GeForce RTX 2080 Ti Linux GPU Compute Perf

GeForce RTX 2080 Ti Linux 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 1809214-RA-GEFORCERT02
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GeForce GTX 980 Ti
September 20 2018
  1 Hour, 30 Minutes
GeForce GTX 1080 Ti
September 21 2018
  1 Hour, 26 Minutes
GeForce RTX 2080 Ti
September 20 2018
  1 Hour, 28 Minutes
Radeon RX Vega 64
September 21 2018
  30 Minutes
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  1 Hour, 13 Minutes

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GeForce RTX 2080 Ti

Processor: Intel Core i7-8086K @ 5.00GHz (6 Cores / 12 Threads), Motherboard: ASUS PRIME Z370-A (1002 BIOS), Chipset: Intel 8th Gen Core, Memory: 16384MB, Disk: 525GB SABRENT + 118GB INTEL SSDPEK1W120GA, Graphics: NVIDIA GeForce RTX 2080 Ti 11264MB (1350/7000MHz), Audio: Realtek ALC1220, Monitor: Acer B286HK, Network: Intel Connection

OS: Ubuntu 18.04, Kernel: 4.18.0-041800-generic (x86_64), Desktop: GNOME Shell 3.28.3, Display Server: X Server 1.19.6, Display Driver: NVIDIA 410.57, OpenGL: 4.6.0, OpenCL: OpenCL 1.2 CUDA 10.0.154, Compiler: GCC 7.3.0 + CUDA 10.0, File-System: ext4, Screen Resolution: 3840x2160

Compiler Notes: --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++ --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-as=/usr/bin/x86_64-linux-gnu-as --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-ld=/usr/bin/x86_64-linux-gnu-ld --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -v
Processor Notes: Scaling Governor: intel_pstate performance
OpenCL Notes: GPU Compute Cores: 4352
Python Notes: Python 2.7.15rc1 + Python 3.6.5
Security Notes: KPTI + __user pointer sanitization + Full generic retpoline IBPB IBRS_FW + SSB disabled via prctl and seccomp

GeForce GTX 980 Ti

Changed Graphics to NVIDIA GeForce GTX 980 Ti 6144MB (999/3505MHz).

OpenCL Change: GPU Compute Cores: 2816

GeForce GTX 1080 Ti

Changed Graphics to NVIDIA GeForce GTX 1080 Ti 11264MB (1480/5508MHz).

OpenCL Change: GPU Compute Cores: 3584

Radeon RX Vega 64

Processor: Intel Core i7-8086K @ 5.00GHz (6 Cores / 12 Threads), Motherboard: ASUS PRIME Z370-A (1002 BIOS), Chipset: Intel 8th Gen Core, Memory: 16384MB, Disk: 525GB SABRENT + 118GB INTEL SSDPEK1W120GA, Graphics: AMD Radeon RX Vega 8192MB, Audio: Realtek ALC1220, Monitor: Acer B286HK, Network: Intel Connection

OS: Ubuntu 18.04, Kernel: 4.18.0-041800-generic (x86_64), Desktop: GNOME Shell 3.28.3, Display Server: X Server 1.19.6, OpenGL: 4.5 Mesa 18.3.0-devel- padoka PPA (LLVM 8.0.0), OpenCL: OpenCL 2.1 AMD-APP (2679.0), Compiler: GCC 7.3.0, File-System: ext4, Screen Resolution: 3840x2160

Compiler Notes: --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++ --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-as=/usr/bin/x86_64-linux-gnu-as --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-ld=/usr/bin/x86_64-linux-gnu-ld --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -v
Processor Notes: Scaling Governor: intel_pstate performance
Python Notes: Python 2.7.15rc1 + Python 3.6.5
Security Notes: KPTI + __user pointer sanitization + Full generic retpoline IBPB IBRS_FW + SSB disabled via prctl and seccomp

GeForce RTX 2080 Ti Linux GPU Compute PerfProcessorMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelDesktopDisplay ServerDisplay DriverOpenGLOpenCLCompilerFile-SystemScreen ResolutionGeForce RTX 2080 TiGeForce GTX 980 TiGeForce GTX 1080 TiRadeon RX Vega 64Intel Core i7-8086K @ 5.00GHz (6 Cores / 12 Threads)ASUS PRIME Z370-A (1002 BIOS)Intel 8th Gen Core16384MB525GB SABRENT + 118GB INTEL SSDPEK1W120GANVIDIA GeForce RTX 2080 Ti 11264MB (1350/7000MHz)Realtek ALC1220Acer B286HKIntel ConnectionUbuntu 18.044.18.0-041800-generic (x86_64)GNOME Shell 3.28.3X Server 1.19.6NVIDIA 410.574.6.0OpenCL 1.2 CUDA 10.0.154GCC 7.3.0 + CUDA 10.0ext43840x2160NVIDIA GeForce GTX 980 Ti 6144MB (999/3505MHz)NVIDIA GeForce GTX 1080 Ti 11264MB (1480/5508MHz)AMD Radeon RX Vega 8192MB4.5 Mesa 18.3.0-devel- padoka PPA (LLVM 8.0.0)OpenCL 2.1 AMD-APP (2679.0)GCC 7.3.0OpenBenchmarking.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++ --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-as=/usr/bin/x86_64-linux-gnu-as --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-ld=/usr/bin/x86_64-linux-gnu-ld --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -v Processor Details- Scaling Governor: intel_pstate performanceOpenCL Details- GeForce RTX 2080 Ti: GPU Compute Cores: 4352- GeForce GTX 980 Ti: GPU Compute Cores: 2816- GeForce GTX 1080 Ti: GPU Compute Cores: 3584Python Details- Python 2.7.15rc1 + Python 3.6.5Security Details- KPTI + __user pointer sanitization + Full generic retpoline IBPB IBRS_FW + SSB disabled via prctl and seccomp

GeForce RTX 2080 TiGeForce GTX 980 TiGeForce GTX 1080 TiRadeon RX Vega 64Result OverviewPhoronix Test Suite100%167%234%301%clpeakRodiniaDarktableSHOC Scalable HeterOgeneous ComputingLuxMarkcl-mem

GeForce RTX 2080 Ti Linux GPU Compute Perfdarktable: Boat - OpenCLdarktable: Server Room - OpenCLshoc: OpenCL - MD5 Hashrodinia: OpenCL Myocyteshoc: OpenCL - Texture Read Bandwidthcuda-mini-nbody: Originalshoc: OpenCL - Max SP Flopsparboil: OpenCL LBMluxmark: GPU - Microphoneluxmark: GPU - Luxball HDRindigobench: Supercarluxmark: GPU - Hotelrodinia: OpenCL Particle Filterfinancebench: Monte-Carlo OpenCLindigobench: Bedroomcl-mem: Copycl-mem: Readshoc: OpenCL - FFT SPclpeak: Global Memory Bandwidthaskap: Griddingcl-mem: Writedarktable: Server Rack - OpenCLdarktable: Masskrug - OpenCLclpeak: Integer Compute INTclpeak: Single-Precision Floatparboil: OpenCL TPACFv-ray: CUDA GPUaskap: DegriddingGeForce RTX 2080 TiGeForce GTX 980 TiGeForce GTX 1080 TiRadeon RX Vega 641.720.7434.8931.55117110.69165695.43288504241629.7991654.413008.714545441452505166414430.114.1714515154950.6352.35364523.351.539.1852.6035234.85620614.12110921677912.12388110.086763.9121726472326386842390.184.67161453461.3780.85170112.371.0419.6836.1159520.611324014.20137942139817.6256385.036405.33318338982330119273360.134.443272108620.8269.082218814.504.9416.28113.95424336662213979243573780.196.40250112778OpenBenchmarking.org

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 2.4.2Test: Boat - Acceleration: OpenCLGeForce RTX 2080 TiGeForce GTX 980 TiGeForce GTX 1080 TiRadeon RX Vega 6448121620SE +/- 0.01, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 31.723.352.3714.50

LuxMark

MinAvgMaxGeForce RTX 2080 Ti70.1333.4344.6GeForce GTX 980 Ti109.9254.6264.5GeForce GTX 1080 Ti47.4277.7288.4OpenBenchmarking.orgWatts, Fewer Is BetterLuxMark 3.1System Power Consumption Monitor80160240320400

MinAvgMaxGeForce RTX 2080 Ti56.4329.6343.2GeForce GTX 980 Ti157.7235.3241.7GeForce GTX 1080 Ti48.2242.0248.1Radeon RX Vega 6449.6332.9342.2OpenBenchmarking.orgWatts, Fewer Is BetterLuxMark 3.1System Power Consumption Monitor80160240320400

IndigoBench

MinAvgMaxGeForce RTX 2080 Ti57.6229.1327.5GeForce GTX 980 Ti74.6187.9255.5GeForce GTX 1080 Ti48.1190.2264.2OpenBenchmarking.orgWatts, Fewer Is BetterIndigoBench 4.0.64System Power Consumption Monitor80160240320400

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 2.4.2Test: Server Room - Acceleration: OpenCLGeForce RTX 2080 TiGeForce GTX 980 TiGeForce GTX 1080 TiRadeon RX Vega 641.11152.2233.33454.4465.5575SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 30.741.531.044.94

SHOC Scalable HeterOgeneous Computing

MinAvgMaxGeForce RTX 2080 Ti54.1219.5338.5GeForce GTX 980 Ti127.5192.0295.8GeForce GTX 1080 Ti88.9199.4314.5OpenBenchmarking.orgWatts, Fewer Is BetterSHOC Scalable HeterOgeneous Computing 2015-11-10System Power Consumption Monitor80160240320400

MinAvgMaxGeForce RTX 2080 Ti56.8237.5291.0GeForce GTX 980 Ti50.2179.2218.7GeForce GTX 1080 Ti96.5189.0209.9Radeon RX Vega 6453.2208.7281.3OpenBenchmarking.orgWatts, Fewer Is BetterSHOC Scalable HeterOgeneous Computing 2015-11-10System Power Consumption Monitor70140210280350

Chaos Group V-RAY

MinAvgMaxGeForce RTX 2080 Ti58.4251.9284.0GeForce GTX 980 Ti79.8216.2234.2GeForce GTX 1080 Ti50.4215.2234.4OpenBenchmarking.orgWatts, Fewer Is BetterChaos Group V-RAY 1.1.0System Power Consumption Monitor70140210280350

LuxMark

MinAvgMaxGeForce RTX 2080 Ti73.9325.8337.2GeForce GTX 980 Ti86.7234.9240.0GeForce GTX 1080 Ti108.2234.6242.0OpenBenchmarking.orgWatts, Fewer Is BetterLuxMark 3.1System Power Consumption Monitor80160240320400

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 HashGeForce RTX 2080 TiGeForce GTX 980 TiGeForce GTX 1080 TiRadeon RX Vega 64816243240SE +/- 0.39, N = 3SE +/- 0.00, N = 3SE +/- 0.07, N = 3SE +/- 0.01, N = 334.899.1819.6816.28-std=c++14 -lcudadevrt -lcudart_static -lpthread -ldl -lcufft-std=c++14 -lcudadevrt -lcudart_static -lpthread -ldl -lcufft-std=c++14 -lcudadevrt -lcudart_static -lpthread -ldl -lcufft-lSHOCCommonMPI -lSHOCCommonOpenCL -lOpenCL -pthread -lmpi_cxx -lmpi1. (CXX) g++ options: -O2 -lSHOCCommon -lrt

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 MyocyteGeForce RTX 2080 TiGeForce GTX 980 TiGeForce GTX 1080 TiRadeon RX Vega 64306090120150SE +/- 0.08, N = 3SE +/- 0.17, N = 3SE +/- 0.26, N = 3SE +/- 0.62, N = 331.5552.6036.11113.951. (CXX) g++ options: -O2 -lOpenCL

IndigoBench

MinAvgMaxGeForce RTX 2080 Ti119.4231.2322.7GeForce GTX 980 Ti95.2185.1237.0GeForce GTX 1080 Ti90.4191.9248.6OpenBenchmarking.orgWatts, Fewer Is BetterIndigoBench 4.0.64System Power Consumption Monitor80160240320400

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.orgGB/s, More Is BetterSHOC Scalable HeterOgeneous Computing 2015-11-10Target: OpenCL - Benchmark: Texture Read BandwidthGeForce RTX 2080 TiGeForce GTX 980 TiGeForce GTX 1080 TiRadeon RX Vega 6430060090012001500SE +/- 2.71, N = 3SE +/- 0.31, N = 3SE +/- 2.34, N = 3SE +/- 0.32, N = 31171352595424-std=c++14 -lcudadevrt -lcudart_static -lpthread -ldl -lcufft-std=c++14 -lcudadevrt -lcudart_static -lpthread -ldl -lcufft-std=c++14 -lcudadevrt -lcudart_static -lpthread -ldl -lcufft-lSHOCCommonMPI -lSHOCCommonOpenCL -lOpenCL -pthread -lmpi_cxx -lmpi1. (CXX) g++ options: -O2 -lSHOCCommon -lrt

CUDA Mini-Nbody

OpenBenchmarking.orgSeconds, Fewer Is BetterCUDA Mini-Nbody 2015-11-10Test: OriginalGeForce RTX 2080 TiGeForce GTX 980 TiGeForce GTX 1080 Ti816243240SE +/- 0.05, N = 3SE +/- 0.34, N = 3SE +/- 0.02, N = 310.6934.8520.61

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 FlopsGeForce RTX 2080 TiGeForce GTX 980 TiGeForce GTX 1080 Ti4K8K12K16K20KSE +/- 128.82, N = 3SE +/- 15.55, N = 3SE +/- 68.74, N = 3165696206132401. (CXX) g++ options: -O2 -lSHOCCommon -std=c++14 -lcudadevrt -lcudart_static -lrt -lpthread -ldl -lcufft

Parboil

The Parboil Benchmarks from the IMPACT Research Group at University of Illinois are a set of throughput computing applications for looking at computing architecture and compilers. Parboil test-cases support OpenMP, OpenCL, and CUDA multi-processing environments. However, at this time the test profile is just making use of the OpenMP and OpenCL test workloads. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterParboil 2.5Test: OpenCL LBMGeForce RTX 2080 TiGeForce GTX 980 TiGeForce GTX 1080 Ti48121620SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.02, N = 35.4314.1214.201. (CXX) g++ options: -lm -lpthread -lgomp -O3 -ffast-math -fopenmp

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: MicrophoneGeForce RTX 2080 TiGeForce GTX 980 TiGeForce GTX 1080 Ti6K12K18K24K30KSE +/- 39.34, N = 3SE +/- 43.50, N = 3SE +/- 19.17, N = 3288501109213794

OpenBenchmarking.orgScore, More Is BetterLuxMark 3.1OpenCL Device: GPU - Scene: Luxball HDRGeForce RTX 2080 TiGeForce GTX 980 TiGeForce GTX 1080 TiRadeon RX Vega 649K18K27K36K45KSE +/- 114.33, N = 3SE +/- 66.34, N = 3SE +/- 38.00, N = 3SE +/- 497.89, N = 342416167792139833666

SHOC Scalable HeterOgeneous Computing

OpenBenchmarking.orgGB/s Per Watt, More Is BetterSHOC Scalable HeterOgeneous Computing 2015-11-10Target: OpenCL - Benchmark: Texture Read BandwidthGeForce RTX 2080 TiGeForce GTX 980 TiGeForce GTX 1080 TiRadeon RX Vega 641.10932.21863.32794.43725.54654.931.973.152.03

IndigoBench

This is a test of Indigo Renderer's IndigoBench benchmark. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgM samples/s, More Is BetterIndigoBench 4.0.64Scene: SupercarGeForce RTX 2080 TiGeForce GTX 980 TiGeForce GTX 1080 Ti714212835SE +/- 0.02, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 329.7912.1217.62

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: HotelGeForce RTX 2080 TiGeForce GTX 980 TiGeForce GTX 1080 Ti2K4K6K8K10KSE +/- 40.67, N = 3SE +/- 10.00, N = 3SE +/- 15.33, N = 3916538815638

SHOC Scalable HeterOgeneous Computing

OpenBenchmarking.orgGFLOPS Per Watt, More Is BetterSHOC Scalable HeterOgeneous Computing 2015-11-10Target: OpenCL - Benchmark: Max SP FlopsGeForce RTX 2080 TiGeForce GTX 980 TiGeForce GTX 1080 Ti2040608010075.5032.3266.40

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 FilterGeForce RTX 2080 TiGeForce GTX 980 TiGeForce GTX 1080 Ti3691215SE +/- 0.03, N = 3SE +/- 0.07, N = 3SE +/- 0.08, N = 34.4110.085.031. (CXX) g++ options: -O2 -lOpenCL

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 OpenCLGeForce RTX 2080 TiGeForce GTX 980 TiGeForce GTX 1080 Ti150300450600750SE +/- 1.40, N = 3SE +/- 1.65, N = 3SE +/- 0.34, N = 33006766401. (CXX) g++ options: -O3 -lOpenCL

IndigoBench

This is a test of Indigo Renderer's IndigoBench benchmark. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgM samples/s, More Is BetterIndigoBench 4.0.64Scene: BedroomGeForce RTX 2080 TiGeForce GTX 980 TiGeForce GTX 1080 Ti246810SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 38.713.915.33

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: CopyGeForce RTX 2080 TiGeForce GTX 980 TiGeForce GTX 1080 TiRadeon RX Vega 64100200300400500SE +/- 0.17, N = 3SE +/- 0.00, N = 3SE +/- 0.15, N = 3SE +/- 0.03, N = 34542173182211. (CC) gcc options: -O2 -flto -lOpenCL

OpenBenchmarking.orgGB/s, More Is Bettercl-mem 2017-01-13Benchmark: ReadGeForce RTX 2080 TiGeForce GTX 980 TiGeForce GTX 1080 TiRadeon RX Vega 64120240360480600SE +/- 0.46, N = 3SE +/- 0.09, N = 3SE +/- 0.50, N = 3SE +/- 0.07, N = 35442643383971. (CC) gcc options: -O2 -flto -lOpenCL

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 SPGeForce RTX 2080 TiGeForce GTX 980 TiGeForce GTX 1080 TiRadeon RX Vega 6430060090012001500SE +/- 8.98, N = 3SE +/- 3.37, N = 3SE +/- 3.61, N = 3SE +/- 2.70, N = 31452723982924-std=c++14 -lcudadevrt -lcudart_static -lpthread -ldl -lcufft-std=c++14 -lcudadevrt -lcudart_static -lpthread -ldl -lcufft-std=c++14 -lcudadevrt -lcudart_static -lpthread -ldl -lcufft-lSHOCCommonMPI -lSHOCCommonOpenCL -lOpenCL -pthread -lmpi_cxx -lmpi1. (CXX) g++ options: -O2 -lSHOCCommon -lrt

IndigoBench

OpenBenchmarking.orgM samples/s Per Watt, More Is BetterIndigoBench 4.0.64Scene: BedroomGeForce RTX 2080 TiGeForce GTX 980 TiGeForce GTX 1080 Ti0.0090.0180.0270.0360.0450.040.020.03

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 BandwidthGeForce RTX 2080 TiGeForce GTX 980 TiGeForce GTX 1080 TiRadeon RX Vega 64110220330440550SE +/- 0.84, N = 3SE +/- 0.45, N = 3SE +/- 0.64, N = 3SE +/- 0.01, N = 3505263330357

ASKAP tConvolveCuda

This is a CUDA benchmark of ATNF's ASKAP Benchmark with currently using the tConvolveCuda sub-test. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMillion Grid Points Per Second, More Is BetterASKAP tConvolveCuda 2015-11-10Processing: GriddingGeForce RTX 2080 TiGeForce GTX 980 TiGeForce GTX 1080 Ti4K8K12K16K20KSE +/- 95.43, N = 3SE +/- 175.40, N = 3166418684119271. (CXX) g++ options: -fPIC -O3 -m64 -std=c++14 -lcudadevrt -lcudart_static -lrt -lpthread -ldl

LuxMark

OpenBenchmarking.orgScore Per Watt, More Is BetterLuxMark 3.1OpenCL Device: GPU - Scene: MicrophoneGeForce RTX 2080 TiGeForce GTX 980 TiGeForce GTX 1080 Ti2040608010088.5647.2258.81

IndigoBench

OpenBenchmarking.orgM samples/s Per Watt, More Is BetterIndigoBench 4.0.64Scene: SupercarGeForce RTX 2080 TiGeForce GTX 980 TiGeForce GTX 1080 Ti0.02930.05860.08790.11720.14650.130.070.09

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: WriteGeForce RTX 2080 TiGeForce GTX 980 TiGeForce GTX 1080 TiRadeon RX Vega 64100200300400500SE +/- 1.67, N = 3SE +/- 0.03, N = 3SE +/- 0.12, N = 3SE +/- 0.87, N = 34432393363781. (CC) gcc options: -O2 -flto -lOpenCL

LuxMark

OpenBenchmarking.orgScore Per Watt, More Is BetterLuxMark 3.1OpenCL Device: GPU - Scene: Luxball HDRGeForce RTX 2080 TiGeForce GTX 980 TiGeForce GTX 1080 TiRadeon RX Vega 64306090120150128.6871.3188.42101.12

OpenBenchmarking.orgScore Per Watt, More Is BetterLuxMark 3.1OpenCL Device: GPU - Scene: HotelGeForce RTX 2080 TiGeForce GTX 980 TiGeForce GTX 1080 Ti61218243027.4915.2420.30

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 2.4.2Test: Server Rack - Acceleration: OpenCLGeForce RTX 2080 TiGeForce GTX 980 TiGeForce GTX 1080 TiRadeon RX Vega 640.04280.08560.12840.17120.214SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 30.110.180.130.19

OpenBenchmarking.orgSeconds, Fewer Is BetterDarktable 2.4.2Test: Masskrug - Acceleration: OpenCLGeForce RTX 2080 TiGeForce GTX 980 TiGeForce GTX 1080 TiRadeon RX Vega 64246810SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.02, N = 3SE +/- 0.00, N = 34.174.674.446.40

System Power Consumption Monitor

MinAvgMaxGeForce RTX 2080 Ti53.6218.4344.6GeForce GTX 980 Ti50.0190.3325.3GeForce GTX 1080 Ti47.2198.5314.5OpenBenchmarking.orgWattsSystem Power Consumption MonitorPhoronix Test Suite System Monitoring80160240320400

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 INTGeForce RTX 2080 TiGeForce GTX 980 TiGeForce GTX 1080 TiRadeon RX Vega 643K6K9K12K15KSE +/- 870.04, N = 3SE +/- 10.92, N = 3SE +/- 88.57, N = 3SE +/- 1.12, N = 314515161432722501

OpenBenchmarking.orgGFLOPS, More Is BetterclpeakOpenCL Test: Single-Precision FloatGeForce RTX 2080 TiGeForce GTX 980 TiGeForce GTX 1080 TiRadeon RX Vega 643K6K9K12K15KSE +/- 1135.64, N = 3SE +/- 234.92, N = 3SE +/- 796.36, N = 3SE +/- 4.98, N = 31549553461086212778

Parboil

The Parboil Benchmarks from the IMPACT Research Group at University of Illinois are a set of throughput computing applications for looking at computing architecture and compilers. Parboil test-cases support OpenMP, OpenCL, and CUDA multi-processing environments. However, at this time the test profile is just making use of the OpenMP and OpenCL test workloads. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterParboil 2.5Test: OpenCL TPACFGeForce RTX 2080 TiGeForce GTX 980 TiGeForce GTX 1080 Ti0.30830.61660.92491.23321.5415SE +/- 0.03, N = 3SE +/- 0.04, N = 3SE +/- 0.07, N = 30.631.370.821. (CXX) g++ options: -lm -lpthread -lgomp -O3 -ffast-math -fopenmp

Chaos Group V-RAY

This is a test of Chaos Group's V-RAY benchmark. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterChaos Group V-RAY 1.1.0Mode: CUDA GPUGeForce RTX 2080 TiGeForce GTX 980 TiGeForce GTX 1080 Ti20406080100SE +/- 0.02, N = 3SE +/- 3.22, N = 3SE +/- 3.17, N = 352.3580.8569.08

ASKAP tConvolveCuda

This is a CUDA benchmark of ATNF's ASKAP Benchmark with currently using the tConvolveCuda sub-test. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMillion Grid Points Per Second, More Is BetterASKAP tConvolveCuda 2015-11-10Processing: DegriddingGeForce RTX 2080 TiGeForce GTX 980 TiGeForce GTX 1080 Ti8K16K24K32K40KSE +/- 1584.87, N = 3SE +/- 369.80, N = 33645217011221881. (CXX) g++ options: -fPIC -O3 -m64 -std=c++14 -lcudadevrt -lcudart_static -lrt -lpthread -ldl

GeForce RTX 2080 Ti

Processor: Intel Core i7-8086K @ 5.00GHz (6 Cores / 12 Threads), Motherboard: ASUS PRIME Z370-A (1002 BIOS), Chipset: Intel 8th Gen Core, Memory: 16384MB, Disk: 525GB SABRENT + 118GB INTEL SSDPEK1W120GA, Graphics: NVIDIA GeForce RTX 2080 Ti 11264MB (1350/7000MHz), Audio: Realtek ALC1220, Monitor: Acer B286HK, Network: Intel Connection

OS: Ubuntu 18.04, Kernel: 4.18.0-041800-generic (x86_64), Desktop: GNOME Shell 3.28.3, Display Server: X Server 1.19.6, Display Driver: NVIDIA 410.57, OpenGL: 4.6.0, OpenCL: OpenCL 1.2 CUDA 10.0.154, Compiler: GCC 7.3.0 + CUDA 10.0, File-System: ext4, Screen Resolution: 3840x2160

Compiler Notes: --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++ --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-as=/usr/bin/x86_64-linux-gnu-as --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-ld=/usr/bin/x86_64-linux-gnu-ld --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -v
Processor Notes: Scaling Governor: intel_pstate performance
OpenCL Notes: GPU Compute Cores: 4352
Python Notes: Python 2.7.15rc1 + Python 3.6.5
Security Notes: KPTI + __user pointer sanitization + Full generic retpoline IBPB IBRS_FW + SSB disabled via prctl and seccomp

Testing initiated at 20 September 2018 19:34 by user phoronix.

GeForce GTX 980 Ti

Processor: Intel Core i7-8086K @ 5.00GHz (6 Cores / 12 Threads), Motherboard: ASUS PRIME Z370-A (1002 BIOS), Chipset: Intel 8th Gen Core, Memory: 16384MB, Disk: 525GB SABRENT + 118GB INTEL SSDPEK1W120GA, Graphics: NVIDIA GeForce GTX 980 Ti 6144MB (999/3505MHz), Audio: Realtek ALC1220, Monitor: Acer B286HK, Network: Intel Connection

OS: Ubuntu 18.04, Kernel: 4.18.0-041800-generic (x86_64), Desktop: GNOME Shell 3.28.3, Display Server: X Server 1.19.6, Display Driver: NVIDIA 410.57, OpenGL: 4.6.0, OpenCL: OpenCL 1.2 CUDA 10.0.154, Compiler: GCC 7.3.0 + CUDA 10.0, File-System: ext4, Screen Resolution: 3840x2160

Compiler Notes: --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++ --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-as=/usr/bin/x86_64-linux-gnu-as --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-ld=/usr/bin/x86_64-linux-gnu-ld --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -v
Processor Notes: Scaling Governor: intel_pstate performance
OpenCL Notes: GPU Compute Cores: 2816
Python Notes: Python 2.7.15rc1 + Python 3.6.5
Security Notes: KPTI + __user pointer sanitization + Full generic retpoline IBPB IBRS_FW + SSB disabled via prctl and seccomp

Testing initiated at 20 September 2018 21:31 by user phoronix.

GeForce GTX 1080 Ti

Processor: Intel Core i7-8086K @ 5.00GHz (6 Cores / 12 Threads), Motherboard: ASUS PRIME Z370-A (1002 BIOS), Chipset: Intel 8th Gen Core, Memory: 16384MB, Disk: 525GB SABRENT + 118GB INTEL SSDPEK1W120GA, Graphics: NVIDIA GeForce GTX 1080 Ti 11264MB (1480/5508MHz), Audio: Realtek ALC1220, Monitor: Acer B286HK, Network: Intel Connection

OS: Ubuntu 18.04, Kernel: 4.18.0-041800-generic (x86_64), Desktop: GNOME Shell 3.28.3, Display Server: X Server 1.19.6, Display Driver: NVIDIA 410.57, OpenGL: 4.6.0, OpenCL: OpenCL 1.2 CUDA 10.0.154, Compiler: GCC 7.3.0 + CUDA 10.0, File-System: ext4, Screen Resolution: 3840x2160

Compiler Notes: --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++ --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-as=/usr/bin/x86_64-linux-gnu-as --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-ld=/usr/bin/x86_64-linux-gnu-ld --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -v
Processor Notes: Scaling Governor: intel_pstate performance
OpenCL Notes: GPU Compute Cores: 3584
Python Notes: Python 2.7.15rc1 + Python 3.6.5
Security Notes: KPTI + __user pointer sanitization + Full generic retpoline IBPB IBRS_FW + SSB disabled via prctl and seccomp

Testing initiated at 21 September 2018 05:38 by user phoronix.

Radeon RX Vega 64

Processor: Intel Core i7-8086K @ 5.00GHz (6 Cores / 12 Threads), Motherboard: ASUS PRIME Z370-A (1002 BIOS), Chipset: Intel 8th Gen Core, Memory: 16384MB, Disk: 525GB SABRENT + 118GB INTEL SSDPEK1W120GA, Graphics: AMD Radeon RX Vega 8192MB, Audio: Realtek ALC1220, Monitor: Acer B286HK, Network: Intel Connection

OS: Ubuntu 18.04, Kernel: 4.18.0-041800-generic (x86_64), Desktop: GNOME Shell 3.28.3, Display Server: X Server 1.19.6, OpenGL: 4.5 Mesa 18.3.0-devel- padoka PPA (LLVM 8.0.0), OpenCL: OpenCL 2.1 AMD-APP (2679.0), Compiler: GCC 7.3.0, File-System: ext4, Screen Resolution: 3840x2160

Compiler Notes: --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++ --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-as=/usr/bin/x86_64-linux-gnu-as --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-ld=/usr/bin/x86_64-linux-gnu-ld --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -v
Processor Notes: Scaling Governor: intel_pstate performance
Python Notes: Python 2.7.15rc1 + Python 3.6.5
Security Notes: KPTI + __user pointer sanitization + Full generic retpoline IBPB IBRS_FW + SSB disabled via prctl and seccomp

Testing initiated at 21 September 2018 08:51 by user phoronix.