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 HashRTX 2070 SUPERGTX 980 TiRTX 2080 SUPERTITAN RTXRTX 2070RTX 2080RTX 2060GTX 1060GTX 1080GTX 1660 TiGTX 980GTX 1660GTX 9700.08330.16660.24990.33320.41650.300.040.320.370.150.210.120.110.150.260.080.260.05

NAMD CUDA

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

SHOC Scalable HeterOgeneous Computing

OpenBenchmarking.orgWatts, Fewer Is BetterSHOC Scalable HeterOgeneous Computing 2015-11-10System Power Consumption MonitorRTX 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 Ti70140210280350Min: 47.1 / Avg: 150.09 / Max: 265.5Min: 46.8 / Avg: 148.63 / Max: 238Min: 126.9 / Avg: 193.91 / Max: 298.6Min: 47 / Avg: 164.08 / Max: 318.6Min: 52 / Avg: 223.03 / Max: 367Min: 47.9 / Avg: 149.29 / Max: 251.7Min: 50.5 / Avg: 125.61 / Max: 179.8Min: 48.7 / Avg: 171.33 / Max: 292.2Min: 47 / Avg: 145.37 / Max: 229.5Min: 74.8 / Avg: 119.53 / Max: 184.8Min: 94 / Avg: 157.13 / Max: 259.6Min: 49.6 / Avg: 199.67 / Max: 326.6Min: 46.4 / Avg: 118.75 / Max: 170.7Min: 97.6 / Avg: 160.93 / Max: 243.5Min: 44.5 / Avg: 106.24 / Max: 161Min: 78 / Avg: 141.46 / Max: 206.4Min: 80.6 / Avg: 148.92 / Max: 222.7Min: 51.3 / Avg: 217.17 / Max: 360

LeelaChessZero

OpenBenchmarking.orgWatts, Fewer Is BetterLeelaChessZero 0.22.0System Power Consumption MonitorRTX 2070 SUPERRTX 2060 SUPERGTX 980 TiRTX 2080 SUPERTITAN RTXRTX 2070GTX 1070 TiRTX 2080RTX 2060GTX 1060GTX 1080GTX 1080 TiGTX 1660 TiGTX 980GTX 1660GTX 1070GTX 97070140210280350Min: 47.2 / Avg: 178.69 / Max: 276Min: 45.5 / Avg: 151.83 / Max: 241.9Min: 59.1 / Avg: 216.14 / Max: 319.4Min: 47.5 / Avg: 170.9 / Max: 315Min: 53.3 / Avg: 197.7 / Max: 371.4Min: 48.6 / Avg: 172.95 / Max: 253.7Min: 52 / Avg: 128.59 / Max: 197.7Min: 52.8 / Avg: 175.13 / Max: 286.6Min: 49.1 / Avg: 147.07 / Max: 231.4Min: 47.2 / Avg: 138.37 / Max: 187.2Min: 48.8 / Avg: 161.47 / Max: 252.9Min: 106.6 / Avg: 215.46 / Max: 320.5Min: 47.9 / Avg: 134.26 / Max: 195.9Min: 51.8 / Avg: 153.94 / Max: 247.5Min: 46.5 / Avg: 118.46 / Max: 180.4Min: 71.9 / Avg: 152.4 / Max: 214.7Min: 82.3 / Avg: 164.63 / Max: 252.9

LuxMark

OpenBenchmarking.orgWatts, Fewer Is BetterLuxMark 3.1System Power Consumption MonitorRTX 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 Ti70140210280350Min: 47.6 / Avg: 241.53 / Max: 254.1Min: 47.9 / Avg: 233.07 / Max: 242.2Min: 57.2 / Avg: 255.39 / Max: 271.7Min: 50.8 / Avg: 249.5 / Max: 264.2Min: 57.7 / Avg: 358.16 / Max: 371Min: 51.8 / Avg: 241 / Max: 251.5Min: 51.1 / Avg: 162.66 / Max: 167.9Min: 52.6 / Avg: 269.03 / Max: 281.5Min: 50.4 / Avg: 210.86 / Max: 220.4Min: 45.7 / Avg: 155.74 / Max: 161.6Min: 47.9 / Avg: 205.71 / Max: 214.4Min: 55.9 / Avg: 282.16 / Max: 295.6Min: 47.2 / Avg: 169.1 / Max: 176.4Min: 51.4 / Avg: 215.19 / Max: 226.6Min: 46.7 / Avg: 154.16 / Max: 157.9Min: 48.8 / Avg: 197.56 / Max: 206Min: 50.9 / Avg: 198.98 / Max: 206.3Min: 54.2 / Avg: 341.41 / Max: 361

PlaidML

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorRTX 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 Ti60120180240300Min: 47.5 / Avg: 199.98 / Max: 276.8Min: 55 / Avg: 193.52 / Max: 240.6Min: 119.7 / Avg: 273.57 / Max: 330.8Min: 49.5 / Avg: 224.18 / Max: 302.6Min: 53.2 / Avg: 260.22 / Max: 361.7Min: 49.7 / Avg: 197.21 / Max: 252.5Min: 52.4 / Avg: 180.41 / Max: 207.7Min: 49.9 / Avg: 230.45 / Max: 288.2Min: 50.1 / Avg: 192.21 / Max: 230.7Min: 45.1 / Avg: 170.04 / Max: 188.8Min: 89.9 / Avg: 209.47 / Max: 253.5Min: 55.7 / Avg: 245.95 / Max: 321.1Min: 48.3 / Avg: 167.7 / Max: 196.3Min: 55.7 / Avg: 208.34 / Max: 246.7Min: 46 / Avg: 160.67 / Max: 185.8Min: 84.2 / Avg: 180.68 / Max: 209.8Min: 75.4 / Avg: 201.26 / Max: 220.7Min: 52.9 / Avg: 251.39 / Max: 354

OctaneBench

OpenBenchmarking.orgWatts, Fewer Is BetterOctaneBench 4.00cSystem Power Consumption MonitorRTX 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 Ti60120180240300Min: 49 / Avg: 211.57 / Max: 245.6Min: 46.5 / Avg: 210.53 / Max: 232.6Min: 128.3 / Avg: 220.62 / Max: 240Min: 47.8 / Avg: 225.1 / Max: 261.8Min: 55.3 / Avg: 326.69 / Max: 357.7Min: 47.1 / Avg: 215.17 / Max: 242.1Min: 52.2 / Avg: 132.45 / Max: 182.7Min: 50 / Avg: 239.21 / Max: 278.1Min: 49.8 / Avg: 188.5 / Max: 218.2Min: 44.9 / Avg: 120.33 / Max: 135.2Min: 48.3 / Avg: 167.77 / Max: 228.3Min: 130.6 / Avg: 236.94 / Max: 265Min: 47.1 / Avg: 145.79 / Max: 161.1Min: 53.6 / Avg: 178.66 / Max: 203.2Min: 46.3 / Avg: 127.11 / Max: 144.7Min: 86 / Avg: 157.88 / Max: 173.8Min: 50.8 / Avg: 160.22 / Max: 180Min: 51.7 / Avg: 322.94 / Max: 355.5

PlaidML

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorRTX 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 Ti60120180240300Min: 47.2 / Avg: 191.71 / Max: 276.3Min: 53.3 / Avg: 181.51 / Max: 239.5Min: 56.5 / Avg: 270.73 / Max: 328.7Min: 47.7 / Avg: 218.91 / Max: 299.1Min: 52.4 / Avg: 239.94 / Max: 363Min: 48.4 / Avg: 193.79 / Max: 250.6Min: 52.3 / Avg: 169.99 / Max: 205.7Min: 48.9 / Avg: 201.23 / Max: 285.7Min: 48.4 / Avg: 179.22 / Max: 228.5Min: 69.4 / Avg: 166.46 / Max: 190Min: 46.2 / Avg: 209.24 / Max: 254.3Min: 51.8 / Avg: 234.29 / Max: 318.4Min: 46.4 / Avg: 163.81 / Max: 195.7Min: 90.4 / Avg: 213.83 / Max: 251.4Min: 45.6 / Avg: 146.27 / Max: 182Min: 50 / Avg: 172.78 / Max: 208.8Min: 94.5 / Avg: 195.88 / Max: 219.3Min: 52.7 / Avg: 239.16 / Max: 354.3

clpeak

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

LuxMark

OpenBenchmarking.orgWatts, Fewer Is BetterLuxMark 3.1System Power Consumption MonitorRTX 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 Ti60120180240300Min: 47.5 / Avg: 217.27 / Max: 227.7Min: 47.2 / Avg: 229.14 / Max: 241Min: 130.4 / Avg: 238.82 / Max: 247.5Min: 49.4 / Avg: 230.52 / Max: 238Min: 53.7 / Avg: 338.9 / Max: 360.6Min: 50.1 / Avg: 230.98 / Max: 243.5Min: 52.3 / Avg: 151.74 / Max: 155.9Min: 52.5 / Avg: 244.9 / Max: 255.3Min: 47.4 / Avg: 192.86 / Max: 200.8Min: 76 / Avg: 146.92 / Max: 152Min: 75.8 / Avg: 180.11 / Max: 185.5Min: 107.7 / Avg: 245.73 / Max: 254Min: 48.2 / Avg: 157.16 / Max: 163.8Min: 87.7 / Avg: 195.16 / Max: 205Min: 45.9 / Avg: 139.49 / Max: 144Min: 48.6 / Avg: 181.94 / Max: 188.2Min: 52.2 / Avg: 180.29 / Max: 185.6Min: 53.9 / Avg: 326.39 / Max: 340.7

PlaidML

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorRTX 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 Ti60120180240300Min: 47.2 / Avg: 198.27 / Max: 271.7Min: 57.1 / Avg: 209.61 / Max: 237.5Min: 71.2 / Avg: 244.52 / Max: 316.6Min: 49.1 / Avg: 194.92 / Max: 278.5Min: 52.8 / Avg: 227.24 / Max: 356.3Min: 48.7 / Avg: 189.06 / Max: 250.5Min: 51.9 / Avg: 158.16 / Max: 196.1Min: 52.6 / Avg: 181.66 / Max: 277.7Min: 48.9 / Avg: 179.62 / Max: 228Min: 45.9 / Avg: 157.15 / Max: 187.3Min: 91.2 / Avg: 194.23 / Max: 252.2Min: 120.6 / Avg: 236.48 / Max: 318.6Min: 48.2 / Avg: 154.23 / Max: 191.6Min: 53.3 / Avg: 201.25 / Max: 246.9Min: 45.5 / Avg: 136.67 / Max: 171.6Min: 70.7 / Avg: 170.23 / Max: 208.9Min: 89.6 / Avg: 193.7 / Max: 220.3Min: 52.9 / Avg: 210.77 / Max: 350.6

LuxMark

OpenBenchmarking.orgWatts, Fewer Is BetterLuxMark 3.1System Power Consumption MonitorRTX 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 Ti60120180240300Min: 47.6 / Avg: 220.93 / Max: 232.4Min: 49.8 / Avg: 222.76 / Max: 232.3Min: 112.5 / Avg: 234.81 / Max: 244.3Min: 47.8 / Avg: 225.09 / Max: 235.4Min: 60.2 / Avg: 337.98 / Max: 356.9Min: 51.5 / Avg: 219.74 / Max: 234.1Min: 50.1 / Avg: 145.89 / Max: 150.4Min: 53.8 / Avg: 241.11 / Max: 251.4Min: 48.6 / Avg: 190.73 / Max: 198.4Min: 45.6 / Avg: 138.57 / Max: 144.8Min: 49.1 / Avg: 173.32 / Max: 180.3Min: 52.7 / Avg: 237.89 / Max: 245.4Min: 48 / Avg: 156.46 / Max: 161.4Min: 51 / Avg: 193.46 / Max: 203.7Min: 46 / Avg: 137.52 / Max: 142.7Min: 49 / Avg: 170.27 / Max: 177.6Min: 51.9 / Avg: 177.8 / Max: 184.4Min: 55.9 / Avg: 318.95 / Max: 337.2

PlaidML

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorRTX 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 Ti60120180240300Min: 46.7 / Avg: 187.65 / Max: 267.6Min: 54 / Avg: 187.95 / Max: 233.7Min: 55.1 / Avg: 244.29 / Max: 316.2Min: 49.4 / Avg: 181.31 / Max: 274.6Min: 53.8 / Avg: 216.91 / Max: 353.5Min: 48.1 / Avg: 174.02 / Max: 249.3Min: 95.2 / Avg: 160.1 / Max: 191.4Min: 54.1 / Avg: 173.35 / Max: 273.1Min: 48.1 / Avg: 163.79 / Max: 226.4Min: 45.8 / Avg: 152.31 / Max: 187.6Min: 88.2 / Avg: 189.28 / Max: 251.8Min: 118 / Avg: 235.58 / Max: 316.5Min: 47.3 / Avg: 151.58 / Max: 191.5Min: 69.1 / Avg: 196.2 / Max: 247.2Min: 45.6 / Avg: 137.8 / Max: 169.2Min: 47.7 / Avg: 162.2 / Max: 207.3Min: 51.5 / Avg: 184.27 / Max: 233.4Min: 52.7 / Avg: 188.04 / Max: 345.4

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorRTX 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 Ti60120180240300Min: 46.5 / Avg: 184.51 / Max: 249.7Min: 54.2 / Avg: 192.58 / Max: 235.4Min: 124.3 / Avg: 237.03 / Max: 284.6Min: 46.7 / Avg: 204.84 / Max: 277Min: 51.3 / Avg: 235.38 / Max: 341.7Min: 48 / Avg: 190.9 / Max: 247Min: 51.4 / Avg: 151.49 / Max: 175.5Min: 49.7 / Avg: 201.32 / Max: 272.7Min: 48.1 / Avg: 176.3 / Max: 224.1Min: 75.4 / Avg: 157.49 / Max: 178.6Min: 48.2 / Avg: 203.49 / Max: 246Min: 107 / Avg: 238.78 / Max: 315.7Min: 46.5 / Avg: 154.44 / Max: 184.5Min: 99.4 / Avg: 199.9 / Max: 241.3Min: 44.8 / Avg: 135.27 / Max: 159.9Min: 83.7 / Avg: 182.29 / Max: 211.2Min: 94.8 / Avg: 192.64 / Max: 216.8Min: 50.4 / Avg: 231.53 / Max: 336

FAHBench

OpenBenchmarking.orgWatts, Fewer Is BetterFAHBench 2.3.2System Power Consumption MonitorRTX 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 Ti60120180240300Min: 46.6 / Avg: 161.4 / Max: 230Min: 48.5 / Avg: 161.35 / Max: 226.3Min: 56.3 / Avg: 186.17 / Max: 244.4Min: 64 / Avg: 177.55 / Max: 252.2Min: 52.5 / Avg: 226.18 / Max: 324.2Min: 46 / Avg: 158.7 / Max: 226.7Min: 49.1 / Avg: 125.16 / Max: 155Min: 47.5 / Avg: 176.01 / Max: 263Min: 45.7 / Avg: 151.46 / Max: 214.2Min: 66.3 / Avg: 124.04 / Max: 159.6Min: 44.9 / Avg: 154.62 / Max: 208.2Min: 77.6 / Avg: 195.24 / Max: 264.4Min: 47.6 / Avg: 127.19 / Max: 170.3Min: 49.8 / Avg: 159.19 / Max: 211.9Min: 46.5 / Avg: 114.3 / Max: 152.8Min: 43.8 / Avg: 145.58 / Max: 193.2Min: 48.8 / Avg: 147.69 / Max: 193Min: 49.7 / Avg: 218.05 / Max: 323.3

PlaidML

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorRTX 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 Ti60120180240300Min: 49.5 / Avg: 161.34 / Max: 234.9Min: 54.4 / Avg: 162.79 / Max: 223.8Min: 126.5 / Avg: 220.09 / Max: 281.6Min: 49.6 / Avg: 170.73 / Max: 255.1Min: 56.2 / Avg: 178.56 / Max: 327.6Min: 49.8 / Avg: 167.7 / Max: 230.4Min: 51.1 / Avg: 141.76 / Max: 172.5Min: 49.4 / Avg: 176.08 / Max: 254.9Min: 47.6 / Avg: 150.66 / Max: 214.3Min: 46.9 / Avg: 150.12 / Max: 180Min: 84.7 / Avg: 196.13 / Max: 242.5Min: 128 / Avg: 191.53 / Max: 304Min: 46.3 / Avg: 136.65 / Max: 177.5Min: 56.7 / Avg: 188.31 / Max: 242.7Min: 46.3 / Avg: 123.06 / Max: 152.7Min: 84.3 / Avg: 149.15 / Max: 206.1Min: 81.4 / Avg: 182.54 / Max: 219.9Min: 51.8 / Avg: 206.66 / Max: 321.6

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorRTX 2070 SUPERRTX 2060 SUPERGTX 980 TiRTX 2080 SUPERTITAN RTXRTX 2070GTX 1070 TiRTX 2080RTX 2060GTX 1060GTX 1080GTX 1080 TiGTX 1660 TiGTX 980GTX 1660GTX 1070GTX 97060120180240300Min: 46.8 / Avg: 145.98 / Max: 249.6Min: 55.4 / Avg: 144.71 / Max: 231.4Min: 129.1 / Avg: 233.7 / Max: 292Min: 49.4 / Avg: 162.94 / Max: 270.3Min: 52.7 / Avg: 128.84 / Max: 167.9Min: 47.5 / Avg: 122.1 / Max: 239.9Min: 52.2 / Avg: 140.17 / Max: 177.3Min: 52 / Avg: 137.63 / Max: 231.8Min: 48.6 / Avg: 147.64 / Max: 221.8Min: 45.9 / Avg: 132.6 / Max: 182.3Min: 48.4 / Avg: 149.71 / Max: 246.6Min: 56.4 / Avg: 186.43 / Max: 312.7Min: 47.9 / Avg: 141.14 / Max: 182.8Min: 53 / Avg: 176.69 / Max: 244.6Min: 46.3 / Avg: 119.8 / Max: 159.7Min: 89.6 / Avg: 153.55 / Max: 208.4Min: 83.3 / Avg: 172.91 / Max: 233.2

clpeak

OpenBenchmarking.orgWatts, Fewer Is BetterclpeakSystem Power Consumption MonitorRTX 2070 SUPERRTX 2060 SUPERGTX 980 TiTITAN RTXRTX 2070GTX 1660 TiGTX 980GTX 97060120180240300Min: 47.5 / Avg: 69.91 / Max: 138.9Min: 46.6 / Avg: 63.45 / Max: 103Min: 54.9 / Avg: 131.87 / Max: 194.2Min: 50.6 / Avg: 137.09 / Max: 308.7Min: 48.2 / Avg: 96.86 / Max: 180.2Min: 45.5 / Avg: 67.18 / Max: 127.1Min: 52.5 / Avg: 122.69 / Max: 181.1Min: 51.4 / Avg: 98.78 / Max: 148.8

PlaidML

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorRTX 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 Ti50100150200250Min: 47.9 / Avg: 135.09 / Max: 211.7Min: 54.4 / Avg: 144.26 / Max: 207.2Min: 127.5 / Avg: 205.03 / Max: 260.5Min: 48.5 / Avg: 147.96 / Max: 225.2Min: 55.6 / Avg: 169.21 / Max: 293Min: 49 / Avg: 148.17 / Max: 210.6Min: 51.5 / Avg: 131.42 / Max: 162.8Min: 50.7 / Avg: 139.72 / Max: 234.8Min: 47.9 / Avg: 142.09 / Max: 199.4Min: 68.7 / Avg: 129.36 / Max: 164Min: 94.6 / Avg: 159.56 / Max: 227.4Min: 55.7 / Avg: 189.84 / Max: 284.9Min: 47.3 / Avg: 117.8 / Max: 162Min: 52.8 / Avg: 183.08 / Max: 228.8Min: 44.8 / Avg: 109.89 / Max: 143.5Min: 77.9 / Avg: 157.58 / Max: 202.6Min: 81.7 / Avg: 163.48 / Max: 201.2Min: 51.5 / Avg: 167.74 / Max: 291.7

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorRTX 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 Ti50100150200250Min: 46.6 / Avg: 139.53 / Max: 205.1Min: 53 / Avg: 147.84 / Max: 203.6Min: 128.3 / Avg: 193.81 / Max: 239.9Min: 48.4 / Avg: 151.02 / Max: 226.9Min: 51.1 / Avg: 182.86 / Max: 282.6Min: 47.6 / Avg: 141.04 / Max: 207.9Min: 51 / Avg: 131.33 / Max: 154.1Min: 49 / Avg: 153.24 / Max: 230.1Min: 48.8 / Avg: 144.1 / Max: 197.4Min: 55.5 / Avg: 124.66 / Max: 155.7Min: 84.5 / Avg: 158.48 / Max: 204.6Min: 125.6 / Avg: 201.87 / Max: 257Min: 46.7 / Avg: 122.59 / Max: 164Min: 99.3 / Avg: 168.06 / Max: 211.7Min: 44.4 / Avg: 112.99 / Max: 143Min: 70.5 / Avg: 148.83 / Max: 185.2Min: 72.9 / Avg: 158.81 / Max: 190.7Min: 50.7 / Avg: 178.03 / Max: 280

clpeak

OpenBenchmarking.orgGFLOPS Per Watt, More Is BetterclpeakOpenCL Test: Single-Precision FloatRTX 2070 SUPERRTX 2060 SUPERGTX 980 TiRTX 2080 SUPERTITAN RTXRTX 2070GTX 1070 TiRTX 2080RTX 2060GTX 1080GTX 1660 TiGTX 980GTX 1070GTX 970RTX 2080 Ti50100150200250121.62111.7442.0084.49103.6174.3284.4679.25109.2089.1171.3536.4970.6339.36222.09

PlaidML

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorRTX 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 Ti50100150200250Min: 49.1 / Avg: 124.58 / Max: 203.3Min: 55.8 / Avg: 142.16 / Max: 204.9Min: 57 / Avg: 191.08 / Max: 247.4Min: 48.8 / Avg: 141.86 / Max: 214.3Min: 52.7 / Avg: 173.29 / Max: 277.5Min: 51.5 / Avg: 138.71 / Max: 203.8Min: 53.5 / Avg: 128.35 / Max: 157.6Min: 51.5 / Avg: 146.49 / Max: 216.5Min: 49 / Avg: 134.34 / Max: 190.3Min: 45.7 / Avg: 125.77 / Max: 157.6Min: 49.1 / Avg: 151.63 / Max: 200.9Min: 109.8 / Avg: 203.83 / Max: 255.3Min: 48.2 / Avg: 115.16 / Max: 152Min: 53.5 / Avg: 157.67 / Max: 213.1Min: 45.8 / Avg: 106.92 / Max: 138.1Min: 48.3 / Avg: 135.38 / Max: 188.6Min: 52.1 / Avg: 148.78 / Max: 190.2Min: 52.4 / Avg: 173.16 / Max: 273

clpeak

OpenBenchmarking.orgGBPS Per Watt, More Is BetterclpeakOpenCL Test: Global Memory BandwidthRTX 2070 SUPERRTX 2060 SUPERGTX 980 TiRTX 2080 SUPERTITAN RTXRTX 2070GTX 1070 TiRTX 2080GTX 1060GTX 1080GTX 1080 TiGTX 1660 TiGTX 980GTX 1660GTX 1070GTX 970RTX 2080 Ti36912155.414.882.024.866.183.331.925.091.842.262.732.241.653.162.631.529.15

PlaidML

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorRTX 2070 SUPERRTX 2060 SUPERGTX 980 TiRTX 2080 SUPERGTX 1070 TiRTX 2080RTX 2060GTX 1060GTX 1080GTX 1660 TiGTX 980GTX 1660GTX 1070GTX 970RTX 2080 Ti50100150200250Min: 49.2 / Avg: 136.18 / Max: 192.6Min: 54.9 / Avg: 136.39 / Max: 187.2Min: 57.1 / Avg: 192.1 / Max: 249.1Min: 51.8 / Avg: 130.6 / Max: 207.8Min: 52.4 / Avg: 128.8 / Max: 152Min: 56.5 / Avg: 138.96 / Max: 215.1Min: 49.2 / Avg: 125.65 / Max: 186.5Min: 46.3 / Avg: 122.88 / Max: 159.6Min: 48.5 / Avg: 142.23 / Max: 208.8Min: 46.6 / Avg: 100.43 / Max: 150.5Min: 100 / Avg: 162.49 / Max: 218.7Min: 46.3 / Avg: 96.5 / Max: 135.8Min: 50.4 / Avg: 132.86 / Max: 187.3Min: 94.4 / Avg: 160.18 / Max: 203.4Min: 52.6 / Avg: 166.27 / Max: 275.3

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.orgGHash/s, More Is BetterSHOC Scalable HeterOgeneous Computing 2015-11-10Target: OpenCL - Benchmark: MD5 HashRTX 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 Ti816243240SE +/- 0.05, N = 3SE +/- 0.02, N = 3SE +/- 0.00, N = 3SE +/- 0.02, N = 3SE +/- 0.06, N = 3SE +/- 0.03, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.03, N = 3SE +/- 0.00, N = 3SE +/- 0.02, N = 3SE +/- 0.04, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.02, N = 3SE +/- 0.00, N = 3SE +/- 0.12, N = 321.7818.229.2226.5636.3918.7711.7024.0716.047.2614.2519.7212.987.4911.8710.616.5034.911. (CXX) g++ options: -O2 -lSHOCCommonMPI -lSHOCCommonOpenCL -lSHOCCommon -lOpenCL -lrt -pthread -lmpi_cxx -lmpi

Rodinia

OpenBenchmarking.orgWatts, Fewer Is BetterRodinia 2.4System Power Consumption MonitorRTX 2070 SUPERGTX 980 TiGTX 1070 TiRTX 2060GTX 1060GTX 1660 TiGTX 980GTX 1660GTX 9704080120160200Min: 47 / Avg: 103.36 / Max: 166Min: 54.7 / Avg: 167.04 / Max: 233.5Min: 50.3 / Avg: 101.74 / Max: 149.4Min: 47.6 / Avg: 121.91 / Max: 156.6Min: 44.7 / Avg: 111.27 / Max: 154.1Min: 46 / Avg: 107.04 / Max: 129.7Min: 52.6 / Avg: 156.47 / Max: 203.2Min: 45.1 / Avg: 88.85 / Max: 116.6Min: 50.5 / Avg: 141.83 / Max: 190

clpeak

OpenBenchmarking.orgWatts, Fewer Is BetterclpeakSystem Power Consumption MonitorRTX 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 Ti4080120160200Min: 47 / Avg: 137.66 / Max: 150.3Min: 47.1 / Avg: 142.14 / Max: 150.8Min: 128.4 / Avg: 179.97 / Max: 191.4Min: 47.6 / Avg: 151.43 / Max: 166.9Min: 51.5 / Avg: 203.24 / Max: 225.1Min: 46.9 / Avg: 137.5 / Max: 151.9Min: 51 / Avg: 113.26 / Max: 124.1Min: 49.8 / Avg: 153.89 / Max: 172.5Min: 47.9 / Avg: 126.06 / Max: 143Min: 44.7 / Avg: 102.22 / Max: 117.3Min: 46.2 / Avg: 135.52 / Max: 152.6Min: 51.6 / Avg: 166.5 / Max: 193Min: 46.4 / Avg: 107.92 / Max: 119.4Min: 51.6 / Avg: 146.12 / Max: 159.1Min: 43.9 / Avg: 97.25 / Max: 106.6Min: 46 / Avg: 117.77 / Max: 137.1Min: 93.6 / Avg: 140.29 / Max: 146.2Min: 50.3 / Avg: 197 / Max: 217.1

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 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 Ti30060090012001500SE +/- 0.27, N = 3SE +/- 3.09, N = 3SE +/- 3.01, N = 3SE +/- 0.78, N = 3SE +/- 1.38, N = 3SE +/- 2.90, N = 3SE +/- 0.19, N = 3SE +/- 0.39, N = 3SE +/- 0.56, N = 3SE +/- 3.50, N = 7SE +/- 3.58, N = 3SE +/- 1.06, N = 3SE +/- 1.57, N = 3SE +/- 1.09, N = 3SE +/- 0.27, N = 3SE +/- 6.42, N = 4SE +/- 0.48, N = 3SE +/- 2.79, N = 31088.17971.24725.981203.571578.29976.78525.891100.00818.44326.68614.69982.23665.66458.35452.89478.54411.291485.731. (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 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 Ti1.13182.26363.39544.52725.6592.892.591.063.185.033.092.103.212.161.482.252.661.841.151.901.801.053.70

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: Mobilenet - Device: OpenCLRTX 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 Ti61218243019.7012.986.6416.6023.2314.8411.3014.1611.677.599.3510.2211.205.539.569.655.2022.63

SHOC Scalable HeterOgeneous Computing

OpenBenchmarking.orgGFLOPS Per Watt, More Is BetterSHOC Scalable HeterOgeneous Computing 2015-11-10Target: OpenCL - Benchmark: FFT SPRTX 2070 SUPERRTX 2060 SUPERGTX 980 TiRTX 2070GTX 1070 TiRTX 2080RTX 2060GTX 1060GTX 1080GTX 1080 TiGTX 1660 TiGTX 980GTX 1660GTX 1070GTX 970RTX 2080 Ti4812162015.5817.596.928.676.3615.4613.234.007.877.9712.255.455.706.235.1211.54

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 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 Ti7K14K21K28K35KSE +/- 16.84, N = 3SE +/- 43.34, N = 3SE +/- 49.74, N = 3SE +/- 108.17, N = 3SE +/- 168.12, N = 3SE +/- 26.44, N = 3SE +/- 15.50, N = 3SE +/- 11.68, N = 3SE +/- 3.84, N = 3SE +/- 1.53, N = 3SE +/- 1.20, N = 3SE +/- 19.33, N = 3SE +/- 2.33, N = 3SE +/- 18.25, N = 3SE +/- 1.33, N = 3SE +/- 4.91, N = 3SE +/- 2.00, N = 3SE +/- 21.50, N = 3204991850911096201643075618441102591991613754708687161372111003891497949983798528631

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 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 Ti0.7111.4222.1332.8443.555SE +/- 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 = 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 +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 30.800.751.510.790.740.751.170.800.831.281.091.051.153.101.181.113.160.75

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 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 Ti80160240320400SE +/- 0.10, N = 3SE +/- 0.44, N = 3SE +/- 0.26, N = 3SE +/- 0.23, N = 3SE +/- 0.48, N = 3SE +/- 0.43, N = 3SE +/- 0.06, N = 3SE +/- 0.59, N = 3SE +/- 0.37, N = 3SE +/- 0.20, N = 3SE +/- 0.30, N = 3SE +/- 0.21, N = 3SE +/- 0.05, N = 3SE +/- 0.27, N = 3SE +/- 0.27, N = 3SE +/- 0.18, N = 3SE +/- 0.01, N = 3SE +/- 0.44, N = 3239.61219.76116.31301.11373.71220.99147.04268.33193.7597.83173.79228.68161.33101.92137.66141.5588.16363.16

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: VGG19 - Device: OpenCLRTX 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 Ti4080120160200SE +/- 0.16, N = 3SE +/- 0.23, N = 3SE +/- 0.77, N = 3SE +/- 0.21, N = 3SE +/- 0.48, N = 3SE +/- 0.35, N = 3SE +/- 0.03, N = 3SE +/- 0.44, N = 3SE +/- 0.19, N = 3SE +/- 0.12, N = 3SE +/- 0.28, N = 3SE +/- 0.44, N = 3SE +/- 0.12, N = 3SE +/- 0.62, N = 4SE +/- 0.08, N = 3SE +/- 0.19, N = 3SE +/- 0.18, N = 3SE +/- 0.36, N = 397.8280.8256.13115.44162.0583.5673.12105.5471.0744.3783.83115.0358.0343.6352.5263.5639.34154.20

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: VGG19 - Device: OpenCLRTX 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 Ti4080120160200SE +/- 0.23, N = 3SE +/- 0.19, N = 3SE +/- 0.65, N = 3SE +/- 0.22, N = 3SE +/- 0.54, N = 3SE +/- 0.25, N = 3SE +/- 0.06, N = 3SE +/- 0.42, N = 3SE +/- 0.17, N = 3SE +/- 0.08, N = 3SE +/- 0.16, N = 3SE +/- 0.35, N = 3SE +/- 0.12, N = 3SE +/- 0.47, N = 3SE +/- 0.17, N = 3SE +/- 0.11, N = 3SE +/- 0.01, N = 3SE +/- 0.41, N = 3122.32101.1768.47143.02196.44103.8990.34129.5888.0454.78101.00138.6873.3553.4967.2476.8947.70186.19

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: VGG16 - Device: OpenCLRTX 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 Ti4080120160200SE +/- 0.28, N = 3SE +/- 0.35, N = 3SE +/- 1.12, N = 3SE +/- 0.29, N = 3SE +/- 0.57, N = 3SE +/- 0.39, N = 3SE +/- 0.08, N = 3SE +/- 0.57, N = 3SE +/- 0.23, N = 3SE +/- 0.18, N = 3SE +/- 0.40, N = 3SE +/- 0.62, N = 3SE +/- 0.14, N = 3SE +/- 0.83, N = 4SE +/- 0.17, N = 3SE +/- 0.30, N = 3SE +/- 0.21, N = 3SE +/- 0.51, N = 3123.20102.5871.26145.65204.67105.6092.03133.2089.5556.07106.09145.4273.1855.7066.2480.2749.76194.83

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: VGG16 - Device: OpenCLRTX 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 Ti50100150200250SE +/- 0.29, N = 3SE +/- 0.34, N = 3SE +/- 1.36, N = 3SE +/- 0.28, N = 3SE +/- 0.40, N = 3SE +/- 0.43, N = 3SE +/- 0.06, N = 3SE +/- 0.73, N = 3SE +/- 0.32, N = 3SE +/- 0.12, N = 3SE +/- 0.38, N = 3SE +/- 0.62, N = 3SE +/- 0.24, N = 3SE +/- 0.79, N = 3SE +/- 0.21, N = 3SE +/- 0.17, N = 3SE +/- 0.05, N = 3SE +/- 0.50, N = 3154.64128.2287.39180.45247.83131.54114.03164.05110.9369.31128.05175.3792.4568.9584.8397.3260.32234.65

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: NASNer Large - Device: OpenCLRTX 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 Ti20406080100SE +/- 0.05, N = 3SE +/- 0.14, N = 3SE +/- 0.10, N = 3SE +/- 0.08, N = 3SE +/- 0.25, N = 3SE +/- 0.13, N = 3SE +/- 0.02, N = 3SE +/- 0.15, N = 3SE +/- 0.08, N = 3SE +/- 0.03, N = 3SE +/- 0.08, N = 3SE +/- 0.11, N = 3SE +/- 0.03, N = 3SE +/- 0.15, N = 3SE +/- 0.03, N = 3SE +/- 0.05, N = 3SE +/- 0.03, N = 3SE +/- 0.21, N = 355.2448.9630.6464.8087.1749.9435.4158.4741.1123.1640.3856.6434.1224.2428.9933.0721.4284.97

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 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 Ti120240360480600SE +/- 0.22, N = 3SE +/- 0.22, N = 3SE +/- 0.12, N = 3SE +/- 0.27, N = 3SE +/- 0.40, N = 3SE +/- 0.25, N = 3SE +/- 0.07, N = 3SE +/- 0.25, N = 3SE +/- 0.20, N = 3SE +/- 0.00, N = 3SE +/- 0.12, N = 3SE +/- 0.20, N = 3SE +/- 0.07, N = 3SE +/- 0.10, N = 3SE +/- 0.00, N = 3SE +/- 0.03, N = 3SE +/- 1.50, N = 8SE +/- 0.38, N = 3395.67395.67265.33436.27566.70395.70205.27395.70296.20153.50228.80337.53250.23164.50162.90205.27142.10544.331. (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 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 Ti120240360480600SE +/- 0.77, N = 3SE +/- 0.71, N = 3SE +/- 0.35, N = 3SE +/- 0.03, N = 3SE +/- 1.16, N = 3SE +/- 0.81, N = 3SE +/- 0.02, N = 3SE +/- 0.92, N = 3SE +/- 0.01, N = 3SE +/- 0.14, N = 3SE +/- 0.76, N = 3SE +/- 1.14, N = 3SE +/- 0.01, N = 3SE +/- 0.07, N = 3SE +/- 0.00, N = 3SE +/- 0.71, N = 3SE +/- 0.03, N = 3SE +/- 1.46, N = 3310.27263.11196.60378.98547.97268.32242.63345.81231.44149.58297.94414.96185.12159.68168.44223.91137.47521.901. (CXX) g++ options: -O3 -rdynamic -lOpenCL

PlaidML

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: IMDB LSTM - Device: OpenCLRTX 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 Ti1.14532.29063.43594.58125.72653.673.231.414.525.093.682.593.953.101.832.813.003.141.432.982.371.284.56

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 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 Ti4K8K12K16K20KSE +/- 51.02, N = 3SE +/- 27.40, N = 3SE +/- 11.70, N = 3SE +/- 61.30, N = 3SE +/- 91.95, N = 3SE +/- 45.97, N = 3SE +/- 0.84, N = 3SE +/- 29.32, N = 3SE +/- 19.13, N = 3SE +/- 6.34, N = 3SE +/- 3.00, N = 3SE +/- 3.93, N = 3SE +/- 0.04, N = 3SE +/- 3.92, N = 3SE +/- 13.79, N = 3SE +/- 1.89, N = 3SE +/- 0.74, N = 3SE +/- 87.95, N = 39869.348378.876213.9712015.5017334.008528.707715.4210952.777320.734788.929407.7513230.775893.415052.735329.847115.394362.3116656.201. (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 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 Ti10K20K30K40K50KSE +/- 98.93, N = 3SE +/- 4.93, N = 3SE +/- 39.15, N = 3SE +/- 0.88, N = 3SE +/- 20.92, N = 3SE +/- 7.54, N = 3SE +/- 36.50, N = 3SE +/- 7.51, N = 3SE +/- 0.67, N = 3SE +/- 4.00, N = 3SE +/- 17.98, N = 3SE +/- 7.67, N = 3SE +/- 19.86, N = 3SE +/- 26.16, N = 3SE +/- 35.04, N = 3SE +/- 1.00, N = 3SE +/- 6.23, N = 3SE +/- 166.33, N = 3297343009316871301794654630097169252916421683122451378821689161471324615162172901173242974

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 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 Ti2004006008001000SE +/- 0.67, N = 3SE +/- 0.31, N = 3SE +/- 0.56, N = 3SE +/- 1.47, N = 3SE +/- 2.25, N = 3SE +/- 0.21, N = 3SE +/- 0.49, N = 3SE +/- 1.63, N = 3SE +/- 0.37, N = 3SE +/- 0.17, N = 3SE +/- 0.31, N = 3SE +/- 0.74, N = 3SE +/- 0.15, N = 3SE +/- 0.50, N = 3SE +/- 0.01, N = 3SE +/- 0.13, N = 3SE +/- 0.03, N = 3SE +/- 1.01, N = 3499.69440.79270.00589.86790.77446.23333.03548.83389.40224.89399.00523.98315.83231.66287.68315.37204.32758.21

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: VGG16 - Device: OpenCLRTX 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 Ti0.2340.4680.7020.9361.170.660.550.290.800.940.610.570.770.550.370.560.620.480.280.480.490.271.04

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: Mobilenet - Device: OpenCLRTX 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 Ti61218243024.7520.687.6725.0622.1921.3514.1626.2118.209.5714.0215.2116.067.1714.7912.356.9826.71

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: Inception V3 - Device: OpenCLRTX 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 Ti0.43880.87761.31641.75522.1941.341.230.611.521.951.181.081.361.110.700.941.341.020.560.950.990.521.66

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: ResNet 50 - Device: OpenCLRTX 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 Ti90180270360450SE +/- 0.71, N = 3SE +/- 0.48, N = 3SE +/- 0.06, N = 3SE +/- 0.12, N = 3SE +/- 0.70, N = 3SE +/- 0.53, N = 3SE +/- 0.08, N = 3SE +/- 0.60, N = 3SE +/- 0.16, N = 3SE +/- 0.16, N = 3SE +/- 0.11, N = 3SE +/- 0.42, N = 3SE +/- 0.06, N = 3SE +/- 0.26, N = 3SE +/- 0.31, N = 3SE +/- 0.28, N = 3SE +/- 0.00, N = 3SE +/- 1.04, N = 3283.98250.98162.63327.80433.81251.07205.85305.76220.44130.64240.62333.54172.68142.14156.50196.01116.05424.07

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 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 Ti110220330440550SE +/- 0.43, N = 3SE +/- 0.82, N = 3SE +/- 0.06, N = 3SE +/- 0.54, N = 3SE +/- 1.39, N = 3SE +/- 1.00, N = 3SE +/- 0.03, N = 3SE +/- 0.15, N = 3SE +/- 0.40, N = 3SE +/- 0.03, N = 3SE +/- 0.03, N = 3SE +/- 0.28, N = 3SE +/- 0.12, N = 3SE +/- 0.00, N = 3SE +/- 0.03, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.35, N = 3319.57333.20241.50345.77495.37322.67190.03331.50241.20144.57214.67340.27208.67151.50148.87190.90132.60441.231. (CC) gcc options: -O2 -flto -lOpenCL

Rodinia

OpenBenchmarking.orgWatts, Fewer Is BetterRodinia 2.4System Power Consumption MonitorRTX 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 Ti306090120150Min: 46.4 / Avg: 116.19 / Max: 128.7Min: 46.3 / Avg: 122.27 / Max: 129.5Min: 110.1 / Avg: 153.24 / Max: 157.4Min: 46.6 / Avg: 123.16 / Max: 135.3Min: 51.9 / Avg: 158.82 / Max: 169.5Min: 48.1 / Avg: 122.39 / Max: 128.3Min: 49.1 / Avg: 105.1 / Max: 108.7Min: 49.5 / Avg: 131.08 / Max: 142Min: 46.6 / Avg: 112.18 / Max: 123.5Min: 62.8 / Avg: 97.17 / Max: 100.8Min: 47.4 / Avg: 113.6 / Max: 118.7Min: 53.3 / Avg: 137.65 / Max: 146.3Min: 45.9 / Avg: 98.53 / Max: 104.6Min: 88.8 / Avg: 119.77 / Max: 124.7Min: 45.5 / Avg: 90.35 / Max: 95.7Min: 70.9 / Avg: 107.97 / Max: 112.9Min: 85.4 / Avg: 117.57 / Max: 120.9Min: 51.1 / Avg: 152.87 / Max: 162.6

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 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 Ti2K4K6K8K10KSE +/- 0.67, N = 3SE +/- 8.00, N = 3SE +/- 0.58, N = 3SE +/- 1.73, N = 3SE +/- 1.86, N = 3SE +/- 3.51, N = 3SE +/- 0.88, N = 3SE +/- 0.67, N = 3SE +/- 3.76, N = 3SE +/- 0.67, N = 3SE +/- 7.09, N = 3SE +/- 2.73, N = 3SE +/- 0.58, N = 3SE +/- 1.20, N = 3SE +/- 1.86, N = 3SE +/- 4.37, N = 3656561483885683998366150417065904833264838075649380530483733387027309215

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 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 Ti110220330440550SE +/- 0.33, N = 3SE +/- 0.11, N = 3SE +/- 0.52, N = 3SE +/- 0.08, N = 3SE +/- 0.66, N = 3SE +/- 0.07, N = 3SE +/- 0.00, N = 3SE +/- 0.22, N = 3SE +/- 0.24, N = 3SE +/- 0.06, N = 3SE +/- 0.09, N = 3SE +/- 0.71, N = 3SE +/- 0.17, N = 3SE +/- 0.03, N = 3SE +/- 0.00, N = 3SE +/- 0.18, N = 3SE +/- 0.06, N = 3SE +/- 0.44, N = 3369.11367.92263.22405.00528.89368.96197.26368.47275.86146.62222.09328.90234.67164.25157.60196.47143.48506.331. (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 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 Ti5001000150020002500SE +/- 1.25, N = 3SE +/- 1.59, N = 3SE +/- 0.07, N = 3SE +/- 2.80, N = 3SE +/- 13.68, N = 3SE +/- 1.46, N = 3SE +/- 0.73, N = 3SE +/- 4.17, N = 3SE +/- 2.11, N = 3SE +/- 0.63, N = 3SE +/- 1.27, N = 3SE +/- 5.20, N = 3SE +/- 0.86, N = 3SE +/- 0.24, N = 3SE +/- 1.38, N = 3SE +/- 1.57, N = 3SE +/- 0.75, N = 3SE +/- 6.28, N = 31649.171531.01990.121762.002466.661516.961009.261663.871232.47726.301123.851672.731002.00759.43814.65987.69671.492335.46

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: Inception V3 - Device: OpenCLRTX 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 Ti80160240320400SE +/- 0.07, N = 3SE +/- 0.25, N = 3SE +/- 0.07, N = 3SE +/- 0.10, N = 3SE +/- 0.42, N = 3SE +/- 0.29, N = 3SE +/- 0.06, N = 3SE +/- 0.57, N = 3SE +/- 0.23, N = 3SE +/- 0.10, N = 3SE +/- 0.38, N = 3SE +/- 0.14, N = 3SE +/- 0.23, N = 3SE +/- 0.17, N = 3SE +/- 0.12, N = 3SE +/- 0.09, N = 3SE +/- 0.16, N = 3SE +/- 0.38, N = 3215.85199.43135.14259.26347.93198.03153.34238.73167.87104.44184.80257.55140.05105.64116.90147.1794.72343.49

cl-mem

OpenBenchmarking.orgGB/s Per Watt, More Is Bettercl-mem 2017-01-13Benchmark: ReadRTX 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 Ti0.86631.73262.59893.46524.33153.473.091.763.853.373.281.863.262.761.341.902.102.671.191.691.681.053.38

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 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 Ti3K6K9K12K15KSE +/- 76.18, N = 15SE +/- 84.87, N = 15SE +/- 44.36, N = 15SE +/- 124.22, N = 3SE +/- 228.75, N = 15SE +/- 81.15, N = 15SE +/- 7.63, N = 3SE +/- 7.41, N = 3SE +/- 77.72, N = 3SE +/- 1.88, N = 3SE +/- 3.14, N = 3SE +/- 5.50, N = 3SE +/- 61.47, N = 15SE +/- 46.38, N = 8SE +/- 7.83, N = 3SE +/- 3.03, N = 3SE +/- 40.24, N = 15SE +/- 207.30, N = 38502.717089.505538.7510335.5014203.877198.646770.978883.905329.074199.718314.2911720.574793.664476.694610.016269.493888.1613532.741. (CXX) g++ options: -O3 -rdynamic -lOpenCL

PlaidML

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: VGG19 - Device: OpenCLRTX 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 Ti0.16430.32860.49290.65720.82150.490.390.230.590.710.440.460.580.400.280.430.490.380.220.380.370.200.73

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: Inception V3 - Device: OpenCLRTX 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 Ti0.4590.9181.3771.8362.2951.721.490.601.992.041.571.121.751.340.781.101.131.320.611.220.950.562.04

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: ResNet 50 - Device: OpenCLRTX 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 Ti0.5761.1521.7282.3042.882.101.740.792.222.561.691.572.191.551.011.511.761.470.781.421.240.712.53

cl-mem

OpenBenchmarking.orgGB/s Per Watt, More Is Bettercl-mem 2017-01-13Benchmark: WriteRTX 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 Ti0.83481.66962.50443.33924.1742.602.611.482.853.133.711.762.742.241.441.642.022.331.031.611.541.073.46

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 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 Ti140280420560700SE +/- 0.19, N = 3SE +/- 0.53, N = 3SE +/- 0.58, N = 3SE +/- 0.61, N = 3SE +/- 0.75, N = 3SE +/- 0.27, N = 3SE +/- 0.09, N = 3SE +/- 0.25, N = 3SE +/- 0.39, N = 3SE +/- 0.07, N = 3SE +/- 0.32, N = 3SE +/- 0.72, N = 3SE +/- 0.47, N = 3SE +/- 0.02, N = 3SE +/- 0.16, N = 3SE +/- 0.15, N = 3SE +/- 0.06, N = 3SE +/- 0.63, N = 3421.58374.71247.47468.70648.36376.73294.36441.24319.25196.00337.47496.24259.43203.91228.14276.89181.87634.09

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 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 Ti70140210280350220.76205.23142.20233.56322.76206.88141.35222.88164.5291.44147.98212.04132.28109.70118.49132.8695.60309.04

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 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 Ti6001200180024003000SE +/- 4.73, N = 3SE +/- 10.89, N = 3SE +/- 1.24, N = 3SE +/- 6.75, N = 3SE +/- 4.02, N = 3SE +/- 5.21, N = 3SE +/- 0.80, N = 3SE +/- 4.68, N = 3SE +/- 3.62, N = 3SE +/- 2.37, N = 3SE +/- 4.27, N = 3SE +/- 7.35, N = 3SE +/- 2.77, N = 3SE +/- 2.37, N = 3SE +/- 1.34, N = 3SE +/- 4.57, N = 3SE +/- 1.43, N = 3SE +/- 13.82, N = 32264.971983.821202.772437.482842.381969.501371.212292.381694.07908.431544.502162.581394.05973.391160.521288.94841.482750.57

cl-mem

OpenBenchmarking.orgGB/s Per Watt, More Is Bettercl-mem 2017-01-13Benchmark: CopyRTX 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 Ti0.72681.45362.18042.90723.6342.822.431.452.832.172.441.532.282.661.251.651.621.961.041.581.350.963.23

PlaidML

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: NASNer Large - Device: OpenCLRTX 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 Ti0.08330.16660.24990.33320.41650.300.250.130.320.370.260.230.290.230.150.200.240.220.120.210.180.110.37

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: VGG16 - Device: OpenCLRTX 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 Ti0.23180.46360.69540.92721.1590.810.710.320.821.030.680.670.820.620.420.610.750.560.320.580.560.310.98

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: DenseNet 201 - Device: OpenCLRTX 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 Ti60120180240300SE +/- 0.14, N = 3SE +/- 0.03, N = 3SE +/- 0.18, N = 3SE +/- 0.07, N = 3SE +/- 0.18, N = 3SE +/- 0.22, N = 3SE +/- 0.01, N = 3SE +/- 0.17, N = 3SE +/- 0.05, N = 3SE +/- 0.15, N = 3SE +/- 0.01, N = 3SE +/- 0.03, N = 3SE +/- 0.03, N = 3SE +/- 0.12, N = 3SE +/- 0.10, N = 3SE +/- 0.05, N = 3SE +/- 0.01, N = 3SE +/- 0.10, N = 3190.01179.51111.46200.38263.13176.49130.15189.28154.1991.07143.53191.31114.5892.92102.83127.0279.71254.45

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 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 Ti70140210280350SE +/- 0.60, N = 3SE +/- 0.34, N = 3SE +/- 0.04, N = 3SE +/- 0.78, N = 3SE +/- 0.71, N = 3SE +/- 0.64, N = 3SE +/- 0.05, N = 3SE +/- 0.99, N = 3SE +/- 0.61, N = 3SE +/- 0.17, N = 3SE +/- 0.53, N = 3SE +/- 0.43, N = 3SE +/- 0.15, N = 3SE +/- 0.08, N = 3SE +/- 0.27, N = 3SE +/- 0.43, N = 3SE +/- 0.03, N = 3SE +/- 0.90, N = 3229.12205.20116.02256.83301.93204.71138.21242.75183.41102.61155.22198.25139.81102.86126.64140.2991.53301.89

PlaidML

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: VGG19 - Device: OpenCLRTX 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 Ti0.16880.33760.50640.67520.8440.610.520.250.640.750.530.500.560.460.320.480.560.440.260.420.430.240.74

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 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 Ti3691215SE +/- 0.07, N = 3SE +/- 0.00, N = 3SE +/- 0.04, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.07, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.02, N = 3SE +/- 0.01, N = 3SE +/- 0.02, N = 3SE +/- 0.02, N = 3SE +/- 0.07, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 3SE +/- 0.02, N = 3SE +/- 0.02, N = 36.827.879.955.744.247.757.886.228.9011.936.494.9610.8211.6911.878.2612.994.391. (CXX) g++ options: -O2 -lOpenCL

PlaidML

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: DenseNet 201 - Device: OpenCLRTX 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 Ti0.34430.68861.03291.37721.72151.531.260.581.411.521.271.011.291.150.720.950.940.990.590.960.940.541.47

clpeak

OpenBenchmarking.orgGFLOPS Per Watt, More Is BetterclpeakOpenCL Test: Double-Precision DoubleRTX 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 Ti0.60751.2151.82252.433.03752.251.851.092.502.701.952.142.251.841.462.202.491.721.091.731.900.982.65

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 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 Ti0.99451.9892.98353.9784.9725SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 3SE +/- 0.02, 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 +/- 0.01, 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 = 31.931.953.271.821.641.932.931.902.223.652.722.292.923.923.352.894.421.64

SHOC Scalable HeterOgeneous Computing

OpenBenchmarking.orgGFLOPS Per Watt, More Is BetterSHOC Scalable HeterOgeneous Computing 2015-11-10Target: OpenCL - Benchmark: Max SP FlopsRTX 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 Ti2040608010065.7656.3832.0573.2377.7257.1361.4363.9350.3640.0659.8766.2649.6331.4050.1750.3029.2976.69

JuliaGPU

OpenBenchmarking.orgSamples/sec Per Watt, More Is BetterJuliaGPU 1.2pts1OpenCL Device: GPURTX 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 Ti600K1200K1800K2400K3000K2632329.692670026.701099178.252379445.261923116.672271141.792260229.902691799.292469451.171658141.691906369.991682592.712880366.361325997.882790569.691809790.271275493.931910018.66

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 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 Ti70140210280350SE +/- 0.17, N = 3SE +/- 0.31, N = 3SE +/- 0.17, N = 3SE +/- 0.13, N = 3SE +/- 0.67, N = 3SE +/- 0.24, N = 3SE +/- 0.00, N = 3SE +/- 0.15, N = 3SE +/- 0.12, N = 3SE +/- 0.06, N = 3SE +/- 0.03, N = 3SE +/- 0.25, N = 3SE +/- 0.15, N = 3SE +/- 0.00, N = 3SE +/- 0.03, N = 3SE +/- 0.06, N = 3SE +/- 0.03, N = 3SE +/- 0.40, N = 3291.87287.80216.83301.23322.20284.43182.70289.20237.77137.20205.93283.20208.50143.40145.37182.00124.77324.401. (CC) gcc options: -O2 -flto -lOpenCL

ViennaCL

OpenBenchmarking.orgGFLOPS Per Watt, More Is BetterViennaCL 1.4.2OpenCL 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 Ti0.3150.630.9451.261.5750.901.400.601.181.351.350.710.710.731.000.700.591.100.791.080.800.661.31

FAHBench

OpenBenchmarking.orgNs Per Day Per Watt, More Is BetterFAHBench 2.3.2RTX 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 Ti0.32630.65260.97891.30521.63151.421.270.621.451.331.291.101.381.210.831.001.021.100.651.110.960.621.38

LuxMark

OpenBenchmarking.orgScore Per Watt, More Is BetterLuxMark 3.1OpenCL Device: GPU - Scene: Luxball HDRRTX 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 Ti306090120150136.85131.3370.64130.92137.34130.30111.54119.09112.4383.3476.5588.26102.7567.87108.7095.0365.07131.66

OpenBenchmarking.orgScore Per Watt, More Is BetterLuxMark 3.1OpenCL Device: GPU - Scene: MicrophoneRTX 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 Ti2040608010092.7883.0947.2589.5891.0083.9270.3282.6072.1151.1450.2957.6870.3346.0871.2258.6344.9189.77

OpenBenchmarking.orgScore Per Watt, More Is BetterLuxMark 3.1OpenCL Device: GPU - Scene: HotelRTX 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 Ti61218243027.1826.3815.2127.4127.4625.5225.6424.5022.9217.0018.5120.0222.5014.1624.2219.5913.7226.99

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 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 Ti7001400210028003500SE +/- 17.64, N = 7SE +/- 18.12, N = 15SE +/- 5.67, N = 15SE +/- 29.82, N = 3SE +/- 28.21, N = 3SE +/- 16.93, N = 15SE +/- 8.69, N = 6SE +/- 21.60, N = 3SE +/- 1.84, N = 3SE +/- 3.68, N = 4SE +/- 14.70, N = 3SE +/- 32.29, N = 3SE +/- 5.83, N = 15SE +/- 2.79, N = 3SE +/- 4.05, N = 15SE +/- 12.32, N = 15SE +/- 1.93, N = 15SE +/- 8.77, N = 31604.21998.17466.842105.263126.48999.75753.691879.99704.69262.411146.751886.30420.04280.99335.86642.12207.843032.101. (CXX) g++ options: -lpthread

clpeak

OpenBenchmarking.orgGIOPS Per Watt, More Is BetterclpeakOpenCL Test: Integer Compute INTRTX 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 Ti30609012015060.3980.749.0072.1666.5852.7825.59123.0763.2510.8326.8216.5261.388.4479.9423.899.1954.76

LeelaChessZero

OpenBenchmarking.orgNodes Per Second Per Watt, More Is BetterLeelaChessZero 0.22.0Backend: OpenCLRTX 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 Ti481216208.986.572.1612.3215.815.785.8610.734.791.907.108.753.131.832.844.211.2614.00

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 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 Ti3K6K9K12K15KSE +/- 81.60, N = 15SE +/- 76.65, N = 15SE +/- 23.09, N = 3SE +/- 83.79, N = 15SE +/- 156.59, N = 15SE +/- 84.78, N = 15SE +/- 0.72, N = 3SE +/- 4.11, N = 3SE +/- 63.11, N = 3SE +/- 13.36, N = 15SE +/- 26.46, N = 3SE +/- 29.87, N = 15SE +/- 64.34, N = 15SE +/- 0.38, N = 3SE +/- 32.97, N = 3SE +/- 24.36, N = 3SE +/- 19.67, N = 3SE +/- 57.62, N = 38570.607023.071610.2810404.7113841.257161.482076.939660.925269.011267.892430.743301.894775.451312.064657.791685.051140.2913609.331. (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 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 Ti0.08180.16360.24540.32720.409SE +/- 0.00245, N = 3SE +/- 0.00245, N = 3SE +/- 0.00105, N = 3SE +/- 0.00233, N = 3SE +/- 0.00297, N = 3SE +/- 0.00250, N = 3SE +/- 0.00075, N = 6SE +/- 0.00199, N = 3SE +/- 0.00147, N = 4SE +/- 0.00303, N = 3SE +/- 0.00088, N = 5SE +/- 0.00044, N = 3SE +/- 0.00192, N = 3SE +/- 0.00159, N = 3SE +/- 0.00287, N = 3SE +/- 0.00195, N = 3SE +/- 0.00026, N = 4SE +/- 0.00238, N = 30.195010.193360.286750.193850.188670.194400.222690.193070.202500.317890.209780.196690.231850.331100.250310.239570.363680.18909

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 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 Ti60M120M180M240M300MSE +/- 389272.10, N = 3SE +/- 369711.60, N = 3SE +/- 78142.08, N = 3SE +/- 1165562.77, N = 3SE +/- 489061.14, N = 3SE +/- 633693.84, N = 3SE +/- 97519.45, N = 3SE +/- 169596.23, N = 3SE +/- 121354.48, N = 3SE +/- 137674.47, N = 3SE +/- 341457.11, N = 3SE +/- 540298.84, N = 3SE +/- 495295.96, N = 3SE +/- 52667.10, N = 3SE +/- 197521.26, N = 3SE +/- 76295.47, N = 3SE +/- 383961.59, N = 3SE +/- 78810.54, N = 3275868151.17264172441.47195653728.47286818331.27303198573.97267086274.53220447755.87280162469.67251925176.90182188318.67237914974.40262248899.33239300837.60181882709.77230919642.13216942144.93169258044.90299834728.801. (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 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 Ti0.24080.48160.72240.96321.2041.040.970.641.040.990.961.070.930.870.760.880.890.910.610.930.840.600.96

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 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 Ti1224364860SE +/- 0.15, N = 3SE +/- 0.04, N = 3SE +/- 0.18, N = 3SE +/- 0.04, N = 3SE +/- 0.04, N = 3SE +/- 0.03, N = 3SE +/- 0.14, N = 3SE +/- 0.04, N = 3SE +/- 0.05, N = 3SE +/- 0.10, N = 3SE +/- 0.04, N = 3SE +/- 0.03, N = 3SE +/- 0.05, N = 3SE +/- 0.05, N = 3SE +/- 0.08, N = 3SE +/- 0.08, N = 3SE +/- 0.06, N = 3SE +/- 0.07, N = 330.7630.4252.1330.6331.6931.6438.7031.6531.1134.6934.8735.9130.6747.3830.9735.1045.4831.051. (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 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 Ti1.30052.6013.90155.2026.5025SE +/- 0.02, 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 +/- 0.00, N = 3SE +/- 0.02, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 3SE +/- 0.02, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.03, N = 3SE +/- 0.01, N = 33.713.684.123.693.663.673.973.713.734.073.943.924.025.744.013.925.783.66

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 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 Ti1632486480SE +/- 0.05, N = 3SE +/- 0.06, N = 3SE +/- 0.02, N = 3SE +/- 0.26, N = 3SE +/- 0.60, N = 3SE +/- 0.03, N = 3SE +/- 0.01, N = 3SE +/- 0.07, N = 3SE +/- 0.21, N = 3SE +/- 0.05, N = 3SE +/- 0.20, N = 3SE +/- 0.31, N = 3SE +/- 0.05, N = 3SE +/- 0.04, N = 3SE +/- 0.02, N = 3SE +/- 0.03, N = 3SE +/- 0.11, N = 3SE +/- 0.72, N = 370.4569.1762.0171.4772.9669.4164.6870.9667.9258.6766.6769.0966.0659.2165.1063.8656.9572.711. (CXX) g++ options: -rdynamic -lOpenCL

System Power Consumption Monitor

OpenBenchmarking.orgWattsSystem Power Consumption MonitorPhoronix Test Suite System MonitoringRTX 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 Ti70140210280350Min: 45.5 / Avg: 134.05 / Max: 323.3Min: 45.4 / Avg: 158.95 / Max: 312Min: 53.6 / Avg: 199.07 / Max: 370.3Min: 46 / Avg: 173.42 / Max: 330.5Min: 50.6 / Avg: 227.86 / Max: 371.4Min: 46 / Avg: 164.53 / Max: 321.3Min: 48.6 / Avg: 131.89 / Max: 259.9Min: 47.5 / Avg: 181.54 / Max: 342.9Min: 46.1 / Avg: 153.75 / Max: 303.8Min: 44.3 / Avg: 128.45 / Max: 269.5Min: 44.9 / Avg: 162.99 / Max: 328.3Min: 49.6 / Avg: 207.86 / Max: 380Min: 45.4 / Avg: 127.55 / Max: 273.9Min: 49.8 / Avg: 167.77 / Max: 329.4Min: 43.1 / Avg: 115.15 / Max: 262.4Min: 43.8 / Avg: 150.54 / Max: 286.9Min: 48.8 / Avg: 157.71 / Max: 306.3Min: 49.7 / Avg: 227.4 / Max: 374

GPU Temperature Monitor

OpenBenchmarking.orgCelsiusGPU Temperature MonitorPhoronix Test Suite System MonitoringRTX 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 Ti1632486480Min: 27 / Avg: 43.67 / Max: 69Min: 29 / Avg: 54.33 / Max: 75Min: 36 / Avg: 71.62 / Max: 85Min: 34 / Avg: 53.35 / Max: 70Min: 37 / Avg: 62.01 / Max: 80Min: 28 / Avg: 58.64 / Max: 77Min: 39 / Avg: 48.41 / Max: 61Min: 30 / Avg: 66.02 / Max: 83Min: 32 / Avg: 57.94 / Max: 72Min: 30 / Avg: 58.15 / Max: 74Min: 30 / Avg: 63.66 / Max: 77Min: 34 / Avg: 67.92 / Max: 84Min: 30 / Avg: 50.73 / Max: 65Min: 29 / Avg: 68.53 / Max: 81Min: 28 / Avg: 56.71 / Max: 77Min: 28 / Avg: 61.94 / Max: 76Min: 28 / Avg: 52.34 / Max: 68Min: 31 / Avg: 60.94 / Max: 77

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