GPU Compute

AMD Ryzen 9 3950X 16-Core testing with a ASUS ROG CROSSHAIR VIII HERO (WI-FI) (1302 BIOS) and NVIDIA GeForce GTX 1060 6GB on Ubuntu 20.04 via the Phoronix Test Suite.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2009080-FI-GPUCOMPUT34
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BLAS (Basic Linear Algebra Sub-Routine) Tests 2 Tests
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Result
Identifier
Performance Per
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Date
Run
  Test
  Duration
TITAN RTX
September 06 2020
  1 Hour, 24 Minutes
GTX 1070 Ti
September 06 2020
  1 Hour, 31 Minutes
GTX 970
September 06 2020
  2 Hours, 9 Minutes
GTX 1660 SUPER
September 07 2020
  1 Hour, 30 Minutes
GTX 980
September 07 2020
  1 Hour, 34 Minutes
GTX 1070
September 07 2020
  1 Hour, 26 Minutes
GTX 1080
September 07 2020
  1 Hour, 23 Minutes
GTX 980 Ti
September 07 2020
  1 Hour, 29 Minutes
RTX 2080 Ti
September 07 2020
  1 Hour, 24 Minutes
GTX 1060
September 08 2020
  1 Hour, 32 Minutes
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GPU ComputeProcessorMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelDesktopDisplay ServerDisplay DriverOpenGLOpenCLVulkanCompilerFile-SystemScreen ResolutionTITAN RTXGTX 1070 TiGTX 970GTX 1660 SUPERGTX 980GTX 1070GTX 1080GTX 980 TiRTX 2080 TiGTX 1060AMD Ryzen 9 3950X 16-Core @ 3.50GHz (16 Cores / 32 Threads)ASUS ROG CROSSHAIR VIII HERO (WI-FI) (1302 BIOS)AMD Starship/Matisse16GB2000GB Corsair Force MP600NVIDIA TITAN RTX 24GB (420/405MHz)NVIDIA TU102 HD AudioDELL P2415QRealtek RTL8125 2.5GbE + Intel I211 + Intel Wi-Fi 6 AX200Ubuntu 20.045.4.0-45-generic (x86_64)GNOME Shell 3.36.4X Server 1.20.8NVIDIA 450.664.6.0OpenCL 1.2 CUDA 11.0.2281.2.133GCC 9.3.0 + CUDA 11.0ext43840x2160Zotac NVIDIA GeForce GTX 1070 Ti 8GB (1607/4006MHz)NVIDIA GP104 HD AudioeVGA NVIDIA GeForce GTX 970 4GB (1163/3505MHz)NVIDIA GM204 HD AudioeVGA NVIDIA GeForce GTX 1660 SUPER 6GB (1530/7000MHz)NVIDIA TU116 HD AudioNVIDIA GeForce GTX 980 4GB (1126/3505MHz)NVIDIA GM204 HD AudioNVIDIA GeForce GTX 1070 8GB (1506/4006MHz)NVIDIA GP104 HD AudioNVIDIA GeForce GTX 1080 8GB (1607/5005MHz)NVIDIA GeForce GTX 980 Ti 6GB (999/3505MHz)NVIDIA GM200 HD AudioNVIDIA GeForce RTX 2080 Ti 11GB (1350/7000MHz)NVIDIA TU102 HD AudioNVIDIA GeForce GTX 1060 6GB (1506/4006MHz)NVIDIA GP106 HD Audio5.4.0-47-generic (x86_64)OpenBenchmarking.orgCompiler Details- --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --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++,gm2 --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none,hsa --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=auto --with-tune=generic --without-cuda-driver -v Processor Details- Scaling Governor: acpi-cpufreq performance - CPU Microcode: 0x8701013OpenCL Details- TITAN RTX: GPU Compute Cores: 4608- GTX 1070 Ti: GPU Compute Cores: 2432- GTX 970: GPU Compute Cores: 1664- GTX 1660 SUPER: GPU Compute Cores: 1408- GTX 980: GPU Compute Cores: 2048- GTX 1070: GPU Compute Cores: 1920- GTX 1080: GPU Compute Cores: 2560- GTX 980 Ti: GPU Compute Cores: 2816- RTX 2080 Ti: GPU Compute Cores: 4352- GTX 1060: GPU Compute Cores: 1280Python Details- Python 3.8.2Security Details- itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + 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 AMD retpoline IBPB: conditional STIBP: conditional RSB filling + srbds: Not affected + tsx_async_abort: Not affected

TITAN RTXGTX 1070 TiGTX 970GTX 1660 SUPERGTX 980GTX 1070GTX 1080GTX 980 TiRTX 2080 TiGTX 1060Result OverviewPhoronix Test Suite100%213%326%439%552%MixbenchclpeakLeelaChessZeroMandelGPUOctaneBenchPlaidMLcl-memFAHBenchLuxCoreRender OpenCLFinanceBenchArrayFireGROMACSDarktableNAMD CUDARodiniaViennaCLDarmstadt Automotive Parallel Heterogeneous Suite

GPU Computelczero: OpenCLgromacs-gpu: Water Benchmarkoctanebench: Total Scorefahbench: luxcorerender-cl: Foodluxcorerender-cl: LuxCore Benchmarkdaphne: OpenCL - Points2Imagedaphne: NVIDIA CUDA - Points2Imageluxcorerender-cl: DLSCrodinia: NVIDIA CUDA GPU Myocyteplaidml: No - Inference - DenseNet 201 - OpenCLluxcorerender-cl: Rainbow Colors and Prismrodinia: OpenCL Myocyteplaidml: No - Inference - VGG19 - OpenCLdaphne: OpenCL - NDT Mappingplaidml: No - Training - Mobilenet - OpenCLplaidml: No - Inference - VGG16 - OpenCLclpeak: Double-Precision Doubleplaidml: No - Inference - Inception V3 - OpenCLdaphne: NVIDIA CUDA - NDT Mappingarrayfire: BLAS OpenCLdaphne: NVIDIA CUDA - Euclidean Clusternamd-cuda: ATPase Simulation - 327,506 Atomsplaidml: No - Inference - IMDB LSTM - OpenCLdaphne: OpenCL - Euclidean Clustermandelgpu: GPUrodinia: OpenCL Particle Filtercl-mem: Readcl-mem: Writecl-mem: Copyplaidml: Yes - Inference - Mobilenet - OpenCLplaidml: No - Inference - Mobilenet - OpenCLfinancebench: Monte-Carlo OpenCLdarktable: Masskrug - OpenCLdarktable: Boat - OpenCLdarktable: Server Room - OpenCLclpeak: Integer Compute INTarrayfire: Conjugate Gradient OpenCLviennacl: OpenCL LU Factorizationmixbench: NVIDIA CUDA - Single Precisionclpeak: Global Memory Bandwidthmixbench: NVIDIA CUDA - Integermixbench: NVIDIA CUDA - Double Precisionmixbench: NVIDIA CUDA - Half Precisionclpeak: Single-Precision Floatmixbench: OpenCL - Single Precisiondarktable: Server Rack - OpenCLneatbench: GPUmixbench: OpenCL - Integermixbench: OpenCL - Double Precisionfinancebench: Black-Scholes OpenCLTITAN RTXGTX 1070 TiGTX 970GTX 1660 SUPERGTX 980GTX 1070GTX 1080GTX 980 TiRTX 2080 TiGTX 1060224247.117324.546769292.15932.234.9912538.24578708129401.5140702215.9840.373227.3012.7335.767196.63343.61198.37248.79548.26355.85590.635040.581434.170.19195775.692279.14480798376.64.250567.7491.7322.72856.832544.67277.2321212.7921.4910.76713783.931.66676.641015103.61530.7914426.11413.6632084.7914178.8515032.470.10348.116979.99454.375.70199474.259141.667655137.13930.982.2413281.7676294192.5547.722108.235.3842.08192.87349.1299.64116.89242.70159.434304.761204.770.22300331.842223.78194875210.87.791206.2198.2184.11485.781070.90754.2840122.9982.7411.1662076.453.81469.18386647.94198.181887.61240.92121.426788.407018.900.1172157.31241.997.29851632.99596.20086490.84600.671.4611485.5041370451.7356.49873.894.8148.92051.14324.7073.2564.53137.4897.832457.73979.330.36071203.081928.88113624502.013.185144.6136.3125.9910.91716.82841.1885814.6104.3112.8621145.145.40060.1979144.563874.984141.790.16315.41215.75137.2014.19673664.629135.657134135.60731.092.2613933.27394816529306.1275059072.6339.905100.515.6134.12768.81320.97111.3986.61172.49135.31563.131765.011466.240.23177298.772175.96200846066.411.482296.6240.7240.21380.681080.11594.4380043.0302.6071.0824280.552.64268.15325440.74276.354866.61144.1410862.904440.235462.590.1045432.40144.3015.27162653.271110.814321102.36680.781.6311735.8414852981.9359.47482.215.1150.55356.60333.5280.4772.21159.72109.502826.161019.040.33566228.461976.41121139566.811.774165.3159.1145.01053.49810.50749.2880024.5433.7642.7301306.514.90461.9362165.294472.774683.960.16217.31389.90159.3312.10197504.052132.839354139.49740.922.1213045.8573943512.4642.955108.466.6238.00379.12345.44103.7999.88223.60151.712905.881231.440.24022314.832243.10184077179.78.205206.2199.5183.31392.461052.64697.5462912.9742.7091.1121695.794.07766.20686174.80197.201764.63225.05113.326093.026476.920.11721.52019.08224.828.968126624.634148.472009151.56790.992.1313141.7294623902.4543.197112.284.2337.998103.83348.2999.82131.34298.46190.145091.861218.560.22426398.822345.38231826397.86.457229.6225.6207.41665.721154.13921.6841522.9742.5461.0952430.553.38770.68808182.72223.142326.09296.09149.358218.628520.970.11124.62655.58296.666.98182833.857143.521432115.77530.922.0011829.8646244982.3664.75899.846.5955.17471.18339.2189.2890.74197.23138.332438.97976.750.29138267.881908.81148357386.110.071266.0245.9217.81290.481029.36660.5482493.2273.0171.3981612.523.62264.5358264.745512.895844.900.1641711.03197.449.596218397.136310.814399290.72492.234.7513045.03092394128816.8178368955.6740.352212.1112.3335.235187.92350.37187.73237.29522.22353.54606.754836.621436.620.19082753.752268.23448915216.64.414545.7449.5324.02751.852406.16319.9141272.7551.4920.75913629.371.67775.787114734.03506.9014103.79409.4631492.2413536.2516061.090.10016323.94436.816.02059333.18191.732906102.26830.651.5311766.2918261271.7842.70379.135.4138.11456.62333.4783.5271.78150.68108.562856.381253.430.30957227.232076.48130290433.812.002154.4148.1138.5987.07775.73894.0848653.1693.5171.3011275.125.00061.65304167.41147.661187.72151.6375.774110.714355.280.1241354.14150.4813.340OpenBenchmarking.org

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 0.26Backend: OpenCLGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX5K10K15K20K25KSE +/- 28.32, N = 3SE +/- 55.16, N = 3SE +/- 28.99, N = 3SE +/- 57.21, N = 3SE +/- 85.75, N = 3SE +/- 43.89, N = 3SE +/- 54.30, N = 3SE +/- 36.50, N = 3SE +/- 20.50, N = 359332183982831266297506265736651639947224241. (CXX) g++ options: -flto -pthread

GROMACS

The CUDA version of the Gromacs molecular dynamics package. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgNs Per Day, More Is BetterGROMACS 2020.3Water BenchmarkGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX246810SE +/- 0.003, N = 3SE +/- 0.020, N = 2SE +/- 0.003, N = 3SE +/- 0.004, N = 3SE +/- 0.003, N = 3SE +/- 0.003, N = 3SE +/- 0.007, N = 3SE +/- 0.003, N = 3SE +/- 0.002, N = 3SE +/- 0.005, N = 33.1817.1363.8574.6344.0523.2714.6292.9954.2597.1171. (CXX) g++ options: -O3 -lpthread -ldl -lrt -lm

OctaneBench

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

OpenBenchmarking.orgScore, More Is BetterOctaneBench 4.00cTotal ScoreGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX7014021028035091.73310.81143.52148.47132.84110.81135.6696.20141.67324.55

FAHBench

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

OpenBenchmarking.orgNs Per Day, More Is BetterFAHBench 2.3.2GTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX60120180240300SE +/- 0.16, N = 3SE +/- 1.17, N = 3SE +/- 0.33, N = 3SE +/- 0.41, N = 3SE +/- 0.46, N = 3SE +/- 0.15, N = 3SE +/- 0.17, N = 3SE +/- 0.03, N = 3SE +/- 0.06, N = 3SE +/- 0.85, N = 3102.27290.72115.78151.57139.50102.37135.6190.85137.14292.16

LuxCoreRender OpenCL

LuxCoreRender is an open-source physically based renderer. This test profile is focused on running LuxCoreRender on OpenCL accelerators/GPUs. The alternative luxcorerender test profile is for CPU execution due to a difference in tests, etc. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgM samples/sec, More Is BetterLuxCoreRender OpenCL 2.3Scene: FoodGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX0.50181.00361.50542.00722.509SE +/- 0.01, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.02, N = 12SE +/- 0.01, N = 3SE +/- 0.02, N = 30.652.230.920.990.920.781.090.670.982.23MIN: 0.22 / MAX: 0.74MIN: 0.32 / MAX: 2.65MIN: 0.23 / MAX: 1.06MIN: 0.24 / MAX: 1.15MIN: 0.23 / MAX: 1.06MIN: 0.23 / MAX: 0.88MIN: 0.25 / MAX: 1.26MIN: 0.12 / MAX: 0.81MIN: 0.24 / MAX: 1.14MIN: 0.25 / MAX: 2.7

OpenBenchmarking.orgM samples/sec, More Is BetterLuxCoreRender OpenCL 2.3Scene: LuxCore BenchmarkGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX1.12282.24563.36844.49125.614SE +/- 0.01, N = 3SE +/- 0.02, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.02, N = 3SE +/- 0.03, N = 12SE +/- 0.01, N = 3SE +/- 0.02, N = 31.534.752.002.132.121.632.261.462.244.99MIN: 0.23 / MAX: 1.72MIN: 0.32 / MAX: 5.39MIN: 0.27 / MAX: 2.27MIN: 0.27 / MAX: 2.39MIN: 0.27 / MAX: 2.4MIN: 0.27 / MAX: 1.83MIN: 0.27 / MAX: 2.54MIN: 0.12 / MAX: 1.68MIN: 0.27 / MAX: 2.52MIN: 0.32 / MAX: 5.69

Darmstadt Automotive Parallel Heterogeneous Suite

DAPHNE is the Darmstadt Automotive Parallel HeterogeNEous Benchmark Suite with OpenCL / CUDA / OpenMP test cases for these automotive benchmarks for evaluating programming models in context to vehicle autonomous driving capabilities. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgTest Cases Per Minute, More Is BetterDarmstadt Automotive Parallel Heterogeneous SuiteBackend: OpenCL - Kernel: Points2ImageGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX3K6K9K12K15KSE +/- 136.54, N = 3SE +/- 70.09, N = 3SE +/- 62.20, N = 3SE +/- 90.00, N = 3SE +/- 180.15, N = 3SE +/- 75.04, N = 3SE +/- 16.13, N = 3SE +/- 123.30, N = 3SE +/- 112.38, N = 3SE +/- 36.56, N = 311766.2913045.0311829.8613141.7313045.8611735.8413933.2711485.5013281.7712538.251. (CXX) g++ options: -O3 -m64 -std=c++11 -lcudadevrt -lcudart_static -lrt -lpthread -ldl

OpenBenchmarking.orgTest Cases Per Minute, More Is BetterDarmstadt Automotive Parallel Heterogeneous SuiteBackend: NVIDIA CUDA - Kernel: Points2ImageRTX 2080 TiGTX 1660 SUPERTITAN RTX6K12K18K24K30KSE +/- 496.68, N = 3SE +/- 284.42, N = 3SE +/- 203.08, N = 328816.8229306.1329401.511. (CXX) g++ options: -O3 -m64 -std=c++11 -lcudadevrt -lcudart_static -lrt -lpthread -ldl

LuxCoreRender OpenCL

LuxCoreRender is an open-source physically based renderer. This test profile is focused on running LuxCoreRender on OpenCL accelerators/GPUs. The alternative luxcorerender test profile is for CPU execution due to a difference in tests, etc. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgM samples/sec, More Is BetterLuxCoreRender OpenCL 2.3Scene: DLSCGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX1.34552.6914.03655.3826.7275SE +/- 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 +/- 0.04, N = 12SE +/- 0.00, N = 3SE +/- 0.01, N = 31.785.672.362.452.461.932.631.732.555.98MIN: 1.64 / MAX: 1.82MIN: 5.22 / MAX: 5.74MIN: 2.29 / MAX: 2.42MIN: 2.29 / MAX: 2.5MIN: 2.29 / MAX: 2.51MIN: 1.74 / MAX: 1.98MIN: 2.55 / MAX: 2.68MIN: 0.43 / MAX: 1.81MIN: 2.31 / MAX: 2.62MIN: 4.3 / MAX: 6.07

Rodinia

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

OpenBenchmarking.orgSeconds, Fewer Is BetterRodinia 3.1Test: NVIDIA CUDA GPU MyocyteGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX1428425670SE +/- 0.06, N = 3SE +/- 0.06, N = 3SE +/- 0.01, N = 3SE +/- 0.07, N = 3SE +/- 0.12, N = 3SE +/- 0.04, N = 3SE +/- 0.10, N = 3SE +/- 0.01, N = 3SE +/- 0.22, N = 3SE +/- 0.03, N = 342.7040.3564.7643.2042.9659.4739.9156.5047.7240.371. (CXX) g++ options: -m64 -lm -lcuda -lcudart -lcudadevrt -lcudart_static -lrt -lpthread -ldl

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: DenseNet 201 - Device: OpenCLGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX50100150200250SE +/- 0.02, N = 3SE +/- 0.21, N = 3SE +/- 0.09, N = 3SE +/- 0.07, N = 3SE +/- 0.04, N = 3SE +/- 0.15, N = 3SE +/- 0.05, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.25, N = 379.13212.1199.84112.28108.4682.21100.5173.89108.23227.30

LuxCoreRender OpenCL

LuxCoreRender is an open-source physically based renderer. This test profile is focused on running LuxCoreRender on OpenCL accelerators/GPUs. The alternative luxcorerender test profile is for CPU execution due to a difference in tests, etc. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgM samples/sec, More Is BetterLuxCoreRender OpenCL 2.3Scene: Rainbow Colors and PrismGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX3691215SE +/- 0.01, N = 3SE +/- 0.02, N = 4SE +/- 0.02, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.04, N = 3SE +/- 0.10, N = 12SE +/- 0.13, N = 12SE +/- 0.18, N = 45.4112.336.594.236.625.115.614.815.3812.73MIN: 4.66 / MAX: 5.64MIN: 11.33 / MAX: 12.81MIN: 5.89 / MAX: 6.88MIN: 3.57 / MAX: 4.38MIN: 5.17 / MAX: 6.91MIN: 4.25 / MAX: 5.29MIN: 5.07 / MAX: 5.86MIN: 1.5 / MAX: 5.09MIN: 1.63 / MAX: 5.69MIN: 11.95 / MAX: 14

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 select OpenCL, NVIDIA CUDA and OpenMP test binaries at the moment. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterRodinia 3.1Test: OpenCL MyocyteGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX1224364860SE +/- 0.15, N = 3SE +/- 0.07, N = 3SE +/- 0.04, N = 3SE +/- 0.07, N = 3SE +/- 0.08, N = 3SE +/- 0.06, N = 3SE +/- 0.08, N = 3SE +/- 0.26, N = 3SE +/- 0.24, N = 3SE +/- 0.08, N = 338.1135.2455.1738.0038.0050.5534.1348.9242.0835.771. (CXX) g++ options: -m64 -lm -lcuda -lcudart -lcudadevrt -lcudart_static -lrt -lpthread -ldl

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: VGG19 - Device: OpenCLGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX4080120160200SE +/- 0.16, N = 3SE +/- 0.60, N = 3SE +/- 1.20, N = 3SE +/- 0.31, N = 3SE +/- 0.13, N = 3SE +/- 0.61, N = 3SE +/- 0.11, N = 3SE +/- 0.04, N = 3SE +/- 0.05, N = 3SE +/- 0.42, N = 456.62187.9271.18103.8379.1256.6068.8151.1492.87196.63

Darmstadt Automotive Parallel Heterogeneous Suite

DAPHNE is the Darmstadt Automotive Parallel HeterogeNEous Benchmark Suite with OpenCL / CUDA / OpenMP test cases for these automotive benchmarks for evaluating programming models in context to vehicle autonomous driving capabilities. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgTest Cases Per Minute, More Is BetterDarmstadt Automotive Parallel Heterogeneous SuiteBackend: OpenCL - Kernel: NDT MappingGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX80160240320400SE +/- 0.67, N = 3SE +/- 0.87, N = 3SE +/- 2.08, N = 3SE +/- 1.38, N = 3SE +/- 2.24, N = 3SE +/- 0.61, N = 3SE +/- 2.54, N = 3SE +/- 0.82, N = 3SE +/- 2.01, N = 3SE +/- 1.41, N = 3333.47350.37339.21348.29345.44333.52320.97324.70349.12343.611. (CXX) g++ options: -O3 -m64 -std=c++11 -lcudadevrt -lcudart_static -lrt -lpthread -ldl

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: Training - Network: Mobilenet - Device: OpenCLGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX4080120160200SE +/- 0.06, N = 3SE +/- 0.19, N = 3SE +/- 0.08, N = 3SE +/- 0.11, N = 3SE +/- 0.06, N = 3SE +/- 0.01, N = 3SE +/- 0.07, N = 3SE +/- 0.01, N = 3SE +/- 0.05, N = 3SE +/- 0.21, N = 383.52187.7389.2899.82103.7980.47111.3973.2599.64198.37

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: VGG16 - Device: OpenCLGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX50100150200250SE +/- 0.22, N = 3SE +/- 0.64, N = 3SE +/- 0.87, N = 3SE +/- 0.42, N = 3SE +/- 0.18, N = 3SE +/- 0.21, N = 3SE +/- 0.10, N = 3SE +/- 0.06, N = 3SE +/- 0.10, N = 3SE +/- 0.54, N = 471.78237.2990.74131.3499.8872.2186.6164.53116.89248.79

clpeak

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

OpenBenchmarking.orgGFLOPS, More Is BetterclpeakOpenCL Test: Double-Precision DoubleGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX120240360480600SE +/- 0.23, N = 3SE +/- 1.30, N = 3SE +/- 0.11, N = 3SE +/- 0.60, N = 3SE +/- 0.38, N = 4SE +/- 0.03, N = 3SE +/- 0.02, N = 3SE +/- 0.02, N = 3SE +/- 0.06, N = 3SE +/- 1.32, N = 3150.68522.22197.23298.46223.60159.72172.49137.48242.70548.261. (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: Inception V3 - Device: OpenCLGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX80160240320400SE +/- 0.19, N = 3SE +/- 0.25, N = 3SE +/- 0.02, N = 3SE +/- 0.11, N = 3SE +/- 0.23, N = 3SE +/- 0.62, N = 3SE +/- 0.04, N = 3SE +/- 0.02, N = 3SE +/- 0.04, N = 3SE +/- 0.19, N = 3108.56353.54138.33190.14151.71109.50135.3197.83159.43355.85

Darmstadt Automotive Parallel Heterogeneous Suite

DAPHNE is the Darmstadt Automotive Parallel HeterogeNEous Benchmark Suite with OpenCL / CUDA / OpenMP test cases for these automotive benchmarks for evaluating programming models in context to vehicle autonomous driving capabilities. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgTest Cases Per Minute, More Is BetterDarmstadt Automotive Parallel Heterogeneous SuiteBackend: NVIDIA CUDA - Kernel: NDT MappingRTX 2080 TiGTX 1660 SUPERTITAN RTX130260390520650SE +/- 2.73, N = 3SE +/- 4.39, N = 3SE +/- 5.64, N = 3606.75563.13590.631. (CXX) g++ options: -O3 -m64 -std=c++11 -lcudadevrt -lcudart_static -lrt -lpthread -ldl

ArrayFire

ArrayFire is an GPU and CPU numeric processing library, this test uses the built-in CPU and OpenCL ArrayFire benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGFLOPS, More Is BetterArrayFire 3.7Test: BLAS OpenCLGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX11002200330044005500SE +/- 2.50, N = 4SE +/- 13.92, N = 4SE +/- 8.83, N = 4SE +/- 10.96, N = 4SE +/- 4.04, N = 4SE +/- 10.36, N = 4SE +/- 3.01, N = 4SE +/- 1.45, N = 4SE +/- 1.17, N = 4SE +/- 17.72, N = 42856.384836.622438.975091.862905.882826.161765.012457.734304.765040.581. (CXX) g++ options: -rdynamic

Darmstadt Automotive Parallel Heterogeneous Suite

DAPHNE is the Darmstadt Automotive Parallel HeterogeNEous Benchmark Suite with OpenCL / CUDA / OpenMP test cases for these automotive benchmarks for evaluating programming models in context to vehicle autonomous driving capabilities. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgTest Cases Per Minute, More Is BetterDarmstadt Automotive Parallel Heterogeneous SuiteBackend: NVIDIA CUDA - Kernel: Euclidean ClusterGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX30060090012001500SE +/- 8.38, N = 3SE +/- 0.89, N = 4SE +/- 15.93, N = 3SE +/- 2.36, N = 3SE +/- 4.73, N = 3SE +/- 1.10, N = 3SE +/- 0.96, N = 4SE +/- 2.99, N = 3SE +/- 7.67, N = 3SE +/- 2.28, N = 41253.431436.62976.751218.561231.441019.041466.24979.331204.771434.171. (CXX) g++ options: -O3 -m64 -std=c++11 -lcudadevrt -lcudart_static -lrt -lpthread -ldl

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 2.14ATPase Simulation - 327,506 AtomsGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX0.08120.16240.24360.32480.406SE +/- 0.00077, N = 3SE +/- 0.00046, N = 4SE +/- 0.00163, N = 4SE +/- 0.00174, N = 4SE +/- 0.00276, N = 4SE +/- 0.00291, N = 3SE +/- 0.00026, N = 4SE +/- 0.00170, N = 3SE +/- 0.00101, N = 4SE +/- 0.00134, N = 40.309570.190820.291380.224260.240220.335660.231770.360710.223000.19195

PlaidML

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

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: IMDB LSTM - Device: OpenCLGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX2004006008001000SE +/- 0.09, N = 4SE +/- 1.41, N = 5SE +/- 0.57, N = 4SE +/- 0.35, N = 4SE +/- 0.44, N = 4SE +/- 0.41, N = 4SE +/- 0.17, N = 4SE +/- 0.11, N = 4SE +/- 0.07, N = 4SE +/- 0.80, N = 5227.23753.75267.88398.82314.83228.46298.77203.08331.84775.69

Darmstadt Automotive Parallel Heterogeneous Suite

DAPHNE is the Darmstadt Automotive Parallel HeterogeNEous Benchmark Suite with OpenCL / CUDA / OpenMP test cases for these automotive benchmarks for evaluating programming models in context to vehicle autonomous driving capabilities. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgTest Cases Per Minute, More Is BetterDarmstadt Automotive Parallel Heterogeneous SuiteBackend: OpenCL - Kernel: Euclidean ClusterGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX5001000150020002500SE +/- 3.33, N = 5SE +/- 5.93, N = 5SE +/- 5.50, N = 4SE +/- 5.86, N = 5SE +/- 7.62, N = 5SE +/- 2.91, N = 5SE +/- 3.67, N = 5SE +/- 1.83, N = 4SE +/- 0.67, N = 5SE +/- 9.59, N = 52076.482268.231908.812345.382243.101976.412175.961928.882223.782279.141. (CXX) g++ options: -O3 -m64 -std=c++11 -lcudadevrt -lcudart_static -lrt -lpthread -ldl

MandelGPU

MandelGPU is an OpenCL benchmark and this test runs with the OpenCL rendering float4 kernel with a maximum of 4096 iterations. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSamples/sec, More Is BetterMandelGPU 1.3pts1OpenCL Device: GPUGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX100M200M300M400M500MSE +/- 339240.54, N = 6SE +/- 2765042.11, N = 10SE +/- 353641.55, N = 6SE +/- 528438.95, N = 8SE +/- 327094.24, N = 7SE +/- 4075144.18, N = 15SE +/- 173522.04, N = 7SE +/- 113731.50, N = 5SE +/- 459096.61, N = 7SE +/- 2829613.77, N = 10130290433.8448915216.6148357386.1231826397.8184077179.7121139566.8200846066.4113624502.0194875210.8480798376.61. (CC) gcc options: -O3 -lm -ftree-vectorize -funroll-loops -lglut -lOpenCL -lGL

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 select OpenCL, NVIDIA CUDA and OpenMP test binaries at the moment. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterRodinia 3.1Test: OpenCL Particle FilterGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX3691215SE +/- 0.012, N = 4SE +/- 0.009, N = 8SE +/- 0.092, N = 5SE +/- 0.018, N = 6SE +/- 0.019, N = 6SE +/- 0.058, N = 4SE +/- 0.009, N = 5SE +/- 0.026, N = 4SE +/- 0.006, N = 6SE +/- 0.008, N = 812.0024.41410.0716.4578.20511.77411.48213.1857.7914.2501. (CXX) g++ options: -m64 -lm -lcuda -lcudart -lcudadevrt -lcudart_static -lrt -lpthread -ldl

cl-mem

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

OpenBenchmarking.orgGB/s, More Is Bettercl-mem 2017-01-13Benchmark: ReadGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX120240360480600SE +/- 0.02, N = 5SE +/- 0.13, N = 8SE +/- 0.17, N = 6SE +/- 0.08, N = 6SE +/- 0.03, N = 6SE +/- 0.08, N = 5SE +/- 0.07, N = 7SE +/- 0.02, N = 4SE +/- 0.03, N = 6SE +/- 0.13, N = 9154.4545.7266.0229.6206.2165.3296.6144.6206.2567.71. (CC) gcc options: -O2 -flto -lOpenCL

OpenBenchmarking.orgGB/s, More Is Bettercl-mem 2017-01-13Benchmark: WriteGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX110220330440550SE +/- 0.02, N = 5SE +/- 0.21, N = 8SE +/- 0.14, N = 6SE +/- 0.09, N = 6SE +/- 0.03, N = 6SE +/- 0.20, N = 5SE +/- 0.36, N = 7SE +/- 0.15, N = 4SE +/- 0.03, N = 6SE +/- 0.97, N = 9148.1449.5245.9225.6199.5159.1240.7136.3198.2491.71. (CC) gcc options: -O2 -flto -lOpenCL

OpenBenchmarking.orgGB/s, More Is Bettercl-mem 2017-01-13Benchmark: CopyGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX70140210280350SE +/- 0.02, N = 5SE +/- 0.10, N = 8SE +/- 0.07, N = 6SE +/- 0.02, N = 6SE +/- 0.02, N = 6SE +/- 0.02, N = 5SE +/- 0.05, N = 7SE +/- 0.02, N = 4SE +/- 0.03, N = 6SE +/- 0.08, N = 9138.5324.0217.8207.4183.3145.0240.2125.9184.1322.71. (CC) gcc options: -O2 -flto -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: Yes - Mode: Inference - Network: Mobilenet - Device: OpenCLGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX6001200180024003000SE +/- 2.10, N = 6SE +/- 1.82, N = 7SE +/- 2.34, N = 5SE +/- 1.79, N = 7SE +/- 3.20, N = 7SE +/- 0.78, N = 6SE +/- 0.83, N = 7SE +/- 0.24, N = 6SE +/- 0.31, N = 7SE +/- 1.27, N = 8987.072751.851290.481665.721392.461053.491380.68910.911485.782856.83

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: Mobilenet - Device: OpenCLGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX5001000150020002500SE +/- 0.68, N = 7SE +/- 1.58, N = 8SE +/- 0.66, N = 8SE +/- 0.60, N = 8SE +/- 1.14, N = 8SE +/- 0.69, N = 7SE +/- 1.11, N = 8SE +/- 0.28, N = 7SE +/- 0.27, N = 8SE +/- 2.36, N = 8775.732406.161029.361154.131052.64810.501080.11716.821070.902544.67

FinanceBench

FinanceBench is a collection of financial program benchmarks with support for benchmarking on the GPU. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterFinanceBench 2016-06-06Benchmark: Monte-Carlo OpenCLGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX2004006008001000SE +/- 0.45, N = 7SE +/- 0.60, N = 8SE +/- 0.29, N = 8SE +/- 0.48, N = 7SE +/- 0.41, N = 7SE +/- 0.37, N = 8SE +/- 0.49, N = 8SE +/- 1.03, N = 7SE +/- 0.22, N = 8SE +/- 1.20, N = 8894.08319.91660.55921.68697.55749.29594.44841.19754.28277.231. (CXX) g++ options: -O3 -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 3.0.1Test: Masskrug - Acceleration: OpenCLGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX1.03732.07463.11194.14925.1865SE +/- 0.009, N = 8SE +/- 0.009, N = 9SE +/- 0.012, N = 8SE +/- 0.011, N = 8SE +/- 0.008, N = 8SE +/- 0.023, N = 7SE +/- 0.011, N = 8SE +/- 0.022, N = 7SE +/- 0.016, N = 8SE +/- 0.011, N = 83.1692.7553.2272.9742.9744.5433.0304.6102.9982.792

OpenBenchmarking.orgSeconds, Fewer Is BetterDarktable 3.0.1Test: Boat - Acceleration: OpenCLGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX0.971.942.913.884.85SE +/- 0.012, N = 8SE +/- 0.007, N = 10SE +/- 0.013, N = 8SE +/- 0.006, N = 9SE +/- 0.009, N = 9SE +/- 0.014, N = 8SE +/- 0.010, N = 9SE +/- 0.014, N = 7SE +/- 0.012, N = 8SE +/- 0.008, N = 93.5171.4923.0172.5462.7093.7642.6074.3112.7411.491

OpenBenchmarking.orgSeconds, Fewer Is BetterDarktable 3.0.1Test: Server Room - Acceleration: OpenCLGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX0.6441.2881.9322.5763.22SE +/- 0.002, N = 10SE +/- 0.002, N = 11SE +/- 0.002, N = 10SE +/- 0.003, N = 10SE +/- 0.004, N = 10SE +/- 0.004, N = 8SE +/- 0.002, N = 10SE +/- 0.017, N = 8SE +/- 0.001, N = 10SE +/- 0.002, N = 111.3010.7591.3981.0951.1122.7301.0822.8621.1660.767

clpeak

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

OpenBenchmarking.orgGIOPS, More Is BetterclpeakOpenCL Test: Integer Compute INTGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX3K6K9K12K15KSE +/- 10.83, N = 15SE +/- 23.37, N = 12SE +/- 8.22, N = 9SE +/- 7.00, N = 10SE +/- 6.03, N = 12SE +/- 1.81, N = 8SE +/- 6.44, N = 12SE +/- 8.78, N = 10SE +/- 0.30, N = 10SE +/- 169.21, N = 151275.1213629.371612.522430.551695.791306.514280.551145.142076.4513783.931. (CXX) g++ options: -O3 -rdynamic -lOpenCL

ArrayFire

ArrayFire is an GPU and CPU numeric processing library, this test uses the built-in CPU and OpenCL ArrayFire benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterArrayFire 3.7Test: Conjugate Gradient OpenCLGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX1.2152.433.6454.866.075SE +/- 0.003, N = 10SE +/- 0.005, N = 10SE +/- 0.006, N = 10SE +/- 0.002, N = 10SE +/- 0.004, N = 10SE +/- 0.002, N = 10SE +/- 0.001, N = 10SE +/- 0.002, N = 9SE +/- 0.001, N = 10SE +/- 0.001, N = 105.0001.6773.6223.3874.0774.9042.6425.4003.8141.6661. (CXX) g++ options: -rdynamic

ViennaCL

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

OpenBenchmarking.orgGFLOPS, More Is BetterViennaCL 1.4.2OpenCL LU FactorizationGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX20406080100SE +/- 0.32, N = 11SE +/- 0.39, N = 11SE +/- 0.25, N = 11SE +/- 0.21, N = 11SE +/- 0.23, N = 11SE +/- 0.29, N = 11SE +/- 0.37, N = 11SE +/- 0.20, N = 10SE +/- 0.38, N = 11SE +/- 0.57, N = 1161.6575.7964.5470.6966.2161.9468.1560.2069.1876.641. (CXX) g++ options: -rdynamic -lOpenCL

Mixbench

A benchmark suite for GPUs on mixed operational intensity kernels. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGFLOPS, More Is BetterMixbench 2020-06-23Backend: NVIDIA CUDA - Benchmark: Single PrecisionGTX 1060RTX 2080 TiGTX 1080GTX 1070GTX 1660 SUPERGTX 1070 TiTITAN RTX3K6K9K12K15KSE +/- 1.19, N = 9SE +/- 556.93, N = 15SE +/- 3.04, N = 11SE +/- 30.05, N = 15SE +/- 0.25, N = 13SE +/- 2.31, N = 11SE +/- 595.40, N = 154167.4114734.038182.726174.805440.746647.9415103.611. (CXX) g++ options: -lm -lstdc++ -lOpenCL -lrt -O2

clpeak

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

OpenBenchmarking.orgGBPS, More Is BetterclpeakOpenCL Test: Global Memory BandwidthGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX110220330440550SE +/- 0.04, N = 10SE +/- 0.46, N = 12SE +/- 0.13, N = 15SE +/- 0.11, N = 15SE +/- 0.04, N = 11SE +/- 0.01, N = 13SE +/- 0.16, N = 12SE +/- 0.02, N = 12SE +/- 0.01, N = 11SE +/- 0.05, N = 13147.66506.90264.74223.14197.20165.29276.35144.56198.18530.791. (CXX) g++ options: -O3 -rdynamic -lOpenCL

Mixbench

A benchmark suite for GPUs on mixed operational intensity kernels. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGIOPS, More Is BetterMixbench 2020-06-23Backend: NVIDIA CUDA - Benchmark: IntegerGTX 1060RTX 2080 TiGTX 1080GTX 1070GTX 1660 SUPERGTX 1070 TiTITAN RTX3K6K9K12K15KSE +/- 2.01, N = 9SE +/- 264.51, N = 15SE +/- 1.56, N = 11SE +/- 3.28, N = 11SE +/- 4.94, N = 15SE +/- 0.87, N = 11SE +/- 458.60, N = 151187.7214103.792326.091764.634866.611887.6114426.111. (CXX) g++ options: -lm -lstdc++ -lOpenCL -lrt -O2

OpenBenchmarking.orgGFLOPS, More Is BetterMixbench 2020-06-23Backend: NVIDIA CUDA - Benchmark: Double PrecisionGTX 1060RTX 2080 TiGTX 1080GTX 1070GTX 1660 SUPERGTX 1070 TiTITAN RTX90180270360450SE +/- 0.00, N = 9SE +/- 10.76, N = 15SE +/- 0.03, N = 11SE +/- 0.10, N = 11SE +/- 0.66, N = 15SE +/- 0.35, N = 11SE +/- 15.67, N = 15151.63409.46296.09225.05144.14240.92413.661. (CXX) g++ options: -lm -lstdc++ -lOpenCL -lrt -O2

OpenBenchmarking.orgGFLOPS, More Is BetterMixbench 2020-06-23Backend: NVIDIA CUDA - Benchmark: Half PrecisionGTX 1060RTX 2080 TiGTX 1080GTX 1070GTX 1660 SUPERGTX 1070 TiTITAN RTX7K14K21K28K35KSE +/- 0.02, N = 9SE +/- 601.15, N = 15SE +/- 0.10, N = 11SE +/- 0.02, N = 11SE +/- 15.42, N = 13SE +/- 0.07, N = 11SE +/- 939.79, N = 1575.7731492.24149.35113.3210862.90121.4232084.791. (CXX) g++ options: -lm -lstdc++ -lOpenCL -lrt -O2

clpeak

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

OpenBenchmarking.orgGFLOPS, More Is BetterclpeakOpenCL Test: Single-Precision FloatGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX3K6K9K12K15KSE +/- 76.28, N = 15SE +/- 177.79, N = 15SE +/- 62.62, N = 15SE +/- 104.59, N = 15SE +/- 112.12, N = 15SE +/- 36.45, N = 13SE +/- 43.47, N = 15SE +/- 48.39, N = 15SE +/- 3.15, N = 13SE +/- 206.22, N = 154110.7113536.255512.898218.626093.024472.774440.233874.986788.4014178.851. (CXX) g++ options: -O3 -rdynamic -lOpenCL

Mixbench

A benchmark suite for GPUs on mixed operational intensity kernels. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGFLOPS, More Is BetterMixbench 2020-06-23Backend: OpenCL - Benchmark: Single PrecisionGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX3K6K9K12K15KSE +/- 2.22, N = 13SE +/- 66.33, N = 15SE +/- 4.87, N = 13SE +/- 11.17, N = 14SE +/- 12.17, N = 15SE +/- 23.81, N = 15SE +/- 8.38, N = 13SE +/- 0.70, N = 11SE +/- 2.95, N = 12SE +/- 619.26, N = 154355.2816061.095844.908520.976476.924683.965462.594141.797018.9015032.471. (CXX) g++ options: -lm -lstdc++ -lOpenCL -lrt -O2

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 3.0.1Test: Server Rack - Acceleration: OpenCLGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX0.03690.07380.11070.14760.1845SE +/- 0.001, N = 13SE +/- 0.001, N = 13SE +/- 0.001, N = 15SE +/- 0.001, N = 13SE +/- 0.001, N = 15SE +/- 0.001, N = 13SE +/- 0.000, N = 13SE +/- 0.001, N = 15SE +/- 0.000, N = 13SE +/- 0.000, N = 130.1240.1000.1640.1110.1170.1620.1040.1630.1170.103

NeatBench

NeatBench is a benchmark of the cross-platform Neat Video software on the CPU and optional GPU (OpenCL / CUDA) support. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterNeatBench 5Acceleration: GPUGTX 1080GTX 1070GTX 980GTX 970TITAN RTX1122334455SE +/- 0.04, N = 13SE +/- 0.13, N = 13SE +/- 0.04, N = 13SE +/- 0.05, N = 13SE +/- 0.02, N = 1324.621.517.315.448.1

Mixbench

A benchmark suite for GPUs on mixed operational intensity kernels. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGIOPS, More Is BetterMixbench 2020-06-23Backend: OpenCL - Benchmark: IntegerGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX4K8K12K16K20KSE +/- 2.70, N = 14SE +/- 11.06, N = 14SE +/- 1.27, N = 13SE +/- 6.51, N = 15SE +/- 0.96, N = 13SE +/- 5.50, N = 15SE +/- 7.30, N = 13SE +/- 0.40, N = 13SE +/- 0.83, N = 14SE +/- 63.55, N = 151354.1416323.941711.032655.582019.081389.905432.401215.752157.3116979.991. (CXX) g++ options: -lm -lstdc++ -lOpenCL -lrt -O2

OpenBenchmarking.orgGFLOPS, More Is BetterMixbench 2020-06-23Backend: OpenCL - Benchmark: Double PrecisionGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX100200300400500SE +/- 0.23, N = 13SE +/- 0.56, N = 15SE +/- 0.12, N = 13SE +/- 0.15, N = 14SE +/- 0.06, N = 13SE +/- 0.18, N = 13SE +/- 0.22, N = 13SE +/- 0.16, N = 13SE +/- 0.08, N = 14SE +/- 1.13, N = 14150.48436.81197.44296.66224.82159.33144.30137.20241.99454.371. (CXX) g++ options: -lm -lstdc++ -lOpenCL -lrt -O2

FinanceBench

FinanceBench is a collection of financial program benchmarks with support for benchmarking on the GPU. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterFinanceBench 2016-06-06Benchmark: Black-Scholes OpenCLGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX48121620SE +/- 0.317, N = 15SE +/- 0.002, N = 14SE +/- 0.156, N = 15SE +/- 0.003, N = 15SE +/- 0.209, N = 15SE +/- 0.023, N = 15SE +/- 0.001, N = 14SE +/- 0.003, N = 15SE +/- 0.003, N = 15SE +/- 0.002, N = 1513.3406.0209.5966.9818.96812.10115.27114.1967.2985.7011. (CXX) g++ options: -O3 -lOpenCL

GPU Temperature Monitor

OpenBenchmarking.orgCelsiusGPU Temperature MonitorPhoronix Test Suite System MonitoringGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970GTX 1070 TiTITAN RTX1632486480Min: 32 / Avg: 52.77 / Max: 69Min: 29 / Avg: 56.11 / Max: 78Min: 30 / Avg: 70.66 / Max: 85Min: 28 / Avg: 61.17 / Max: 83Min: 29 / Avg: 59.81 / Max: 78Min: 31 / Avg: 65.22 / Max: 80Min: 33 / Avg: 55.48 / Max: 68Min: 33 / Avg: 52.58 / Max: 74Min: 32 / Avg: 45.46 / Max: 58Min: 35 / Avg: 55.61 / Max: 78

GPU Power Consumption Monitor

OpenBenchmarking.orgWattsGPU Power Consumption MonitorPhoronix Test Suite System MonitoringGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970TITAN RTX60120180240300Min: 6.24 / Avg: 64.43 / Max: 128.04Min: 5.74 / Avg: 124.11 / Max: 273.84Min: 15.33 / Avg: 131.28 / Max: 252.57Min: 6.47 / Avg: 92.36 / Max: 196.24Min: 6.84 / Avg: 82.21 / Max: 159.92Min: 15.1 / Avg: 102.77 / Max: 192.38Min: 10.68 / Avg: 67.65 / Max: 128.36Min: 15.21 / Avg: 95.21 / Max: 176.52Min: 24.02 / Avg: 126.58 / Max: 312.98

Meta Performance Per Watts

OpenBenchmarking.orgPerformance Per Watts, More Is BetterMeta Performance Per WattsPerformance Per WattsGTX 1060RTX 2080 TiGTX 980 TiGTX 1080GTX 1070GTX 980GTX 1660 SUPERGTX 970TITAN RTX2004006008001000280.521013.20327.28406.50348.12249.04497.00223.07962.08