cores: 2944- RTX 2060: GPU Compute Cores: 1920- GTX 1060: GPU Compute Cores: 1280- GTX 1080: GPU Compute Cores: 2560- GTX 1080 Ti: GPU Compute Cores: 3584- GTX 1660 Ti: GPU Compute Cores: 1536- GTX 980: GPU Compute Cores: 2048- GTX 1660: GPU Compute Cores: 1408- GTX 1070: GPU Compute Cores: 1920- GTX 970: GPU Compute Cores: 1664- RTX 2080 Ti: GPU Compute Cores: 4352- RTX 2070 SUPER, GTX 980 Ti, RTX 2080 SUPER, TITAN RTX, RTX 2070, GTX 1070 Ti, RTX 2080, RTX 2060, GTX 1060, GTX 1080, GTX 1080 Ti, GTX 1660 Ti, GTX 980, GTX 1660, GTX 1070, GTX 970, RTX 2080 Ti: 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

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

RTX 2070 SUPERRTX 2060 SUPERGTX 980 TiRTX 2080 SUPERTITAN RTXRTX 2070GTX 1070 TiRTX 2080RTX 2060GTX 1060GTX 1080GTX 1080 TiGTX 1660 TiGTX 980GTX 1660GTX 1070GTX 970RTX 2080 TiLogarithmic 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 FactorizationRTX 2070 SUPERRTX 2060 SUPERGTX 980 TiRTX 2080 SUPERTITAN RTXRTX 2070GTX 1070 TiRTX 2080RTX 2060GTX 1060GTX 1080GTX 1080 TiGTX 1660 TiGTX 980GTX 1660GTX 1070GTX 970RTX 2080 Ti21.781088.17204990.80239.6197.82122.32123.20154.6455.24395.67310.279869.3429734499.69283.98319.576565369.111649.17215.858502.71421.58220.762264.97190.01229.126.821.93291.871604.218570.600.19501275868151.1730.763.7170.4518.22971.24185090.75219.7680.82101.17102.58128.2248.96395.67263.118378.8730093440.79250.98333.206148367.921531.01199.437089.50374.71205.231983.82179.51205.207.871.95287.80998.177023.070.19336264172441.4730.423.6869.179.22725.98110961.51116.3156.1368.4771.2687.3930.64265.33196.606213.9716871270.00162.63241.503885263.22990.12135.145538.75247.47142.201202.77111.46116.029.953.27216.83466.841610.280.28675195653728.4752.134.1262.0126.561203.57201640.79301.11115.44143.02145.65180.4564.80436.27378.9812015.5030179589.86327.80345.776839405.001762.00259.2610335.50468.70233.562437.48200.38256.835.741.82301.232105.2610404.710.19385286818331.2730.633.6971.4736.391578.29307560.74373.71162.05196.44204.67247.8387.17566.70547.9717334.0046546790.77433.81495.379836528.892466.66347.9314203.87648.36322.762842.38263.13301.934.241.64322.203126.4813841.250.18867303198573.9731.693.6672.9618.77976.78184410.75220.9983.56103.89105.60131.5449.94395.70268.328528.7030097446.23251.07322.676150368.961516.96198.037198.64376.73206.881969.50176.49204.717.751.93284.43999.757161.480.19440267086274.5331.643.6769.4111.70525.89102591.17147.0473.1290.3492.03114.0335.41205.27242.637715.4216925333.03205.85190.034170197.261009.26153.346770.97294.36141.351371.21130.15138.217.882.93182.70753.692076.930.22269220447755.8738.703.9764.6824.071100.00199160.80268.33105.54129.58133.20164.0558.47395.70345.8110952.7729164548.83305.76331.506590368.471663.87238.738883.90441.24222.882292.38189.28242.756.221.90289.201879.999660.920.19307280162469.6731.653.7170.9616.04818.44137540.83193.7571.0788.0489.55110.9341.11296.20231.447320.7321683389.40220.44241.204833275.861232.47167.875329.07319.25164.521694.07154.19183.418.902.22237.77704.695269.010.20250251925176.9031.113.7367.927.26326.6870861.2897.8344.3754.7856.0769.3123.16153.50149.584788.9212245224.89130.64144.572648146.62726.30104.444199.71196.0091.44908.4391.07102.6111.933.65137.20262.411267.890.31789182188318.6734.694.0758.6714.25614.6987161.09173.7983.83101.00106.09128.0540.38228.80297.949407.7513788399.00240.62214.673807222.091123.85184.808314.29337.47147.981544.50143.53155.226.492.72205.931146.752430.740.20978237914974.4034.873.9466.6719.72982.23137211.05228.68115.03138.68145.42175.3756.64337.53414.9613230.7721689523.98333.54340.275649328.901672.73257.5511720.57496.24212.042162.58191.31198.254.962.29283.201886.303301.890.19669262248899.3335.913.9269.0912.98665.66110031.15161.3358.0373.3573.1892.4534.12250.23185.125893.4116147315.83172.68208.673805234.671002.00140.054793.66259.43132.281394.05114.58139.8110.822.92208.50420.044775.450.23185239300837.6030.674.0266.067.49458.3589143.10101.9243.6353.4955.7068.9524.24164.50159.685052.7313246231.66142.14151.503048164.25759.43105.644476.69203.91109.70973.3992.92102.8611.693.92143.40280.991312.060.33110181882709.7747.385.7459.2111.87452.8997941.18137.6652.5267.2466.2484.8328.99162.90168.445329.8415162287.68156.50148.873733157.60814.65116.904610.01228.14118.491160.52102.83126.6411.873.35145.37335.864657.790.25031230919642.1330.974.0165.1010.61478.5499831.11141.5563.5676.8980.2797.3233.07205.27223.917115.3917290315.37196.01190.903870196.47987.69147.176269.49276.89132.861288.94127.02140.298.262.89182.00642.121685.050.23957216942144.9335.103.9263.866.50411.2979853.1688.1639.3447.7049.7660.3221.42142.10137.474362.3111732204.32116.05132.602730143.48671.4994.723888.16181.8795.60841.4879.7191.5312.994.42124.77207.841140.290.36368169258044.9045.485.7856.9534.911485.73286310.75363.16154.20186.19194.83234.6584.97544.33521.9016656.2042974758.21424.07441.239215506.332335.46343.4913532.74634.09309.042750.57254.45301.894.391.64324.403032.1013609.330.18909299834728.8031.053.6672.71OpenBenchmarking.org

SHOC Scalable HeterOgeneous Computing

OpenBenchmarking.orgGHash/s Per Watt, More Is BetterSHOC Scalable HeterOgeneous Computing 2015-11-10Target: OpenCL - Benchmark: MD5 HashGTX 970GTX 1660GTX 980GTX 1660 TiGTX 1080GTX 1060RTX 2060RTX 2080RTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2070 SUPER0.08330.16660.24990.33320.41650.050.260.080.260.150.110.120.210.150.370.320.040.30

NAMD CUDA

OpenBenchmarking.orgWatts, Fewer Is BetterNAMD CUDA 2.13System Power Consumption MonitorRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER70140210280350Min: 53.9 / Avg: 251.92 / Max: 374Min: 51.3 / Avg: 258.19 / Max: 306.3Min: 48.2 / Avg: 206.59 / Max: 286.9Min: 44.9 / Avg: 177.54 / Max: 262.4Min: 52.6 / Avg: 238.95 / Max: 329.4Min: 47.7 / Avg: 177.22 / Max: 273.9Min: 55.3 / Avg: 266.23 / Max: 380Min: 48.6 / Avg: 253.18 / Max: 326.9Min: 45.2 / Avg: 198.8 / Max: 269.5Min: 46.1 / Avg: 197.89 / Max: 303.8Min: 52.9 / Avg: 238.49 / Max: 342.9Min: 50.3 / Avg: 198.82 / Max: 259.9Min: 50 / Avg: 202.69 / Max: 321.3Min: 54.3 / Avg: 214.96 / Max: 367.7Min: 48.8 / Avg: 219.44 / Max: 330.5Min: 55.9 / Avg: 272.91 / Max: 370.3Min: 48.4 / Avg: 233.81 / Max: 312Min: 47.2 / Avg: 198.42 / Max: 323.3

SHOC Scalable HeterOgeneous Computing

OpenBenchmarking.orgWatts, Fewer Is BetterSHOC Scalable HeterOgeneous Computing 2015-11-10System Power Consumption MonitorRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER70140210280350Min: 51.3 / Avg: 217.17 / Max: 360Min: 80.6 / Avg: 148.92 / Max: 222.7Min: 78 / Avg: 141.46 / Max: 206.4Min: 44.5 / Avg: 106.24 / Max: 161Min: 97.6 / Avg: 160.93 / Max: 243.5Min: 46.4 / Avg: 118.75 / Max: 170.7Min: 49.6 / Avg: 199.67 / Max: 326.6Min: 94 / Avg: 157.13 / Max: 259.6Min: 74.8 / Avg: 119.53 / Max: 184.8Min: 47 / Avg: 145.37 / Max: 229.5Min: 48.7 / Avg: 171.33 / Max: 292.2Min: 50.5 / Avg: 125.61 / Max: 179.8Min: 47.9 / Avg: 149.29 / Max: 251.7Min: 52 / Avg: 223.03 / Max: 367Min: 47 / Avg: 164.08 / Max: 318.6Min: 126.9 / Avg: 193.91 / Max: 298.6Min: 46.8 / Avg: 148.63 / Max: 238Min: 47.1 / Avg: 150.09 / Max: 265.5

LeelaChessZero

OpenBenchmarking.orgWatts, Fewer Is BetterLeelaChessZero 0.22.0System Power Consumption MonitorGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER70140210280350Min: 82.3 / Avg: 164.63 / Max: 252.9Min: 71.9 / Avg: 152.4 / Max: 214.7Min: 46.5 / Avg: 118.46 / Max: 180.4Min: 51.8 / Avg: 153.94 / Max: 247.5Min: 47.9 / Avg: 134.26 / Max: 195.9Min: 106.6 / Avg: 215.46 / Max: 320.5Min: 48.8 / Avg: 161.47 / Max: 252.9Min: 47.2 / Avg: 138.37 / Max: 187.2Min: 49.1 / Avg: 147.07 / Max: 231.4Min: 52.8 / Avg: 175.13 / Max: 286.6Min: 52 / Avg: 128.59 / Max: 197.7Min: 48.6 / Avg: 172.95 / Max: 253.7Min: 53.3 / Avg: 197.7 / Max: 371.4Min: 47.5 / Avg: 170.9 / Max: 315Min: 59.1 / Avg: 216.14 / Max: 319.4Min: 45.5 / Avg: 151.83 / Max: 241.9Min: 47.2 / Avg: 178.69 / Max: 276

LuxMark

OpenBenchmarking.orgWatts, Fewer Is BetterLuxMark 3.1System Power Consumption MonitorRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER70140210280350Min: 54.2 / Avg: 341.41 / Max: 361Min: 50.9 / Avg: 198.98 / Max: 206.3Min: 48.8 / Avg: 197.56 / Max: 206Min: 46.7 / Avg: 154.16 / Max: 157.9Min: 51.4 / Avg: 215.19 / Max: 226.6Min: 47.2 / Avg: 169.1 / Max: 176.4Min: 55.9 / Avg: 282.16 / Max: 295.6Min: 47.9 / Avg: 205.71 / Max: 214.4Min: 45.7 / Avg: 155.74 / Max: 161.6Min: 50.4 / Avg: 210.86 / Max: 220.4Min: 52.6 / Avg: 269.03 / Max: 281.5Min: 51.1 / Avg: 162.66 / Max: 167.9Min: 51.8 / Avg: 241 / Max: 251.5Min: 57.7 / Avg: 358.16 / Max: 371Min: 50.8 / Avg: 249.5 / Max: 264.2Min: 57.2 / Avg: 255.39 / Max: 271.7Min: 47.9 / Avg: 233.07 / Max: 242.2Min: 47.6 / Avg: 241.53 / Max: 254.1

PlaidML

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER60120180240300Min: 52.9 / Avg: 251.39 / Max: 354Min: 75.4 / Avg: 201.26 / Max: 220.7Min: 84.2 / Avg: 180.68 / Max: 209.8Min: 46 / Avg: 160.67 / Max: 185.8Min: 55.7 / Avg: 208.34 / Max: 246.7Min: 48.3 / Avg: 167.7 / Max: 196.3Min: 55.7 / Avg: 245.95 / Max: 321.1Min: 89.9 / Avg: 209.47 / Max: 253.5Min: 45.1 / Avg: 170.04 / Max: 188.8Min: 50.1 / Avg: 192.21 / Max: 230.7Min: 49.9 / Avg: 230.45 / Max: 288.2Min: 52.4 / Avg: 180.41 / Max: 207.7Min: 49.7 / Avg: 197.21 / Max: 252.5Min: 53.2 / Avg: 260.22 / Max: 361.7Min: 49.5 / Avg: 224.18 / Max: 302.6Min: 119.7 / Avg: 273.57 / Max: 330.8Min: 55 / Avg: 193.52 / Max: 240.6Min: 47.5 / Avg: 199.98 / Max: 276.8

OctaneBench

OpenBenchmarking.orgWatts, Fewer Is BetterOctaneBench 4.00cSystem Power Consumption MonitorRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER60120180240300Min: 51.7 / Avg: 322.94 / Max: 355.5Min: 50.8 / Avg: 160.22 / Max: 180Min: 86 / Avg: 157.88 / Max: 173.8Min: 46.3 / Avg: 127.11 / Max: 144.7Min: 53.6 / Avg: 178.66 / Max: 203.2Min: 47.1 / Avg: 145.79 / Max: 161.1Min: 130.6 / Avg: 236.94 / Max: 265Min: 48.3 / Avg: 167.77 / Max: 228.3Min: 44.9 / Avg: 120.33 / Max: 135.2Min: 49.8 / Avg: 188.5 / Max: 218.2Min: 50 / Avg: 239.21 / Max: 278.1Min: 52.2 / Avg: 132.45 / Max: 182.7Min: 47.1 / Avg: 215.17 / Max: 242.1Min: 55.3 / Avg: 326.69 / Max: 357.7Min: 47.8 / Avg: 225.1 / Max: 261.8Min: 128.3 / Avg: 220.62 / Max: 240Min: 46.5 / Avg: 210.53 / Max: 232.6Min: 49 / Avg: 211.57 / Max: 245.6

PlaidML

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER60120180240300Min: 52.7 / Avg: 239.16 / Max: 354.3Min: 94.5 / Avg: 195.88 / Max: 219.3Min: 50 / Avg: 172.78 / Max: 208.8Min: 45.6 / Avg: 146.27 / Max: 182Min: 90.4 / Avg: 213.83 / Max: 251.4Min: 46.4 / Avg: 163.81 / Max: 195.7Min: 51.8 / Avg: 234.29 / Max: 318.4Min: 46.2 / Avg: 209.24 / Max: 254.3Min: 69.4 / Avg: 166.46 / Max: 190Min: 48.4 / Avg: 179.22 / Max: 228.5Min: 48.9 / Avg: 201.23 / Max: 285.7Min: 52.3 / Avg: 169.99 / Max: 205.7Min: 48.4 / Avg: 193.79 / Max: 250.6Min: 52.4 / Avg: 239.94 / Max: 363Min: 47.7 / Avg: 218.91 / Max: 299.1Min: 56.5 / Avg: 270.73 / Max: 328.7Min: 53.3 / Avg: 181.51 / Max: 239.5Min: 47.2 / Avg: 191.71 / Max: 276.3

clpeak

OpenBenchmarking.orgWatts, Fewer Is BetterclpeakSystem Power Consumption MonitorGTX 1660 TiGTX 1080 TiGTX 1060RTX 2070TITAN RTXRTX 2080 SUPERRTX 2060 SUPERRTX 2070 SUPER70140210280350Min: 46.4 / Avg: 77.81 / Max: 158.1Min: 52.4 / Avg: 199.89 / Max: 328.7Min: 66.2 / Avg: 117.06 / Max: 191Min: 47.8 / Avg: 135.68 / Max: 254.5Min: 52.5 / Avg: 207.88 / Max: 366.7Min: 47.9 / Avg: 144.19 / Max: 288.8Min: 47.4 / Avg: 86.98 / Max: 242.5Min: 47.5 / Avg: 141.91 / Max: 279.4

LuxMark

OpenBenchmarking.orgWatts, Fewer Is BetterLuxMark 3.1System Power Consumption MonitorRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER60120180240300Min: 53.9 / Avg: 326.39 / Max: 340.7Min: 52.2 / Avg: 180.29 / Max: 185.6Min: 48.6 / Avg: 181.94 / Max: 188.2Min: 45.9 / Avg: 139.49 / Max: 144Min: 87.7 / Avg: 195.16 / Max: 205Min: 48.2 / Avg: 157.16 / Max: 163.8Min: 107.7 / Avg: 245.73 / Max: 254Min: 75.8 / Avg: 180.11 / Max: 185.5Min: 76 / Avg: 146.92 / Max: 152Min: 47.4 / Avg: 192.86 / Max: 200.8Min: 52.5 / Avg: 244.9 / Max: 255.3Min: 52.3 / Avg: 151.74 / Max: 155.9Min: 50.1 / Avg: 230.98 / Max: 243.5Min: 53.7 / Avg: 338.9 / Max: 360.6Min: 49.4 / Avg: 230.52 / Max: 238Min: 130.4 / Avg: 238.82 / Max: 247.5Min: 47.2 / Avg: 229.14 / Max: 241Min: 47.5 / Avg: 217.27 / Max: 227.7

PlaidML

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER60120180240300Min: 52.9 / Avg: 210.77 / Max: 350.6Min: 89.6 / Avg: 193.7 / Max: 220.3Min: 70.7 / Avg: 170.23 / Max: 208.9Min: 45.5 / Avg: 136.67 / Max: 171.6Min: 53.3 / Avg: 201.25 / Max: 246.9Min: 48.2 / Avg: 154.23 / Max: 191.6Min: 120.6 / Avg: 236.48 / Max: 318.6Min: 91.2 / Avg: 194.23 / Max: 252.2Min: 45.9 / Avg: 157.15 / Max: 187.3Min: 48.9 / Avg: 179.62 / Max: 228Min: 52.6 / Avg: 181.66 / Max: 277.7Min: 51.9 / Avg: 158.16 / Max: 196.1Min: 48.7 / Avg: 189.06 / Max: 250.5Min: 52.8 / Avg: 227.24 / Max: 356.3Min: 49.1 / Avg: 194.92 / Max: 278.5Min: 71.2 / Avg: 244.52 / Max: 316.6Min: 57.1 / Avg: 209.61 / Max: 237.5Min: 47.2 / Avg: 198.27 / Max: 271.7

LuxMark

OpenBenchmarking.orgWatts, Fewer Is BetterLuxMark 3.1System Power Consumption MonitorRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER60120180240300Min: 55.9 / Avg: 318.95 / Max: 337.2Min: 51.9 / Avg: 177.8 / Max: 184.4Min: 49 / Avg: 170.27 / Max: 177.6Min: 46 / Avg: 137.52 / Max: 142.7Min: 51 / Avg: 193.46 / Max: 203.7Min: 48 / Avg: 156.46 / Max: 161.4Min: 52.7 / Avg: 237.89 / Max: 245.4Min: 49.1 / Avg: 173.32 / Max: 180.3Min: 45.6 / Avg: 138.57 / Max: 144.8Min: 48.6 / Avg: 190.73 / Max: 198.4Min: 53.8 / Avg: 241.11 / Max: 251.4Min: 50.1 / Avg: 145.89 / Max: 150.4Min: 51.5 / Avg: 219.74 / Max: 234.1Min: 60.2 / Avg: 337.98 / Max: 356.9Min: 47.8 / Avg: 225.09 / Max: 235.4Min: 112.5 / Avg: 234.81 / Max: 244.3Min: 49.8 / Avg: 222.76 / Max: 232.3Min: 47.6 / Avg: 220.93 / Max: 232.4

PlaidML

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER60120180240300Min: 52.7 / Avg: 188.04 / Max: 345.4Min: 51.5 / Avg: 184.27 / Max: 233.4Min: 47.7 / Avg: 162.2 / Max: 207.3Min: 45.6 / Avg: 137.8 / Max: 169.2Min: 69.1 / Avg: 196.2 / Max: 247.2Min: 47.3 / Avg: 151.58 / Max: 191.5Min: 118 / Avg: 235.58 / Max: 316.5Min: 88.2 / Avg: 189.28 / Max: 251.8Min: 45.8 / Avg: 152.31 / Max: 187.6Min: 48.1 / Avg: 163.79 / Max: 226.4Min: 54.1 / Avg: 173.35 / Max: 273.1Min: 95.2 / Avg: 160.1 / Max: 191.4Min: 48.1 / Avg: 174.02 / Max: 249.3Min: 53.8 / Avg: 216.91 / Max: 353.5Min: 49.4 / Avg: 181.31 / Max: 274.6Min: 55.1 / Avg: 244.29 / Max: 316.2Min: 54 / Avg: 187.95 / Max: 233.7Min: 46.7 / Avg: 187.65 / Max: 267.6

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER60120180240300Min: 50.4 / Avg: 231.53 / Max: 336Min: 94.8 / Avg: 192.64 / Max: 216.8Min: 83.7 / Avg: 182.29 / Max: 211.2Min: 44.8 / Avg: 135.27 / Max: 159.9Min: 99.4 / Avg: 199.9 / Max: 241.3Min: 46.5 / Avg: 154.44 / Max: 184.5Min: 107 / Avg: 238.78 / Max: 315.7Min: 48.2 / Avg: 203.49 / Max: 246Min: 75.4 / Avg: 157.49 / Max: 178.6Min: 48.1 / Avg: 176.3 / Max: 224.1Min: 49.7 / Avg: 201.32 / Max: 272.7Min: 51.4 / Avg: 151.49 / Max: 175.5Min: 48 / Avg: 190.9 / Max: 247Min: 51.3 / Avg: 235.38 / Max: 341.7Min: 46.7 / Avg: 204.84 / Max: 277Min: 124.3 / Avg: 237.03 / Max: 284.6Min: 54.2 / Avg: 192.58 / Max: 235.4Min: 46.5 / Avg: 184.51 / Max: 249.7

FAHBench

OpenBenchmarking.orgWatts, Fewer Is BetterFAHBench 2.3.2System Power Consumption MonitorRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER60120180240300Min: 49.7 / Avg: 218.05 / Max: 323.3Min: 48.8 / Avg: 147.69 / Max: 193Min: 43.8 / Avg: 145.58 / Max: 193.2Min: 46.5 / Avg: 114.3 / Max: 152.8Min: 49.8 / Avg: 159.19 / Max: 211.9Min: 47.6 / Avg: 127.19 / Max: 170.3Min: 77.6 / Avg: 195.24 / Max: 264.4Min: 44.9 / Avg: 154.62 / Max: 208.2Min: 66.3 / Avg: 124.04 / Max: 159.6Min: 45.7 / Avg: 151.46 / Max: 214.2Min: 47.5 / Avg: 176.01 / Max: 263Min: 49.1 / Avg: 125.16 / Max: 155Min: 46 / Avg: 158.7 / Max: 226.7Min: 52.5 / Avg: 226.18 / Max: 324.2Min: 64 / Avg: 177.55 / Max: 252.2Min: 56.3 / Avg: 186.17 / Max: 244.4Min: 48.5 / Avg: 161.35 / Max: 226.3Min: 46.6 / Avg: 161.4 / Max: 230

PlaidML

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER60120180240300Min: 51.8 / Avg: 206.66 / Max: 321.6Min: 81.4 / Avg: 182.54 / Max: 219.9Min: 84.3 / Avg: 149.15 / Max: 206.1Min: 46.3 / Avg: 123.06 / Max: 152.7Min: 56.7 / Avg: 188.31 / Max: 242.7Min: 46.3 / Avg: 136.65 / Max: 177.5Min: 128 / Avg: 191.53 / Max: 304Min: 84.7 / Avg: 196.13 / Max: 242.5Min: 46.9 / Avg: 150.12 / Max: 180Min: 47.6 / Avg: 150.66 / Max: 214.3Min: 49.4 / Avg: 176.08 / Max: 254.9Min: 51.1 / Avg: 141.76 / Max: 172.5Min: 49.8 / Avg: 167.7 / Max: 230.4Min: 56.2 / Avg: 178.56 / Max: 327.6Min: 49.6 / Avg: 170.73 / Max: 255.1Min: 126.5 / Avg: 220.09 / Max: 281.6Min: 54.4 / Avg: 162.79 / Max: 223.8Min: 49.5 / Avg: 161.34 / Max: 234.9

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER60120180240300Min: 83.3 / Avg: 172.91 / Max: 233.2Min: 89.6 / Avg: 153.55 / Max: 208.4Min: 46.3 / Avg: 119.8 / Max: 159.7Min: 53 / Avg: 176.69 / Max: 244.6Min: 47.9 / Avg: 141.14 / Max: 182.8Min: 56.4 / Avg: 186.43 / Max: 312.7Min: 48.4 / Avg: 149.71 / Max: 246.6Min: 45.9 / Avg: 132.6 / Max: 182.3Min: 48.6 / Avg: 147.64 / Max: 221.8Min: 52 / Avg: 137.63 / Max: 231.8Min: 52.2 / Avg: 140.17 / Max: 177.3Min: 47.5 / Avg: 122.1 / Max: 239.9Min: 52.7 / Avg: 128.84 / Max: 167.9Min: 49.4 / Avg: 162.94 / Max: 270.3Min: 129.1 / Avg: 233.7 / Max: 292Min: 55.4 / Avg: 144.71 / Max: 231.4Min: 46.8 / Avg: 145.98 / Max: 249.6

clpeak

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

PlaidML

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER50100150200250Min: 51.5 / Avg: 167.74 / Max: 291.7Min: 81.7 / Avg: 163.48 / Max: 201.2Min: 77.9 / Avg: 157.58 / Max: 202.6Min: 44.8 / Avg: 109.89 / Max: 143.5Min: 52.8 / Avg: 183.08 / Max: 228.8Min: 47.3 / Avg: 117.8 / Max: 162Min: 55.7 / Avg: 189.84 / Max: 284.9Min: 94.6 / Avg: 159.56 / Max: 227.4Min: 68.7 / Avg: 129.36 / Max: 164Min: 47.9 / Avg: 142.09 / Max: 199.4Min: 50.7 / Avg: 139.72 / Max: 234.8Min: 51.5 / Avg: 131.42 / Max: 162.8Min: 49 / Avg: 148.17 / Max: 210.6Min: 55.6 / Avg: 169.21 / Max: 293Min: 48.5 / Avg: 147.96 / Max: 225.2Min: 127.5 / Avg: 205.03 / Max: 260.5Min: 54.4 / Avg: 144.26 / Max: 207.2Min: 47.9 / Avg: 135.09 / Max: 211.7

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER50100150200250Min: 50.7 / Avg: 178.03 / Max: 280Min: 72.9 / Avg: 158.81 / Max: 190.7Min: 70.5 / Avg: 148.83 / Max: 185.2Min: 44.4 / Avg: 112.99 / Max: 143Min: 99.3 / Avg: 168.06 / Max: 211.7Min: 46.7 / Avg: 122.59 / Max: 164Min: 125.6 / Avg: 201.87 / Max: 257Min: 84.5 / Avg: 158.48 / Max: 204.6Min: 55.5 / Avg: 124.66 / Max: 155.7Min: 48.8 / Avg: 144.1 / Max: 197.4Min: 49 / Avg: 153.24 / Max: 230.1Min: 51 / Avg: 131.33 / Max: 154.1Min: 47.6 / Avg: 141.04 / Max: 207.9Min: 51.1 / Avg: 182.86 / Max: 282.6Min: 48.4 / Avg: 151.02 / Max: 226.9Min: 128.3 / Avg: 193.81 / Max: 239.9Min: 53 / Avg: 147.84 / Max: 203.6Min: 46.6 / Avg: 139.53 / Max: 205.1

clpeak

OpenBenchmarking.orgGFLOPS Per Watt, More Is BetterclpeakOpenCL Test: Single-Precision FloatRTX 2080 TiGTX 970GTX 1070GTX 980GTX 1660 TiGTX 1080RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER50100150200250222.0939.3670.6336.4971.3589.11109.2079.2584.4674.32103.6184.4942.00111.74121.62

PlaidML

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER50100150200250Min: 52.4 / Avg: 173.16 / Max: 273Min: 52.1 / Avg: 148.78 / Max: 190.2Min: 48.3 / Avg: 135.38 / Max: 188.6Min: 45.8 / Avg: 106.92 / Max: 138.1Min: 53.5 / Avg: 157.67 / Max: 213.1Min: 48.2 / Avg: 115.16 / Max: 152Min: 109.8 / Avg: 203.83 / Max: 255.3Min: 49.1 / Avg: 151.63 / Max: 200.9Min: 45.7 / Avg: 125.77 / Max: 157.6Min: 49 / Avg: 134.34 / Max: 190.3Min: 51.5 / Avg: 146.49 / Max: 216.5Min: 53.5 / Avg: 128.35 / Max: 157.6Min: 51.5 / Avg: 138.71 / Max: 203.8Min: 52.7 / Avg: 173.29 / Max: 277.5Min: 48.8 / Avg: 141.86 / Max: 214.3Min: 57 / Avg: 191.08 / Max: 247.4Min: 55.8 / Avg: 142.16 / Max: 204.9Min: 49.1 / Avg: 124.58 / Max: 203.3

clpeak

OpenBenchmarking.orgGBPS Per Watt, More Is BetterclpeakOpenCL Test: Global Memory BandwidthRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER36912159.151.522.633.161.652.242.732.261.845.091.923.336.184.862.024.885.41

PlaidML

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER50100150200250Min: 52.6 / Avg: 166.27 / Max: 275.3Min: 94.4 / Avg: 160.18 / Max: 203.4Min: 50.4 / Avg: 132.86 / Max: 187.3Min: 46.3 / Avg: 96.5 / Max: 135.8Min: 100 / Avg: 162.49 / Max: 218.7Min: 46.6 / Avg: 100.43 / Max: 150.5Min: 48.5 / Avg: 142.23 / Max: 208.8Min: 46.3 / Avg: 122.88 / Max: 159.6Min: 49.2 / Avg: 125.65 / Max: 186.5Min: 56.5 / Avg: 138.96 / Max: 215.1Min: 52.4 / Avg: 128.8 / Max: 152Min: 51.8 / Avg: 130.6 / Max: 207.8Min: 57.1 / Avg: 192.1 / Max: 249.1Min: 54.9 / Avg: 136.39 / Max: 187.2Min: 49.2 / Avg: 136.18 / Max: 192.6

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.orgGHash/s, More Is BetterSHOC Scalable HeterOgeneous Computing 2015-11-10Target: OpenCL - Benchmark: MD5 HashRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER816243240SE +/- 0.12, N = 3SE +/- 0.00, N = 3SE +/- 0.02, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.04, N = 3SE +/- 0.02, N = 3SE +/- 0.00, N = 3SE +/- 0.03, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 3SE +/- 0.03, N = 3SE +/- 0.06, N = 3SE +/- 0.02, N = 3SE +/- 0.00, N = 3SE +/- 0.02, N = 3SE +/- 0.05, N = 334.916.5010.6111.877.4912.9819.7214.257.2616.0424.0711.7018.7736.3926.569.2218.2221.781. (CXX) g++ options: -O2 -lSHOCCommonMPI -lSHOCCommonOpenCL -lSHOCCommon -lOpenCL -lrt -pthread -lmpi_cxx -lmpi

Rodinia

OpenBenchmarking.orgWatts, Fewer Is BetterRodinia 2.4System Power Consumption MonitorGTX 970GTX 1660GTX 980GTX 1660 TiGTX 1060RTX 2060GTX 1070 TiGTX 980 TiRTX 2070 SUPER4080120160200Min: 50.5 / Avg: 141.83 / Max: 190Min: 45.1 / Avg: 88.85 / Max: 116.6Min: 52.6 / Avg: 156.47 / Max: 203.2Min: 46 / Avg: 107.04 / Max: 129.7Min: 44.7 / Avg: 111.27 / Max: 154.1Min: 47.6 / Avg: 121.91 / Max: 156.6Min: 50.3 / Avg: 101.74 / Max: 149.4Min: 54.7 / Avg: 167.04 / Max: 233.5Min: 47 / Avg: 103.36 / Max: 166

clpeak

OpenBenchmarking.orgWatts, Fewer Is BetterclpeakSystem Power Consumption MonitorRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER4080120160200Min: 50.3 / Avg: 197 / Max: 217.1Min: 93.6 / Avg: 140.29 / Max: 146.2Min: 46 / Avg: 117.77 / Max: 137.1Min: 43.9 / Avg: 97.25 / Max: 106.6Min: 51.6 / Avg: 146.12 / Max: 159.1Min: 46.4 / Avg: 107.92 / Max: 119.4Min: 51.6 / Avg: 166.5 / Max: 193Min: 46.2 / Avg: 135.52 / Max: 152.6Min: 44.7 / Avg: 102.22 / Max: 117.3Min: 47.9 / Avg: 126.06 / Max: 143Min: 49.8 / Avg: 153.89 / Max: 172.5Min: 51 / Avg: 113.26 / Max: 124.1Min: 46.9 / Avg: 137.5 / Max: 151.9Min: 51.5 / Avg: 203.24 / Max: 225.1Min: 47.6 / Avg: 151.43 / Max: 166.9Min: 128.4 / Avg: 179.97 / Max: 191.4Min: 47.1 / Avg: 142.14 / Max: 150.8Min: 47 / Avg: 137.66 / Max: 150.3

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 SPRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER30060090012001500SE +/- 2.79, N = 3SE +/- 0.48, N = 3SE +/- 6.42, N = 4SE +/- 0.27, N = 3SE +/- 1.09, N = 3SE +/- 1.57, N = 3SE +/- 1.06, N = 3SE +/- 3.58, N = 3SE +/- 3.50, N = 7SE +/- 0.56, N = 3SE +/- 0.39, N = 3SE +/- 0.19, N = 3SE +/- 2.90, N = 3SE +/- 1.38, N = 3SE +/- 0.78, N = 3SE +/- 3.01, N = 3SE +/- 3.09, N = 3SE +/- 0.27, N = 31485.73411.29478.54452.89458.35665.66982.23614.69326.68818.441100.00525.89976.781578.291203.57725.98971.241088.171. (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: OpenCLRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER1.13182.26363.39544.52725.6593.701.051.801.901.151.842.662.251.482.163.212.103.095.033.181.062.592.89

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: Mobilenet - Device: OpenCLRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER61218243022.635.209.659.565.5311.2010.229.357.5911.6714.1611.3014.8423.2316.606.6412.9819.70

SHOC Scalable HeterOgeneous Computing

OpenBenchmarking.orgGFLOPS Per Watt, More Is BetterSHOC Scalable HeterOgeneous Computing 2015-11-10Target: OpenCL - Benchmark: FFT SPRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070GTX 980 TiRTX 2060 SUPERRTX 2070 SUPER4812162011.545.126.235.705.4512.257.977.874.0013.2315.466.368.676.9217.5915.58

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: MicrophoneRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER7K14K21K28K35KSE +/- 21.50, N = 3SE +/- 2.00, N = 3SE +/- 4.91, N = 3SE +/- 1.33, N = 3SE +/- 18.25, N = 3SE +/- 2.33, N = 3SE +/- 19.33, N = 3SE +/- 1.20, N = 3SE +/- 1.53, N = 3SE +/- 3.84, N = 3SE +/- 11.68, N = 3SE +/- 15.50, N = 3SE +/- 26.44, N = 3SE +/- 168.12, N = 3SE +/- 108.17, N = 3SE +/- 49.74, N = 3SE +/- 43.34, N = 3SE +/- 16.84, N = 3286317985998397948914110031372187167086137541991610259184413075620164110961850920499

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: OpenCLRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER0.7111.4222.1332.8443.555SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 4SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 8SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 30.753.161.111.183.101.151.051.091.280.830.801.170.750.740.791.510.750.80

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: OpenCLRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER80160240320400SE +/- 0.44, N = 3SE +/- 0.01, N = 3SE +/- 0.18, N = 3SE +/- 0.27, N = 3SE +/- 0.27, N = 3SE +/- 0.05, N = 3SE +/- 0.21, N = 3SE +/- 0.30, N = 3SE +/- 0.20, N = 3SE +/- 0.37, N = 3SE +/- 0.59, N = 3SE +/- 0.06, N = 3SE +/- 0.43, N = 3SE +/- 0.48, N = 3SE +/- 0.23, N = 3SE +/- 0.26, N = 3SE +/- 0.44, N = 3SE +/- 0.10, N = 3363.1688.16141.55137.66101.92161.33228.68173.7997.83193.75268.33147.04220.99373.71301.11116.31219.76239.61

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: VGG19 - Device: OpenCLRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER4080120160200SE +/- 0.36, N = 3SE +/- 0.18, N = 3SE +/- 0.19, N = 3SE +/- 0.08, N = 3SE +/- 0.62, N = 4SE +/- 0.12, N = 3SE +/- 0.44, N = 3SE +/- 0.28, N = 3SE +/- 0.12, N = 3SE +/- 0.19, N = 3SE +/- 0.44, N = 3SE +/- 0.03, N = 3SE +/- 0.35, N = 3SE +/- 0.48, N = 3SE +/- 0.21, N = 3SE +/- 0.77, N = 3SE +/- 0.23, N = 3SE +/- 0.16, N = 3154.2039.3463.5652.5243.6358.03115.0383.8344.3771.07105.5473.1283.56162.05115.4456.1380.8297.82

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: VGG19 - Device: OpenCLRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER4080120160200SE +/- 0.41, N = 3SE +/- 0.01, N = 3SE +/- 0.11, N = 3SE +/- 0.17, N = 3SE +/- 0.47, N = 3SE +/- 0.12, N = 3SE +/- 0.35, N = 3SE +/- 0.16, N = 3SE +/- 0.08, N = 3SE +/- 0.17, N = 3SE +/- 0.42, N = 3SE +/- 0.06, N = 3SE +/- 0.25, N = 3SE +/- 0.54, N = 3SE +/- 0.22, N = 3SE +/- 0.65, N = 3SE +/- 0.19, N = 3SE +/- 0.23, N = 3186.1947.7076.8967.2453.4973.35138.68101.0054.7888.04129.5890.34103.89196.44143.0268.47101.17122.32

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: VGG16 - Device: OpenCLRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER4080120160200SE +/- 0.51, N = 3SE +/- 0.21, N = 3SE +/- 0.30, N = 3SE +/- 0.17, N = 3SE +/- 0.83, N = 4SE +/- 0.14, N = 3SE +/- 0.62, N = 3SE +/- 0.40, N = 3SE +/- 0.18, N = 3SE +/- 0.23, N = 3SE +/- 0.57, N = 3SE +/- 0.08, N = 3SE +/- 0.39, N = 3SE +/- 0.57, N = 3SE +/- 0.29, N = 3SE +/- 1.12, N = 3SE +/- 0.35, N = 3SE +/- 0.28, N = 3194.8349.7680.2766.2455.7073.18145.42106.0956.0789.55133.2092.03105.60204.67145.6571.26102.58123.20

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: VGG16 - Device: OpenCLRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER50100150200250SE +/- 0.50, N = 3SE +/- 0.05, N = 3SE +/- 0.17, N = 3SE +/- 0.21, N = 3SE +/- 0.79, N = 3SE +/- 0.24, N = 3SE +/- 0.62, N = 3SE +/- 0.38, N = 3SE +/- 0.12, N = 3SE +/- 0.32, N = 3SE +/- 0.73, N = 3SE +/- 0.06, N = 3SE +/- 0.43, N = 3SE +/- 0.40, N = 3SE +/- 0.28, N = 3SE +/- 1.36, N = 3SE +/- 0.34, N = 3SE +/- 0.29, N = 3234.6560.3297.3284.8368.9592.45175.37128.0569.31110.93164.05114.03131.54247.83180.4587.39128.22154.64

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: NASNer Large - Device: OpenCLRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER20406080100SE +/- 0.21, N = 3SE +/- 0.03, N = 3SE +/- 0.05, N = 3SE +/- 0.03, N = 3SE +/- 0.15, N = 3SE +/- 0.03, N = 3SE +/- 0.11, N = 3SE +/- 0.08, N = 3SE +/- 0.03, N = 3SE +/- 0.08, N = 3SE +/- 0.15, N = 3SE +/- 0.02, N = 3SE +/- 0.13, N = 3SE +/- 0.25, N = 3SE +/- 0.08, N = 3SE +/- 0.10, N = 3SE +/- 0.14, N = 3SE +/- 0.05, N = 384.9721.4233.0728.9924.2434.1256.6440.3823.1641.1158.4735.4149.9487.1764.8030.6448.9655.24

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: ReadRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER120240360480600SE +/- 0.38, N = 3SE +/- 1.50, N = 8SE +/- 0.03, N = 3SE +/- 0.00, N = 3SE +/- 0.10, N = 3SE +/- 0.07, N = 3SE +/- 0.20, N = 3SE +/- 0.12, N = 3SE +/- 0.00, N = 3SE +/- 0.20, N = 3SE +/- 0.25, N = 3SE +/- 0.07, N = 3SE +/- 0.25, N = 3SE +/- 0.40, N = 3SE +/- 0.27, N = 3SE +/- 0.12, N = 3SE +/- 0.22, N = 3SE +/- 0.22, N = 3544.33142.10205.27162.90164.50250.23337.53228.80153.50296.20395.70205.27395.70566.70436.27265.33395.67395.671. (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 DoubleRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER120240360480600SE +/- 1.46, N = 3SE +/- 0.03, N = 3SE +/- 0.71, N = 3SE +/- 0.00, N = 3SE +/- 0.07, N = 3SE +/- 0.01, N = 3SE +/- 1.14, N = 3SE +/- 0.76, N = 3SE +/- 0.14, N = 3SE +/- 0.01, N = 3SE +/- 0.92, N = 3SE +/- 0.02, N = 3SE +/- 0.81, N = 3SE +/- 1.16, N = 3SE +/- 0.03, N = 3SE +/- 0.35, N = 3SE +/- 0.71, N = 3SE +/- 0.77, N = 3521.90137.47223.91168.44159.68185.12414.96297.94149.58231.44345.81242.63268.32547.97378.98196.60263.11310.271. (CXX) g++ options: -O3 -rdynamic -lOpenCL

PlaidML

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: IMDB LSTM - Device: OpenCLRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER1.14532.29063.43594.58125.72654.561.282.372.981.433.143.002.811.833.103.952.593.685.094.521.413.233.67

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 FlopsRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER4K8K12K16K20KSE +/- 87.95, N = 3SE +/- 0.74, N = 3SE +/- 1.89, N = 3SE +/- 13.79, N = 3SE +/- 3.92, N = 3SE +/- 0.04, N = 3SE +/- 3.93, N = 3SE +/- 3.00, N = 3SE +/- 6.34, N = 3SE +/- 19.13, N = 3SE +/- 29.32, N = 3SE +/- 0.84, N = 3SE +/- 45.97, N = 3SE +/- 91.95, N = 3SE +/- 61.30, N = 3SE +/- 11.70, N = 3SE +/- 27.40, N = 3SE +/- 51.02, N = 316656.204362.317115.395329.845052.735893.4113230.779407.754788.927320.7310952.777715.428528.7017334.0012015.506213.978378.879869.341. (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 HDRRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER10K20K30K40K50KSE +/- 166.33, N = 3SE +/- 6.23, N = 3SE +/- 1.00, N = 3SE +/- 35.04, N = 3SE +/- 26.16, N = 3SE +/- 19.86, N = 3SE +/- 7.67, N = 3SE +/- 17.98, N = 3SE +/- 4.00, N = 3SE +/- 0.67, N = 3SE +/- 7.51, N = 3SE +/- 36.50, N = 3SE +/- 7.54, N = 3SE +/- 20.92, N = 3SE +/- 0.88, N = 3SE +/- 39.15, N = 3SE +/- 4.93, N = 3SE +/- 98.93, N = 3429741173217290151621324616147216891378812245216832916416925300974654630179168713009329734

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: OpenCLRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER2004006008001000SE +/- 1.01, N = 3SE +/- 0.03, N = 3SE +/- 0.13, N = 3SE +/- 0.01, N = 3SE +/- 0.50, N = 3SE +/- 0.15, N = 3SE +/- 0.74, N = 3SE +/- 0.31, N = 3SE +/- 0.17, N = 3SE +/- 0.37, N = 3SE +/- 1.63, N = 3SE +/- 0.49, N = 3SE +/- 0.21, N = 3SE +/- 2.25, N = 3SE +/- 1.47, N = 3SE +/- 0.56, N = 3SE +/- 0.31, N = 3SE +/- 0.67, N = 3758.21204.32315.37287.68231.66315.83523.98399.00224.89389.40548.83333.03446.23790.77589.86270.00440.79499.69

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: VGG16 - Device: OpenCLRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER0.2340.4680.7020.9361.171.040.270.490.480.280.480.620.560.370.550.770.570.610.940.800.290.550.66

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: Mobilenet - Device: OpenCLRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER61218243026.716.9812.3514.797.1716.0615.2114.029.5718.2026.2114.1621.3522.1925.067.6720.6824.75

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: Inception V3 - Device: OpenCLRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER0.43880.87761.31641.75522.1941.660.520.990.950.561.021.340.940.701.111.361.081.181.951.520.611.231.34

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: ResNet 50 - Device: OpenCLRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER90180270360450SE +/- 1.04, N = 3SE +/- 0.00, N = 3SE +/- 0.28, N = 3SE +/- 0.31, N = 3SE +/- 0.26, N = 3SE +/- 0.06, N = 3SE +/- 0.42, N = 3SE +/- 0.11, N = 3SE +/- 0.16, N = 3SE +/- 0.16, N = 3SE +/- 0.60, N = 3SE +/- 0.08, N = 3SE +/- 0.53, N = 3SE +/- 0.70, N = 3SE +/- 0.12, N = 3SE +/- 0.06, N = 3SE +/- 0.48, N = 3SE +/- 0.71, N = 3424.07116.05196.01156.50142.14172.68333.54240.62130.64220.44305.76205.85251.07433.81327.80162.63250.98283.98

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: WriteRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER110220330440550SE +/- 0.35, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.03, N = 3SE +/- 0.00, N = 3SE +/- 0.12, N = 3SE +/- 0.28, N = 3SE +/- 0.03, N = 3SE +/- 0.03, N = 3SE +/- 0.40, N = 3SE +/- 0.15, N = 3SE +/- 0.03, N = 3SE +/- 1.00, N = 3SE +/- 1.39, N = 3SE +/- 0.54, N = 3SE +/- 0.06, N = 3SE +/- 0.82, N = 3SE +/- 0.43, N = 3441.23132.60190.90148.87151.50208.67340.27214.67144.57241.20331.50190.03322.67495.37345.77241.50333.20319.571. (CC) gcc options: -O2 -flto -lOpenCL

Rodinia

OpenBenchmarking.orgWatts, Fewer Is BetterRodinia 2.4System Power Consumption MonitorRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER306090120150Min: 51.1 / Avg: 152.87 / Max: 162.6Min: 85.4 / Avg: 117.57 / Max: 120.9Min: 70.9 / Avg: 107.97 / Max: 112.9Min: 45.5 / Avg: 90.35 / Max: 95.7Min: 88.8 / Avg: 119.77 / Max: 124.7Min: 45.9 / Avg: 98.53 / Max: 104.6Min: 53.3 / Avg: 137.65 / Max: 146.3Min: 47.4 / Avg: 113.6 / Max: 118.7Min: 62.8 / Avg: 97.17 / Max: 100.8Min: 46.6 / Avg: 112.18 / Max: 123.5Min: 49.5 / Avg: 131.08 / Max: 142Min: 49.1 / Avg: 105.1 / Max: 108.7Min: 48.1 / Avg: 122.39 / Max: 128.3Min: 51.9 / Avg: 158.82 / Max: 169.5Min: 46.6 / Avg: 123.16 / Max: 135.3Min: 110.1 / Avg: 153.24 / Max: 157.4Min: 46.3 / Avg: 122.27 / Max: 129.5Min: 46.4 / Avg: 116.19 / Max: 128.7

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: HotelRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER2K4K6K8K10KSE +/- 4.37, N = 3SE +/- 1.86, N = 3SE +/- 1.20, N = 3SE +/- 0.58, N = 3SE +/- 2.73, N = 3SE +/- 7.09, N = 3SE +/- 0.67, N = 3SE +/- 3.76, N = 3SE +/- 0.67, N = 3SE +/- 0.88, N = 3SE +/- 3.51, N = 3SE +/- 1.86, N = 3SE +/- 1.73, N = 3SE +/- 0.58, N = 3SE +/- 8.00, N = 3SE +/- 0.67, N = 3921527303870373330483805564938072648483365904170615098366839388561486565

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 BandwidthRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER110220330440550SE +/- 0.44, N = 3SE +/- 0.06, N = 3SE +/- 0.18, N = 3SE +/- 0.00, N = 3SE +/- 0.03, N = 3SE +/- 0.17, N = 3SE +/- 0.71, N = 3SE +/- 0.09, N = 3SE +/- 0.06, N = 3SE +/- 0.24, N = 3SE +/- 0.22, N = 3SE +/- 0.00, N = 3SE +/- 0.07, N = 3SE +/- 0.66, N = 3SE +/- 0.08, N = 3SE +/- 0.52, N = 3SE +/- 0.11, N = 3SE +/- 0.33, N = 3506.33143.48196.47157.60164.25234.67328.90222.09146.62275.86368.47197.26368.96528.89405.00263.22367.92369.111. (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: OpenCLRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER5001000150020002500SE +/- 6.28, N = 3SE +/- 0.75, N = 3SE +/- 1.57, N = 3SE +/- 1.38, N = 3SE +/- 0.24, N = 3SE +/- 0.86, N = 3SE +/- 5.20, N = 3SE +/- 1.27, N = 3SE +/- 0.63, N = 3SE +/- 2.11, N = 3SE +/- 4.17, N = 3SE +/- 0.73, N = 3SE +/- 1.46, N = 3SE +/- 13.68, N = 3SE +/- 2.80, N = 3SE +/- 0.07, N = 3SE +/- 1.59, N = 3SE +/- 1.25, N = 32335.46671.49987.69814.65759.431002.001672.731123.85726.301232.471663.871009.261516.962466.661762.00990.121531.011649.17

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: Inception V3 - Device: OpenCLRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER80160240320400SE +/- 0.38, N = 3SE +/- 0.16, N = 3SE +/- 0.09, N = 3SE +/- 0.12, N = 3SE +/- 0.17, N = 3SE +/- 0.23, N = 3SE +/- 0.14, N = 3SE +/- 0.38, N = 3SE +/- 0.10, N = 3SE +/- 0.23, N = 3SE +/- 0.57, N = 3SE +/- 0.06, N = 3SE +/- 0.29, N = 3SE +/- 0.42, N = 3SE +/- 0.10, N = 3SE +/- 0.07, N = 3SE +/- 0.25, N = 3SE +/- 0.07, N = 3343.4994.72147.17116.90105.64140.05257.55184.80104.44167.87238.73153.34198.03347.93259.26135.14199.43215.85

cl-mem

OpenBenchmarking.orgGB/s Per Watt, More Is Bettercl-mem 2017-01-13Benchmark: ReadRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER0.86631.73262.59893.46524.33153.381.051.681.691.192.672.101.901.342.763.261.863.283.373.851.763.093.47

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 FloatRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER3K6K9K12K15KSE +/- 207.30, N = 3SE +/- 40.24, N = 15SE +/- 3.03, N = 3SE +/- 7.83, N = 3SE +/- 46.38, N = 8SE +/- 61.47, N = 15SE +/- 5.50, N = 3SE +/- 3.14, N = 3SE +/- 1.88, N = 3SE +/- 77.72, N = 3SE +/- 7.41, N = 3SE +/- 7.63, N = 3SE +/- 81.15, N = 15SE +/- 228.75, N = 15SE +/- 124.22, N = 3SE +/- 44.36, N = 15SE +/- 84.87, N = 15SE +/- 76.18, N = 1513532.743888.166269.494610.014476.694793.6611720.578314.294199.715329.078883.906770.977198.6414203.8710335.505538.757089.508502.711. (CXX) g++ options: -O3 -rdynamic -lOpenCL

PlaidML

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: VGG19 - Device: OpenCLRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER0.16430.32860.49290.65720.82150.730.200.370.380.220.380.490.430.280.400.580.460.440.710.590.230.390.49

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: Inception V3 - Device: OpenCLRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER0.4590.9181.3771.8362.2952.040.560.951.220.611.321.131.100.781.341.751.121.572.041.990.601.491.72

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: ResNet 50 - Device: OpenCLRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER0.5761.1521.7282.3042.882.530.711.241.420.781.471.761.511.011.552.191.571.692.562.220.791.742.10

cl-mem

OpenBenchmarking.orgGB/s Per Watt, More Is Bettercl-mem 2017-01-13Benchmark: WriteRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER0.83481.66962.50443.33924.1743.461.071.541.611.032.332.021.641.442.242.741.763.713.132.851.482.612.60

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: OpenCLRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER140280420560700SE +/- 0.63, N = 3SE +/- 0.06, N = 3SE +/- 0.15, N = 3SE +/- 0.16, N = 3SE +/- 0.02, N = 3SE +/- 0.47, N = 3SE +/- 0.72, N = 3SE +/- 0.32, N = 3SE +/- 0.07, N = 3SE +/- 0.39, N = 3SE +/- 0.25, N = 3SE +/- 0.09, N = 3SE +/- 0.27, N = 3SE +/- 0.75, N = 3SE +/- 0.61, N = 3SE +/- 0.58, N = 3SE +/- 0.53, N = 3SE +/- 0.19, N = 3634.09181.87276.89228.14203.91259.43496.24337.47196.00319.25441.24294.36376.73648.36468.70247.47374.71421.58

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 ScoreRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER70140210280350309.0495.60132.86118.49109.70132.28212.04147.9891.44164.52222.88141.35206.88322.76233.56142.20205.23220.76

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: OpenCLRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER6001200180024003000SE +/- 13.82, N = 3SE +/- 1.43, N = 3SE +/- 4.57, N = 3SE +/- 1.34, N = 3SE +/- 2.37, N = 3SE +/- 2.77, N = 3SE +/- 7.35, N = 3SE +/- 4.27, N = 3SE +/- 2.37, N = 3SE +/- 3.62, N = 3SE +/- 4.68, N = 3SE +/- 0.80, N = 3SE +/- 5.21, N = 3SE +/- 4.02, N = 3SE +/- 6.75, N = 3SE +/- 1.24, N = 3SE +/- 10.89, N = 3SE +/- 4.73, N = 32750.57841.481288.941160.52973.391394.052162.581544.50908.431694.072292.381371.211969.502842.382437.481202.771983.822264.97

cl-mem

OpenBenchmarking.orgGB/s Per Watt, More Is Bettercl-mem 2017-01-13Benchmark: CopyRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER0.72681.45362.18042.90723.6343.230.961.351.581.041.961.621.651.252.662.281.532.442.172.831.452.432.82

PlaidML

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: NASNer Large - Device: OpenCLRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER0.08330.16660.24990.33320.41650.370.110.180.210.120.220.240.200.150.230.290.230.260.370.320.130.250.30

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: VGG16 - Device: OpenCLRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER0.23180.46360.69540.92721.1590.980.310.560.580.320.560.750.610.420.620.820.670.681.030.820.320.710.81

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: DenseNet 201 - Device: OpenCLRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER60120180240300SE +/- 0.10, N = 3SE +/- 0.01, N = 3SE +/- 0.05, N = 3SE +/- 0.10, N = 3SE +/- 0.12, N = 3SE +/- 0.03, N = 3SE +/- 0.03, N = 3SE +/- 0.01, N = 3SE +/- 0.15, N = 3SE +/- 0.05, N = 3SE +/- 0.17, N = 3SE +/- 0.01, N = 3SE +/- 0.22, N = 3SE +/- 0.18, N = 3SE +/- 0.07, N = 3SE +/- 0.18, N = 3SE +/- 0.03, N = 3SE +/- 0.14, N = 3254.4579.71127.02102.8392.92114.58191.31143.5391.07154.19189.28130.15176.49263.13200.38111.46179.51190.01

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 2.3.2RTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER70140210280350SE +/- 0.90, N = 3SE +/- 0.03, N = 3SE +/- 0.43, N = 3SE +/- 0.27, N = 3SE +/- 0.08, N = 3SE +/- 0.15, N = 3SE +/- 0.43, N = 3SE +/- 0.53, N = 3SE +/- 0.17, N = 3SE +/- 0.61, N = 3SE +/- 0.99, N = 3SE +/- 0.05, N = 3SE +/- 0.64, N = 3SE +/- 0.71, N = 3SE +/- 0.78, N = 3SE +/- 0.04, N = 3SE +/- 0.34, N = 3SE +/- 0.60, N = 3301.8991.53140.29126.64102.86139.81198.25155.22102.61183.41242.75138.21204.71301.93256.83116.02205.20229.12

PlaidML

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: VGG19 - Device: OpenCLRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER0.16880.33760.50640.67520.8440.740.240.430.420.260.440.560.480.320.460.560.500.530.750.640.250.520.61

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 FilterRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER3691215SE +/- 0.02, N = 3SE +/- 0.02, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.07, N = 3SE +/- 0.02, N = 3SE +/- 0.02, N = 3SE +/- 0.01, N = 3SE +/- 0.02, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.07, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.04, N = 3SE +/- 0.00, N = 3SE +/- 0.07, N = 34.3912.998.2611.8711.6910.824.966.4911.938.906.227.887.754.245.749.957.876.821. (CXX) g++ options: -O2 -lOpenCL

PlaidML

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: DenseNet 201 - Device: OpenCLRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER0.34430.68861.03291.37721.72151.470.540.940.960.590.990.940.950.721.151.291.011.271.521.410.581.261.53

clpeak

OpenBenchmarking.orgGFLOPS Per Watt, More Is BetterclpeakOpenCL Test: Double-Precision DoubleRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER0.60751.2151.82252.433.03752.650.981.901.731.091.722.492.201.461.842.252.141.952.702.501.091.852.25

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: OpenCLRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER0.99451.9892.98353.9784.9725SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 3SE +/- 0.01, 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 +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.02, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 31.644.422.893.353.922.922.292.723.652.221.902.931.931.641.823.271.951.93

SHOC Scalable HeterOgeneous Computing

OpenBenchmarking.orgGFLOPS Per Watt, More Is BetterSHOC Scalable HeterOgeneous Computing 2015-11-10Target: OpenCL - Benchmark: Max SP FlopsRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER2040608010076.6929.2950.3050.1731.4049.6366.2659.8740.0650.3663.9361.4357.1377.7273.2332.0556.3865.76

JuliaGPU

OpenBenchmarking.orgSamples/sec Per Watt, More Is BetterJuliaGPU 1.2pts1OpenCL Device: GPURTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER600K1200K1800K2400K3000K1910018.661275493.931809790.272790569.691325997.882880366.361682592.711906369.991658141.692469451.172691799.292260229.902271141.791923116.672379445.261099178.252670026.702632329.69

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: CopyRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER70140210280350SE +/- 0.40, N = 3SE +/- 0.03, N = 3SE +/- 0.06, N = 3SE +/- 0.03, N = 3SE +/- 0.00, N = 3SE +/- 0.15, N = 3SE +/- 0.25, N = 3SE +/- 0.03, N = 3SE +/- 0.06, N = 3SE +/- 0.12, N = 3SE +/- 0.15, N = 3SE +/- 0.00, N = 3SE +/- 0.24, N = 3SE +/- 0.67, N = 3SE +/- 0.13, N = 3SE +/- 0.17, N = 3SE +/- 0.31, N = 3SE +/- 0.17, N = 3324.40124.77182.00145.37143.40208.50283.20205.93137.20237.77289.20182.70284.43322.20301.23216.83287.80291.871. (CC) gcc options: -O2 -flto -lOpenCL

ViennaCL

OpenBenchmarking.orgGFLOPS Per Watt, More Is BetterViennaCL 1.4.2OpenCL LU FactorizationRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER0.3150.630.9451.261.5751.310.660.801.080.791.100.590.701.000.730.710.711.351.351.180.601.400.90

FAHBench

OpenBenchmarking.orgNs Per Day Per Watt, More Is BetterFAHBench 2.3.2RTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER0.32630.65260.97891.30521.63151.380.620.961.110.651.101.021.000.831.211.381.101.291.331.450.621.271.42

LuxMark

OpenBenchmarking.orgScore Per Watt, More Is BetterLuxMark 3.1OpenCL Device: GPU - Scene: Luxball HDRRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER306090120150131.6665.0795.03108.7067.87102.7588.2676.5583.34112.43119.09111.54130.30137.34130.9270.64131.33136.85

OpenBenchmarking.orgScore Per Watt, More Is BetterLuxMark 3.1OpenCL Device: GPU - Scene: MicrophoneRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER2040608010089.7744.9158.6371.2246.0870.3357.6850.2951.1472.1182.6070.3283.9291.0089.5847.2583.0992.78

OpenBenchmarking.orgScore Per Watt, More Is BetterLuxMark 3.1OpenCL Device: GPU - Scene: HotelRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER61218243026.9913.7219.5924.2214.1622.5020.0218.5117.0022.9224.5025.6425.5227.4627.4115.2126.3827.18

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: OpenCLRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER7001400210028003500SE +/- 8.77, N = 3SE +/- 1.93, N = 15SE +/- 12.32, N = 15SE +/- 4.05, N = 15SE +/- 2.79, N = 3SE +/- 5.83, N = 15SE +/- 32.29, N = 3SE +/- 14.70, N = 3SE +/- 3.68, N = 4SE +/- 1.84, N = 3SE +/- 21.60, N = 3SE +/- 8.69, N = 6SE +/- 16.93, N = 15SE +/- 28.21, N = 3SE +/- 29.82, N = 3SE +/- 5.67, N = 15SE +/- 18.12, N = 15SE +/- 17.64, N = 73032.10207.84642.12335.86280.99420.041886.301146.75262.41704.691879.99753.69999.753126.482105.26466.84998.171604.211. (CXX) g++ options: -lpthread

clpeak

OpenBenchmarking.orgGIOPS Per Watt, More Is BetterclpeakOpenCL Test: Integer Compute INTRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER30609012015054.769.1923.8979.948.4461.3816.5226.8210.8363.25123.0725.5952.7866.5872.169.0080.7460.39

LeelaChessZero

OpenBenchmarking.orgNodes Per Second Per Watt, More Is BetterLeelaChessZero 0.22.0Backend: OpenCLRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER4812162014.001.264.212.841.833.138.757.101.904.7910.735.865.7815.8112.322.166.578.98

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 INTRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER3K6K9K12K15KSE +/- 57.62, N = 3SE +/- 19.67, N = 3SE +/- 24.36, N = 3SE +/- 32.97, N = 3SE +/- 0.38, N = 3SE +/- 64.34, N = 15SE +/- 29.87, N = 15SE +/- 26.46, N = 3SE +/- 13.36, N = 15SE +/- 63.11, N = 3SE +/- 4.11, N = 3SE +/- 0.72, N = 3SE +/- 84.78, N = 15SE +/- 156.59, N = 15SE +/- 83.79, N = 15SE +/- 23.09, N = 3SE +/- 76.65, N = 15SE +/- 81.60, N = 1513609.331140.291685.054657.791312.064775.453301.892430.741267.895269.019660.922076.937161.4813841.2510404.711610.287023.078570.601. (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 AtomsRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER0.08180.16360.24540.32720.409SE +/- 0.00238, N = 3SE +/- 0.00026, N = 4SE +/- 0.00195, N = 3SE +/- 0.00287, N = 3SE +/- 0.00159, N = 3SE +/- 0.00192, N = 3SE +/- 0.00044, N = 3SE +/- 0.00088, N = 5SE +/- 0.00303, N = 3SE +/- 0.00147, N = 4SE +/- 0.00199, N = 3SE +/- 0.00075, N = 6SE +/- 0.00250, N = 3SE +/- 0.00297, N = 3SE +/- 0.00233, N = 3SE +/- 0.00105, N = 3SE +/- 0.00245, N = 3SE +/- 0.00245, N = 30.189090.363680.239570.250310.331100.231850.196690.209780.317890.202500.193070.222690.194400.188670.193850.286750.193360.19501

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: GPURTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER60M120M180M240M300MSE +/- 78810.54, N = 3SE +/- 383961.59, N = 3SE +/- 76295.47, N = 3SE +/- 197521.26, N = 3SE +/- 52667.10, N = 3SE +/- 495295.96, N = 3SE +/- 540298.84, N = 3SE +/- 341457.11, N = 3SE +/- 137674.47, N = 3SE +/- 121354.48, N = 3SE +/- 169596.23, N = 3SE +/- 97519.45, N = 3SE +/- 633693.84, N = 3SE +/- 489061.14, N = 3SE +/- 1165562.77, N = 3SE +/- 78142.08, N = 3SE +/- 369711.60, N = 3SE +/- 389272.10, N = 3299834728.80169258044.90216942144.93230919642.13181882709.77239300837.60262248899.33237914974.40182188318.67251925176.90280162469.67220447755.87267086274.53303198573.97286818331.27195653728.47264172441.47275868151.171. (CC) gcc options: -O3 -march=native -ftree-vectorize -funroll-loops -lglut -lOpenCL -lGL -lm

OctaneBench

OpenBenchmarking.orgScore Per Watt, More Is BetterOctaneBench 4.00cTotal ScoreRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER0.24080.48160.72240.96321.2040.960.600.840.930.610.910.890.880.760.870.931.070.960.991.040.640.971.04

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 MyocyteRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER1224364860SE +/- 0.07, N = 3SE +/- 0.06, N = 3SE +/- 0.08, N = 3SE +/- 0.08, N = 3SE +/- 0.05, N = 3SE +/- 0.05, N = 3SE +/- 0.03, N = 3SE +/- 0.04, N = 3SE +/- 0.10, N = 3SE +/- 0.05, N = 3SE +/- 0.04, N = 3SE +/- 0.14, N = 3SE +/- 0.03, N = 3SE +/- 0.04, N = 3SE +/- 0.04, N = 3SE +/- 0.18, N = 3SE +/- 0.04, N = 3SE +/- 0.15, N = 331.0545.4835.1030.9747.3830.6735.9134.8734.6931.1131.6538.7031.6431.6930.6352.1330.4230.761. (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: OpenCLRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER1.30052.6013.90155.2026.5025SE +/- 0.01, N = 3SE +/- 0.03, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.02, N = 3SE +/- 0.00, N = 3SE +/- 0.01, 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 +/- 0.02, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.02, N = 33.665.783.924.015.744.023.923.944.073.733.713.973.673.663.694.123.683.71

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 FactorizationRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER1632486480SE +/- 0.72, N = 3SE +/- 0.11, N = 3SE +/- 0.03, N = 3SE +/- 0.02, N = 3SE +/- 0.04, N = 3SE +/- 0.05, N = 3SE +/- 0.31, N = 3SE +/- 0.20, N = 3SE +/- 0.05, N = 3SE +/- 0.21, N = 3SE +/- 0.07, N = 3SE +/- 0.01, N = 3SE +/- 0.03, N = 3SE +/- 0.60, N = 3SE +/- 0.26, N = 3SE +/- 0.02, N = 3SE +/- 0.06, N = 3SE +/- 0.05, N = 372.7156.9563.8665.1059.2166.0669.0966.6758.6767.9270.9664.6869.4172.9671.4762.0169.1770.451. (CXX) g++ options: -rdynamic -lOpenCL

System Power Consumption Monitor

OpenBenchmarking.orgWattsSystem Power Consumption MonitorPhoronix Test Suite System MonitoringRTX 2080 TiGTX 970GTX 1070GTX 1660GTX 980GTX 1660 TiGTX 1080 TiGTX 1080GTX 1060RTX 2060RTX 2080GTX 1070 TiRTX 2070TITAN RTXRTX 2080 SUPERGTX 980 TiRTX 2060 SUPERRTX 2070 SUPER70140210280350Min: 49.7 / Avg: 227.4 / Max: 374Min: 48.8 / Avg: 157.71 / Max: 306.3Min: 43.8 / Avg: 150.54 / Max: 286.9Min: 43.1 / Avg: 115.15 / Max: 262.4Min: 49.8 / Avg: 167.77 / Max: 329.4Min: 45.4 / Avg: 127.55 / Max: 273.9Min: 49.6 / Avg: 207.86 / Max: 380Min: 44.9 / Avg: 162.99 / Max: 328.3Min: 44.3 / Avg: 128.45 / Max: 269.5Min: 46.1 / Avg: 153.75 / Max: 303.8Min: 47.5 / Avg: 181.54 / Max: 342.9Min: 48.6 / Avg: 131.89 / Max: 259.9Min: 46 / Avg: 164.53 / Max: 321.3Min: 50.6 / Avg: 227.86 / Max: 371.4Min: 46 / Avg: 173.42 / Max: 330.5Min: 53.6 / Avg: 199.07 / Max: 370.3Min: 45.4 / Avg: 158.95 / Max: 312Min: 45.5 / Avg: 134.05 / Max: 323.3

GPU Temperature Monitor

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