Test

2 x Intel Xeon E5-2682 v4 testing with a Supermicro SYS-7048GR-TR X10DRG-Q v1.10 (3.2 BIOS) and MSI NVIDIA GeForce RTX 3090 24GB on Ubuntu 22.04 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 2404173-NE-TEST4784533
Jump To Table - Results

View

Do Not Show Noisy Results
Do Not Show Results With Incomplete Data
Do Not Show Results With Little Change/Spread
List Notable Results
Show Result Confidence Charts

Limit displaying results to tests within:

BLAS (Basic Linear Algebra Sub-Routine) Tests 3 Tests
C++ Boost Tests 2 Tests
CPU Massive 5 Tests
Creator Workloads 4 Tests
HPC - High Performance Computing 9 Tests
Machine Learning 6 Tests
Multi-Core 7 Tests
NVIDIA GPU Compute 21 Tests
OpenCL 6 Tests
OpenMPI Tests 2 Tests
Python Tests 3 Tests
Renderers 3 Tests
Scientific Computing 2 Tests
Server CPU Tests 2 Tests
Common Workstation Benchmarks 2 Tests

Statistics

Show Overall Harmonic Mean(s)
Show Overall Geometric Mean
Show Geometric Means Per-Suite/Category
Show Wins / Losses Counts (Pie Chart)
Normalize Results
Remove Outliers Before Calculating Averages

Graph Settings

Force Line Graphs Where Applicable
Convert To Scalar Where Applicable
Disable Color Branding
Prefer Vertical Bar Graphs

Multi-Way Comparison

Condense Multi-Option Tests Into Single Result Graphs

Table

Show Detailed System Result Table

Run Management

Highlight
Result
Hide
Result
Result
Identifier
View Logs
Performance Per
Dollar
Date
Run
  Test
  Duration
test
April 16
  1 Minute
Test
April 17
 
MSI NVIDIA GeForce RTX 3090
April 17
  13 Hours, 11 Minutes
Invert Hiding All Results Option
  4 Hours, 24 Minutes

Only show results where is faster than
Only show results matching title/arguments (delimit multiple options with a comma):
Do not show results matching title/arguments (delimit multiple options with a comma):

test

Processor: 2 x Intel Xeon E5-2682 v4 @ 3.00GHz (32 Cores / 64 Threads), Motherboard: Supermicro X10DRG-Q v1.10 (3.2 BIOS), Chipset: Intel Xeon E7 v4/Xeon, Memory: 32GB, Disk: 1000GB Samsung SSD 870 + 4001GB Western Digital WD40EFPX-68C, Graphics: MSI NVIDIA GeForce RTX 3090 24GB, Audio: Realtek ALC888-VD, Network: 2 x Intel I350

OS: Ubuntu 22.04, Kernel: 5.15.0-102-generic (x86_64), Display Server: X Server 1.21.1.3, Display Driver: NVIDIA, Compiler: GCC 11.4.0 + Clang 14.0.0-1ubuntu1.1 + LLVM 14.0.0 + CUDA 12.4, File-System: ext4, Screen Resolution: 1024x768

Kernel Notes: Transparent Huge Pages: madvise
Environment Notes: NVM_CD_FLAGS=-q
Processor Notes: Scaling Governor: intel_cpufreq schedutil - CPU Microcode: 0xb000040
Python Notes: Python 3.10.14
Security Notes: gather_data_sampling: Not affected + itlb_multihit: KVM: Mitigation of VMX disabled + l1tf: Mitigation of PTE Inversion; VMX: conditional cache flushes SMT vulnerable + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Mitigation of PTI + mmio_stale_data: Mitigation of Clear buffers; SMT vulnerable + retbleed: Not affected + spec_rstack_overflow: 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 Retpolines IBPB: conditional IBRS_FW STIBP: conditional RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Mitigation of Clear buffers; SMT vulnerable

Test

Processor: 2 x Intel Xeon E5-2682 v4 @ 3.00GHz (32 Cores / 64 Threads), Motherboard: Supermicro SYS-7048GR-TR X10DRG-Q v1.10 (3.2 BIOS), Chipset: Intel Xeon E7 v4/Xeon, Memory: 2 x 16GB DDR4-2400MT/s, Disk: 1000GB Samsung SSD 870 + 4001GB Western Digital WD40EFPX-68C, Graphics: MSI NVIDIA GeForce RTX 3090 24GB, Audio: Realtek ALC888-VD, Network: 2 x Intel I350

OS: Ubuntu 22.04, Kernel: 5.15.0-102-generic (x86_64), Display Server: X Server 1.21.1.3, Display Driver: NVIDIA, OpenCL: OpenCL 3.0 CUDA 12.4.89, Compiler: GCC 11.4.0 + Clang 14.0.0-1ubuntu1.1 + LLVM 14.0.0 + CUDA 12.4, File-System: ext4, Screen Resolution: 1024x768

Kernel Notes: Transparent Huge Pages: madvise
Environment Notes: NVM_CD_FLAGS=-q
Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-cet --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++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-link-serialization=2 --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-11-XeT9lY/gcc-11-11.4.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-11-XeT9lY/gcc-11-11.4.0/debian/tmp-gcn/usr --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-build-config=bootstrap-lto-lean --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 Notes: Scaling Governor: intel_cpufreq schedutil - CPU Microcode: 0xb000040
Security Notes: gather_data_sampling: Not affected + itlb_multihit: KVM: Mitigation of VMX disabled + l1tf: Mitigation of PTE Inversion; VMX: conditional cache flushes SMT vulnerable + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Mitigation of PTI + mmio_stale_data: Mitigation of Clear buffers; SMT vulnerable + retbleed: Not affected + spec_rstack_overflow: 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 Retpolines IBPB: conditional IBRS_FW STIBP: conditional RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Mitigation of Clear buffers; SMT vulnerable

MSI NVIDIA GeForce RTX 3090

OS: Ubuntu 22.04, Kernel: 5.15.0-102-generic (x86_64), Display Server: X Server 1.21.1.3, Display Driver: NVIDIA, OpenCL: OpenCL 3.0 CUDA 12.4.89, Vulkan: 1.3.277, Compiler: GCC 11.4.0 + Clang 14.0.0-1ubuntu1.1 + LLVM 14.0.0 + CUDA 12.4, File-System: ext4, Screen Resolution: 1024x768

Kernel Notes: Transparent Huge Pages: madvise
Environment Notes: NVM_CD_FLAGS=-q
Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-cet --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++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-link-serialization=2 --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-11-XeT9lY/gcc-11-11.4.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-11-XeT9lY/gcc-11-11.4.0/debian/tmp-gcn/usr --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-build-config=bootstrap-lto-lean --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 Notes: Scaling Governor: intel_cpufreq performance - CPU Microcode: 0xb000040
Graphics Notes: BAR1 / Visible vRAM Size: 256 MiB - vBIOS Version: 94.02.59.00.8a
Python Notes: Python 3.10.12
Security Notes: gather_data_sampling: Not affected + itlb_multihit: KVM: Mitigation of VMX disabled + l1tf: Mitigation of PTE Inversion; VMX: conditional cache flushes SMT vulnerable + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Mitigation of PTI + mmio_stale_data: Mitigation of Clear buffers; SMT vulnerable + retbleed: Not affected + spec_rstack_overflow: 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 Retpolines IBPB: conditional IBRS_FW STIBP: conditional RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Mitigation of Clear buffers; SMT vulnerable

TestProcessorMotherboardChipsetMemoryDiskGraphicsAudioNetworkOSKernelDisplay ServerDisplay DriverCompilerFile-SystemScreen ResolutionOpenCLVulkantestTestMSI NVIDIA GeForce RTX 30902 x Intel Xeon E5-2682 v4 @ 3.00GHz (32 Cores / 64 Threads)Supermicro X10DRG-Q v1.10 (3.2 BIOS)Intel Xeon E7 v4/Xeon32GB1000GB Samsung SSD 870 + 4001GB Western Digital WD40EFPX-68CMSI NVIDIA GeForce RTX 3090 24GBRealtek ALC888-VD2 x Intel I350Ubuntu 22.045.15.0-102-generic (x86_64)X Server 1.21.1.3NVIDIAGCC 11.4.0 + Clang 14.0.0-1ubuntu1.1 + LLVM 14.0.0 + CUDA 12.4ext41024x768Supermicro SYS-7048GR-TR X10DRG-Q v1.10 (3.2 BIOS)2 x 16GB DDR4-2400MT/sOpenCL 3.0 CUDA 12.4.891.3.277OpenBenchmarking.orgKernel Details- Transparent Huge Pages: madviseEnvironment Details- NVM_CD_FLAGS=-qProcessor Details- test: Scaling Governor: intel_cpufreq schedutil - CPU Microcode: 0xb000040- Test: Scaling Governor: intel_cpufreq schedutil - CPU Microcode: 0xb000040- MSI NVIDIA GeForce RTX 3090: Scaling Governor: intel_cpufreq performance - CPU Microcode: 0xb000040Python Details- test: Python 3.10.14- MSI NVIDIA GeForce RTX 3090: Python 3.10.12Security Details- gather_data_sampling: Not affected + itlb_multihit: KVM: Mitigation of VMX disabled + l1tf: Mitigation of PTE Inversion; VMX: conditional cache flushes SMT vulnerable + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Mitigation of PTI + mmio_stale_data: Mitigation of Clear buffers; SMT vulnerable + retbleed: Not affected + spec_rstack_overflow: 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 Retpolines IBPB: conditional IBRS_FW STIBP: conditional RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Mitigation of Clear buffers; SMT vulnerable Compiler Details- Test, MSI NVIDIA GeForce RTX 3090: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-cet --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++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-link-serialization=2 --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-11-XeT9lY/gcc-11-11.4.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-11-XeT9lY/gcc-11-11.4.0/debian/tmp-gcn/usr --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-build-config=bootstrap-lto-lean --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 Graphics Details- MSI NVIDIA GeForce RTX 3090: BAR1 / Visible vRAM Size: 256 MiB - vBIOS Version: 94.02.59.00.8a

Testncnn: Vulkan GPU - FastestDetncnn: Vulkan GPU - vision_transformerncnn: Vulkan GPU - regnety_400mncnn: Vulkan GPU - squeezenet_ssdncnn: Vulkan GPU - yolov4-tinyncnn: Vulkan GPUv2-yolov3v2-yolov3 - mobilenetv2-yolov3ncnn: Vulkan GPU - resnet50ncnn: Vulkan GPU - alexnetncnn: Vulkan GPU - resnet18ncnn: Vulkan GPU - vgg16ncnn: Vulkan GPU - googlenetncnn: Vulkan GPU - blazefacencnn: Vulkan GPU - efficientnet-b0ncnn: Vulkan GPU - mnasnetncnn: Vulkan GPU - shufflenet-v2ncnn: Vulkan GPU-v3-v3 - mobilenet-v3ncnn: Vulkan GPU-v2-v2 - mobilenet-v2ncnn: Vulkan GPU - mobilenetluxcorerender: LuxCore Benchmark - GPUfahbench: viennacl: CPU BLAS - dGEMM-TTviennacl: CPU BLAS - dGEMM-TNviennacl: CPU BLAS - dGEMM-NTviennacl: CPU BLAS - dGEMM-NNviennacl: CPU BLAS - dGEMV-Tviennacl: CPU BLAS - dGEMV-Nviennacl: CPU BLAS - dDOTviennacl: CPU BLAS - dAXPYviennacl: CPU BLAS - dCOPYviennacl: CPU BLAS - sDOTviennacl: CPU BLAS - sAXPYviennacl: CPU BLAS - sCOPYblender: Junkshop - NVIDIA OptiXluxcorerender: Orange Juice - GPUluxcorerender: Danish Mood - GPUluxcorerender: DLSC - GPUblender: Barbershop - NVIDIA OptiXblender: BMW27 - NVIDIA OptiXhashcat: MD5luxcorerender: Rainbow Colors and Prism - GPUviennacl: OpenCL BLAS - dGEMM-TTviennacl: OpenCL BLAS - dGEMM-TNviennacl: OpenCL BLAS - dGEMM-NTviennacl: OpenCL BLAS - dGEMM-NNviennacl: OpenCL BLAS - dGEMV-Tviennacl: OpenCL BLAS - dGEMV-Nviennacl: OpenCL BLAS - dDOTviennacl: OpenCL BLAS - dAXPYviennacl: OpenCL BLAS - dCOPYviennacl: OpenCL BLAS - sDOTviennacl: OpenCL BLAS - sAXPYviennacl: OpenCL BLAS - sCOPYblender: Pabellon Barcelona - NVIDIA OptiXclpeak: Double-Precision Doublehashcat: SHA1hashcat: SHA-512blender: Classroom - NVIDIA OptiXblender: Fishy Cat - NVIDIA OptiXhashcat: TrueCrypt RIPEMD160 + XTShashcat: 7-Zipmixbench: OpenCL - Integermixbench: OpenCL - Double Precisionmixbench: OpenCL - Single Precisionmixbench: NVIDIA CUDA - Integerclpeak: Global Memory Bandwidthrodinia: OpenCL Particle Filtermixbench: NVIDIA CUDA - Half Precisionmixbench: NVIDIA CUDA - Double Precisionmixbench: NVIDIA CUDA - Single Precisioncl-mem: Copycl-mem: Writecl-mem: Readneatbench: GPUfinancebench: Black-Scholes OpenCLclpeak: Single-Precision Floatclpeak: Integer Compute INTshoc: OpenCL - TriadtestTestMSI NVIDIA GeForce RTX 309028.33134.1890.8449.9364.1452.6571.4931.1633.80103.3549.1511.3126.4016.6418.4116.9722.2452.6516.71291.243558.760.052.857.537.129.625.323.616.8110.997.569.314.3321.6817.4828.1837.994.8910251636875052.1359059159359037118664171359635949035911.11636.064353720000062859333339.718.451629667212290019101.89526.4337433.2715908.05816.714.03133947.25497.7331838.27359.5753.6827.530906.06034559.2417619.75OpenBenchmarking.org

NCNN

NCNN is a high performance neural network inference framework optimized for mobile and other platforms developed by Tencent. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: FastestDetMSI NVIDIA GeForce RTX 3090714212835SE +/- 3.48, N = 728.33MIN: 10.72 / MAX: 872.511. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: vision_transformerMSI NVIDIA GeForce RTX 3090306090120150SE +/- 4.49, N = 7134.18MIN: 89.58 / MAX: 998.891. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: regnety_400mMSI NVIDIA GeForce RTX 309020406080100SE +/- 5.08, N = 790.84MIN: 38.24 / MAX: 4536.91. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: squeezenet_ssdMSI NVIDIA GeForce RTX 30901122334455SE +/- 4.97, N = 749.93MIN: 25.42 / MAX: 1261.691. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: yolov4-tinyMSI NVIDIA GeForce RTX 30901428425670SE +/- 1.60, N = 764.14MIN: 39.53 / MAX: 565.181. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPUv2-yolov3v2-yolov3 - Model: mobilenetv2-yolov3MSI NVIDIA GeForce RTX 30901224364860SE +/- 2.58, N = 752.65MIN: 24.88 / MAX: 721.831. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: resnet50MSI NVIDIA GeForce RTX 30901632486480SE +/- 4.70, N = 771.49MIN: 33.7 / MAX: 1100.31. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: alexnetMSI NVIDIA GeForce RTX 3090714212835SE +/- 3.50, N = 731.16MIN: 15.67 / MAX: 275.831. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: resnet18MSI NVIDIA GeForce RTX 3090816243240SE +/- 2.60, N = 733.80MIN: 16.74 / MAX: 608.161. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: vgg16MSI NVIDIA GeForce RTX 309020406080100SE +/- 2.34, N = 7103.35MIN: 63.41 / MAX: 795.481. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: googlenetMSI NVIDIA GeForce RTX 30901122334455SE +/- 2.62, N = 749.15MIN: 22.64 / MAX: 1036.321. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: blazefaceMSI NVIDIA GeForce RTX 30903691215SE +/- 1.73, N = 711.31MIN: 4.15 / MAX: 483.311. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: efficientnet-b0MSI NVIDIA GeForce RTX 3090612182430SE +/- 2.12, N = 726.40MIN: 14.1 / MAX: 1069.681. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: mnasnetMSI NVIDIA GeForce RTX 309048121620SE +/- 1.58, N = 716.64MIN: 8.12 / MAX: 610.041. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: shufflenet-v2MSI NVIDIA GeForce RTX 3090510152025SE +/- 2.21, N = 718.41MIN: 9.35 / MAX: 812.961. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3MSI NVIDIA GeForce RTX 309048121620SE +/- 1.38, N = 716.97MIN: 8.58 / MAX: 743.551. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2MSI NVIDIA GeForce RTX 3090510152025SE +/- 2.40, N = 722.24MIN: 8.81 / MAX: 621.741. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: mobilenetMSI NVIDIA GeForce RTX 30901224364860SE +/- 2.58, N = 752.65MIN: 24.88 / MAX: 721.831. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

LuxCoreRender

LuxCoreRender is an open-source 3D physically based renderer formerly known as LuxRender. LuxCoreRender supports CPU-based rendering as well as GPU acceleration via OpenCL, NVIDIA CUDA, and NVIDIA OptiX interfaces. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgM samples/sec, More Is BetterLuxCoreRender 2.6Scene: LuxCore Benchmark - Acceleration: GPUMSI NVIDIA GeForce RTX 309048121620SE +/- 1.52, N = 1216.71MAX: 25.13

GROMACS

The GROMACS (GROningen MAchine for Chemical Simulations) molecular dynamics package testing with the water_GMX50 data. This test profile allows selecting between CPU and GPU-based GROMACS builds. Learn more via the OpenBenchmarking.org test page.

Implementation: NVIDIA CUDA GPU - Input: water_GMX50_bare

MSI NVIDIA GeForce RTX 3090: The test quit with a non-zero exit status. E: Fatal error:

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 2.3.2MSI NVIDIA GeForce RTX 309060120180240300SE +/- 2.67, N = 3291.24

ViennaCL

ViennaCL is an open-source linear algebra library written in C++ and with support for OpenCL and OpenMP. This test profile makes use of ViennaCL's built-in benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGFLOPs/s, More Is BetterViennaCL 1.7.1Test: CPU BLAS - dGEMM-TTMSI NVIDIA GeForce RTX 30901326395265SE +/- 0.39, N = 1558.71. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGFLOPs/s, More Is BetterViennaCL 1.7.1Test: CPU BLAS - dGEMM-TNMSI NVIDIA GeForce RTX 30901326395265SE +/- 0.38, N = 1560.01. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGFLOPs/s, More Is BetterViennaCL 1.7.1Test: CPU BLAS - dGEMM-NTMSI NVIDIA GeForce RTX 30901224364860SE +/- 0.33, N = 1552.81. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGFLOPs/s, More Is BetterViennaCL 1.7.1Test: CPU BLAS - dGEMM-NNMSI NVIDIA GeForce RTX 30901326395265SE +/- 0.25, N = 1557.51. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: CPU BLAS - dGEMV-TMSI NVIDIA GeForce RTX 3090918273645SE +/- 1.64, N = 1537.11. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: CPU BLAS - dGEMV-NMSI NVIDIA GeForce RTX 3090714212835SE +/- 1.03, N = 1529.61. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: CPU BLAS - dDOTMSI NVIDIA GeForce RTX 3090612182430SE +/- 1.08, N = 1525.31. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: CPU BLAS - dAXPYMSI NVIDIA GeForce RTX 3090612182430SE +/- 0.48, N = 1523.61. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: CPU BLAS - dCOPYMSI NVIDIA GeForce RTX 309048121620SE +/- 0.32, N = 1516.81. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: CPU BLAS - sDOTMSI NVIDIA GeForce RTX 309020406080100SE +/- 7.39, N = 15110.91. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: CPU BLAS - sAXPYMSI NVIDIA GeForce RTX 309020406080100SE +/- 8.97, N = 1597.51. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: CPU BLAS - sCOPYMSI NVIDIA GeForce RTX 30901530456075SE +/- 4.86, N = 1569.31. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

Blender

Blender is an open-source 3D creation and modeling software project. This test is of Blender's Cycles performance with various sample files. GPU computing via NVIDIA OptiX and NVIDIA CUDA is currently supported as well as HIP for AMD Radeon GPUs and Intel oneAPI for Intel Graphics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.1Blend File: Junkshop - Compute: NVIDIA OptiXMSI NVIDIA GeForce RTX 309048121620SE +/- 0.16, N = 1514.33

LuxCoreRender

LuxCoreRender is an open-source 3D physically based renderer formerly known as LuxRender. LuxCoreRender supports CPU-based rendering as well as GPU acceleration via OpenCL, NVIDIA CUDA, and NVIDIA OptiX interfaces. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgM samples/sec, More Is BetterLuxCoreRender 2.6Scene: Orange Juice - Acceleration: GPUMSI NVIDIA GeForce RTX 3090510152025SE +/- 0.13, N = 321.68MIN: 10.33 / MAX: 29.71

OpenBenchmarking.orgM samples/sec, More Is BetterLuxCoreRender 2.6Scene: Danish Mood - Acceleration: GPUMSI NVIDIA GeForce RTX 309048121620SE +/- 0.14, N = 317.48MIN: 2.15 / MAX: 22.45

OpenBenchmarking.orgM samples/sec, More Is BetterLuxCoreRender 2.6Scene: DLSC - Acceleration: GPUMSI NVIDIA GeForce RTX 3090714212835SE +/- 0.04, N = 328.18MIN: 24.15 / MAX: 28.79

Blender

Blender is an open-source 3D creation and modeling software project. This test is of Blender's Cycles performance with various sample files. GPU computing via NVIDIA OptiX and NVIDIA CUDA is currently supported as well as HIP for AMD Radeon GPUs and Intel oneAPI for Intel Graphics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.1Blend File: Barbershop - Compute: NVIDIA OptiXMSI NVIDIA GeForce RTX 3090918273645SE +/- 0.12, N = 337.99

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.1Blend File: BMW27 - Compute: NVIDIA OptiXMSI NVIDIA GeForce RTX 30901.10032.20063.30094.40125.5015SE +/- 0.17, N = 154.89

Hashcat

Hashcat is an open-source, advanced password recovery tool supporting GPU acceleration with OpenCL, NVIDIA CUDA, and Radeon ROCm. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgH/s, More Is BetterHashcat 6.2.4Benchmark: MD5MSI NVIDIA GeForce RTX 309020000M40000M60000M80000M100000MSE +/- 8904234078.96, N = 16102516368750

LuxCoreRender

LuxCoreRender is an open-source 3D physically based renderer formerly known as LuxRender. LuxCoreRender supports CPU-based rendering as well as GPU acceleration via OpenCL, NVIDIA CUDA, and NVIDIA OptiX interfaces. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgM samples/sec, More Is BetterLuxCoreRender 2.6Scene: Rainbow Colors and Prism - Acceleration: GPUMSI NVIDIA GeForce RTX 30901224364860SE +/- 0.75, N = 1552.13MIN: 45.12 / MAX: 71.41

ViennaCL

ViennaCL is an open-source linear algebra library written in C++ and with support for OpenCL and OpenMP. This test profile makes use of ViennaCL's built-in benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGFLOPs/s, More Is BetterViennaCL 1.7.1Test: OpenCL BLAS - dGEMM-TTMSI NVIDIA GeForce RTX 3090130260390520650SE +/- 1.33, N = 35901. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGFLOPs/s, More Is BetterViennaCL 1.7.1Test: OpenCL BLAS - dGEMM-TNMSI NVIDIA GeForce RTX 3090130260390520650SE +/- 1.33, N = 35911. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGFLOPs/s, More Is BetterViennaCL 1.7.1Test: OpenCL BLAS - dGEMM-NTMSI NVIDIA GeForce RTX 3090130260390520650SE +/- 1.67, N = 35931. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGFLOPs/s, More Is BetterViennaCL 1.7.1Test: OpenCL BLAS - dGEMM-NNMSI NVIDIA GeForce RTX 3090130260390520650SE +/- 1.33, N = 35901. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: OpenCL BLAS - dGEMV-TMSI NVIDIA GeForce RTX 309080160240320400SE +/- 0.00, N = 33711. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: OpenCL BLAS - dGEMV-NMSI NVIDIA GeForce RTX 30904080120160200SE +/- 0.00, N = 31861. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: OpenCL BLAS - dDOTMSI NVIDIA GeForce RTX 3090140280420560700SE +/- 0.67, N = 36411. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: OpenCL BLAS - dAXPYMSI NVIDIA GeForce RTX 3090150300450600750SE +/- 0.33, N = 37131. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: OpenCL BLAS - dCOPYMSI NVIDIA GeForce RTX 3090130260390520650SE +/- 0.33, N = 35961. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: OpenCL BLAS - sDOTMSI NVIDIA GeForce RTX 309080160240320400SE +/- 0.58, N = 33591. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: OpenCL BLAS - sAXPYMSI NVIDIA GeForce RTX 3090110220330440550SE +/- 0.33, N = 34901. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

OpenBenchmarking.orgGB/s, More Is BetterViennaCL 1.7.1Test: OpenCL BLAS - sCOPYMSI NVIDIA GeForce RTX 309080160240320400SE +/- 1.15, N = 33591. (CXX) g++ options: -fopenmp -O3 -rdynamic -lOpenCL

Blender

Blender is an open-source 3D creation and modeling software project. This test is of Blender's Cycles performance with various sample files. GPU computing via NVIDIA OptiX and NVIDIA CUDA is currently supported as well as HIP for AMD Radeon GPUs and Intel oneAPI for Intel Graphics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.1Blend File: Pabellon Barcelona - Compute: NVIDIA OptiXMSI NVIDIA GeForce RTX 30903691215SE +/- 0.03, N = 311.11

clpeak

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

OpenBenchmarking.orgGFLOPS, More Is Betterclpeak 1.1.2OpenCL Test: Double-Precision DoubleMSI NVIDIA GeForce RTX 3090140280420560700SE +/- 1.57, N = 3636.061. (CXX) g++ options: -O3

Hashcat

Hashcat is an open-source, advanced password recovery tool supporting GPU acceleration with OpenCL, NVIDIA CUDA, and Radeon ROCm. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgH/s, More Is BetterHashcat 6.2.4Benchmark: SHA1MSI NVIDIA GeForce RTX 30909000M18000M27000M36000M45000MSE +/- 42689733.35, N = 343537200000

OpenBenchmarking.orgH/s, More Is BetterHashcat 6.2.4Benchmark: SHA-512MSI NVIDIA GeForce RTX 30901300M2600M3900M5200M6500MSE +/- 12339818.11, N = 36285933333

Blender

Blender is an open-source 3D creation and modeling software project. This test is of Blender's Cycles performance with various sample files. GPU computing via NVIDIA OptiX and NVIDIA CUDA is currently supported as well as HIP for AMD Radeon GPUs and Intel oneAPI for Intel Graphics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.1Blend File: Classroom - Compute: NVIDIA OptiXMSI NVIDIA GeForce RTX 30903691215SE +/- 0.09, N = 39.71

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.1Blend File: Fishy Cat - Compute: NVIDIA OptiXMSI NVIDIA GeForce RTX 3090246810SE +/- 0.04, N = 38.45

Hashcat

Hashcat is an open-source, advanced password recovery tool supporting GPU acceleration with OpenCL, NVIDIA CUDA, and Radeon ROCm. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgH/s, More Is BetterHashcat 6.2.4Benchmark: TrueCrypt RIPEMD160 + XTSMSI NVIDIA GeForce RTX 3090300K600K900K1200K1500KSE +/- 1560.27, N = 31629667

OpenBenchmarking.orgH/s, More Is BetterHashcat 6.2.4Benchmark: 7-ZipMSI NVIDIA GeForce RTX 3090500K1000K1500K2000K2500KSE +/- 2059.94, N = 32122900

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: IntegerMSI NVIDIA GeForce RTX 30904K8K12K16K20KSE +/- 306.56, N = 1519101.891. (CXX) g++ options: -lm -lstdc++ -lOpenCL -lrt -O2

OpenBenchmarking.orgGFLOPS, More Is BetterMixbench 2020-06-23Backend: OpenCL - Benchmark: Double PrecisionMSI NVIDIA GeForce RTX 3090110220330440550SE +/- 5.98, N = 15526.431. (CXX) g++ options: -lm -lstdc++ -lOpenCL -lrt -O2

OpenBenchmarking.orgGFLOPS, More Is BetterMixbench 2020-06-23Backend: OpenCL - Benchmark: Single PrecisionMSI NVIDIA GeForce RTX 30908K16K24K32K40KSE +/- 393.91, N = 1537433.271. (CXX) g++ options: -lm -lstdc++ -lOpenCL -lrt -O2

OpenBenchmarking.orgGIOPS, More Is BetterMixbench 2020-06-23Backend: NVIDIA CUDA - Benchmark: IntegerMSI NVIDIA GeForce RTX 30903K6K9K12K15KSE +/- 297.96, N = 1515908.051. (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 Betterclpeak 1.1.2OpenCL Test: Global Memory BandwidthMSI NVIDIA GeForce RTX 30902004006008001000SE +/- 0.04, N = 3816.711. (CXX) g++ options: -O3

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 FilterMSI NVIDIA GeForce RTX 30900.9071.8142.7213.6284.535SE +/- 0.004, N = 34.0311. (CXX) g++ options: -m64 -lm -lcuda -lcudart -lcudadevrt -lcudart_static -lrt -lpthread -ldl

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: Half PrecisionMSI NVIDIA GeForce RTX 30907K14K21K28K35KSE +/- 584.04, N = 1533947.251. (CXX) g++ options: -lm -lstdc++ -lOpenCL -lrt -O2

OpenBenchmarking.orgGFLOPS, More Is BetterMixbench 2020-06-23Backend: NVIDIA CUDA - Benchmark: Double PrecisionMSI NVIDIA GeForce RTX 3090110220330440550SE +/- 8.29, N = 15497.731. (CXX) g++ options: -lm -lstdc++ -lOpenCL -lrt -O2

OpenBenchmarking.orgGFLOPS, More Is BetterMixbench 2020-06-23Backend: NVIDIA CUDA - Benchmark: Single PrecisionMSI NVIDIA GeForce RTX 30907K14K21K28K35KSE +/- 404.30, N = 1531838.271. (CXX) g++ options: -lm -lstdc++ -lOpenCL -lrt -O2

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: CopyMSI NVIDIA GeForce RTX 309080160240320400SE +/- 0.23, N = 3359.51. (CC) gcc options: -O2 -flto -lOpenCL

OpenBenchmarking.orgGB/s, More Is Bettercl-mem 2017-01-13Benchmark: WriteMSI NVIDIA GeForce RTX 3090160320480640800SE +/- 0.21, N = 3753.61. (CC) gcc options: -O2 -flto -lOpenCL

OpenBenchmarking.orgGB/s, More Is Bettercl-mem 2017-01-13Benchmark: ReadMSI NVIDIA GeForce RTX 30902004006008001000SE +/- 0.18, N = 3827.51. (CC) gcc options: -O2 -flto -lOpenCL

AI Benchmark Alpha

AI Benchmark Alpha is a Python library for evaluating artificial intelligence (AI) performance on diverse hardware platforms and relies upon the TensorFlow machine learning library. Learn more via the OpenBenchmarking.org test page.

test: The test quit with a non-zero exit status. E: AttributeError: module 'numpy' has no attribute 'warnings'. Did you mean: 'hanning'?

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: GPUMSI NVIDIA GeForce RTX 30907001400210028003500SE +/- 0.00, N = 33090

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.

FP16: No - Mode: Training - Network: Mobilenet - Device: OpenCL

MSI NVIDIA GeForce RTX 3090: The test quit with a non-zero exit status. E: ImportError: cannot import name 'Iterable' from 'collections' (/home/guyi/miniconda3/envs/Structimragh/lib/python3.10/collections/__init__.py)

FP16: No - Mode: Inference - Network: DenseNet 201 - Device: OpenCL

MSI NVIDIA GeForce RTX 3090: The test quit with a non-zero exit status. E: ImportError: cannot import name 'Iterable' from 'collections' (/home/guyi/miniconda3/envs/Structimragh/lib/python3.10/collections/__init__.py)

FP16: Yes - Mode: Inference - Network: Mobilenet - Device: OpenCL

MSI NVIDIA GeForce RTX 3090: The test quit with a non-zero exit status. E: ImportError: cannot import name 'Iterable' from 'collections' (/home/guyi/miniconda3/envs/Structimragh/lib/python3.10/collections/__init__.py)

FP16: No - Mode: Inference - Network: Mobilenet - Device: OpenCL

MSI NVIDIA GeForce RTX 3090: The test quit with a non-zero exit status. E: ImportError: cannot import name 'Iterable' from 'collections' (/home/guyi/miniconda3/envs/Structimragh/lib/python3.10/collections/__init__.py)

FP16: No - Mode: Inference - Network: IMDB LSTM - Device: OpenCL

MSI NVIDIA GeForce RTX 3090: The test quit with a non-zero exit status. E: ImportError: cannot import name 'Iterable' from 'collections' (/home/guyi/miniconda3/envs/Structimragh/lib/python3.10/collections/__init__.py)

FinanceBench

FinanceBench is a collection of financial program benchmarks with support for benchmarking on the GPU via OpenCL and CPU benchmarking with OpenMP. The FinanceBench test cases are focused on Black-Sholes-Merton Process with Analytic European Option engine, QMC (Sobol) Monte-Carlo method (Equity Option Example), Bonds Fixed-rate bond with flat forward curve, and Repo Securities repurchase agreement. FinanceBench was originally written by the Cavazos Lab at University of Delaware. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterFinanceBench 2016-07-25Benchmark: Black-Scholes OpenCLMSI NVIDIA GeForce RTX 3090246810SE +/- 0.010, N = 36.0601. (CXX) g++ options: -O3 -march=native -fopenmp

clpeak

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

OpenBenchmarking.orgGFLOPS, More Is Betterclpeak 1.1.2OpenCL Test: Single-Precision FloatMSI NVIDIA GeForce RTX 30907K14K21K28K35KSE +/- 85.81, N = 334559.241. (CXX) g++ options: -O3

OpenBenchmarking.orgGIOPS, More Is Betterclpeak 1.1.2OpenCL Test: Integer Compute INTMSI NVIDIA GeForce RTX 30904K8K12K16K20KSE +/- 10.68, N = 317619.751. (CXX) g++ options: -O3

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.

OpenCL Device: GPU

MSI NVIDIA GeForce RTX 3090: The test quit with a non-zero exit status.

Chaos Group V-RAY

This is a test of Chaos Group's V-RAY benchmark. V-RAY is a commercial renderer that can integrate with various creator software products like SketchUp and 3ds Max. The V-RAY benchmark is standalone and supports CPU and NVIDIA CUDA/RTX based rendering. Learn more via the OpenBenchmarking.org test page.

Mode: NVIDIA RTX GPU

MSI NVIDIA GeForce RTX 3090: The test quit with a non-zero exit status.

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.

Test: Conjugate Gradient OpenCL

MSI NVIDIA GeForce RTX 3090: The test run did not produce a result. E: arrayfire: line 3: ./cg_opencl: No such file or directory

Chaos Group V-RAY

This is a test of Chaos Group's V-RAY benchmark. V-RAY is a commercial renderer that can integrate with various creator software products like SketchUp and 3ds Max. The V-RAY benchmark is standalone and supports CPU and NVIDIA CUDA/RTX based rendering. Learn more via the OpenBenchmarking.org test page.

Mode: NVIDIA CUDA GPU

MSI NVIDIA GeForce RTX 3090: The test quit with a non-zero exit status.

Caffe

This is a benchmark of the Caffe deep learning framework and currently supports the AlexNet and Googlenet model and execution on both CPUs and NVIDIA GPUs. Learn more via the OpenBenchmarking.org test page.

Model: GoogleNet - Acceleration: NVIDIA CUDA - Iterations: 200

MSI NVIDIA GeForce RTX 3090: The test quit with a non-zero exit status. E: caffe: line 3: ./tools/caffe: No such file or directory

Model: AlexNet - Acceleration: NVIDIA CUDA - Iterations: 1000

MSI NVIDIA GeForce RTX 3090: The test quit with a non-zero exit status. E: caffe: line 3: ./tools/caffe: No such file or directory

SHOC Scalable HeterOgeneous Computing

The CUDA and OpenCL version of Vetter's Scalable HeterOgeneous Computing benchmark suite. SHOC provides a number of different benchmark programs for evaluating the performance and stability of compute devices. Learn more via the OpenBenchmarking.org test page.

Target: OpenCL - Benchmark: Texture Read Bandwidth

MSI NVIDIA GeForce RTX 3090: The test quit with a non-zero exit status. E: shoc: line 3: ./bin/shocdriver: No such file or directory

Target: OpenCL - Benchmark: Max SP Flops

MSI NVIDIA GeForce RTX 3090: The test quit with a non-zero exit status. E: shoc: line 3: ./bin/shocdriver: No such file or directory

Target: OpenCL - Benchmark: S3D

MSI NVIDIA GeForce RTX 3090: The test quit with a non-zero exit status. E: shoc: line 3: ./bin/shocdriver: No such file or directory

Target: OpenCL - Benchmark: Bus Speed Download

MSI NVIDIA GeForce RTX 3090: The test quit with a non-zero exit status. E: shoc: line 3: ./bin/shocdriver: No such file or directory

Target: OpenCL - Benchmark: Reduction

MSI NVIDIA GeForce RTX 3090: The test quit with a non-zero exit status. E: shoc: line 3: ./bin/shocdriver: No such file or directory

Target: OpenCL - Benchmark: FFT SP

MSI NVIDIA GeForce RTX 3090: The test quit with a non-zero exit status. E: shoc: line 3: ./bin/shocdriver: No such file or directory

Caffe

This is a benchmark of the Caffe deep learning framework and currently supports the AlexNet and Googlenet model and execution on both CPUs and NVIDIA GPUs. Learn more via the OpenBenchmarking.org test page.

Model: AlexNet - Acceleration: NVIDIA CUDA - Iterations: 100

MSI NVIDIA GeForce RTX 3090: The test quit with a non-zero exit status. E: caffe: line 3: ./tools/caffe: No such file or directory

SHOC Scalable HeterOgeneous Computing

The CUDA and OpenCL version of Vetter's Scalable HeterOgeneous Computing benchmark suite. SHOC provides a number of different benchmark programs for evaluating the performance and stability of compute devices. Learn more via the OpenBenchmarking.org test page.

Target: OpenCL - Benchmark: MD5 Hash

MSI NVIDIA GeForce RTX 3090: The test quit with a non-zero exit status. E: shoc: line 3: ./bin/shocdriver: No such file or directory

Caffe

This is a benchmark of the Caffe deep learning framework and currently supports the AlexNet and Googlenet model and execution on both CPUs and NVIDIA GPUs. Learn more via the OpenBenchmarking.org test page.

Model: GoogleNet - Acceleration: NVIDIA CUDA - Iterations: 1000

MSI NVIDIA GeForce RTX 3090: The test quit with a non-zero exit status. E: caffe: line 3: ./tools/caffe: No such file or directory

Model: GoogleNet - Acceleration: NVIDIA CUDA - Iterations: 100

MSI NVIDIA GeForce RTX 3090: The test quit with a non-zero exit status. E: caffe: line 3: ./tools/caffe: No such file or directory

Model: AlexNet - Acceleration: NVIDIA CUDA - Iterations: 200

MSI NVIDIA GeForce RTX 3090: The test quit with a non-zero exit status. E: caffe: line 3: ./tools/caffe: No such file or directory

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.

Backend: OpenCL

MSI NVIDIA GeForce RTX 3090: The test quit with a non-zero exit status. E: lczero: line 4: ./lc0: No such file or directory

RedShift Demo

This is a test of MAXON's RedShift demo build that currently requires NVIDIA GPU acceleration. Learn more via the OpenBenchmarking.org test page.

MSI NVIDIA GeForce RTX 3090: The test quit with a non-zero exit status. E: redshift: line 3: /usr/redshift/bin/redshiftBenchmark: No such file or directory

SHOC Scalable HeterOgeneous Computing

The CUDA and OpenCL version of Vetter's Scalable HeterOgeneous Computing benchmark suite. SHOC provides a number of different benchmark programs for evaluating the performance and stability of compute devices. Learn more via the OpenBenchmarking.org test page.

Target: OpenCL - Benchmark: Bus Speed Readback

MSI NVIDIA GeForce RTX 3090: The test quit with a non-zero exit status. E: shoc: line 3: ./bin/shocdriver: No such file or directory

Target: OpenCL - Benchmark: GEMM SGEMM_N

MSI NVIDIA GeForce RTX 3090: The test quit with a non-zero exit status. E: shoc: line 3: ./bin/shocdriver: No such file or directory

Target: OpenCL - Benchmark: Triad

MSI NVIDIA GeForce RTX 3090: The test quit with a non-zero exit status. E: shoc: line 3: ./bin/shocdriver: No such file or directory

76 Results Shown

NCNN:
  Vulkan GPU - FastestDet
  Vulkan GPU - vision_transformer
  Vulkan GPU - regnety_400m
  Vulkan GPU - squeezenet_ssd
  Vulkan GPU - yolov4-tiny
  Vulkan GPUv2-yolov3v2-yolov3 - mobilenetv2-yolov3
  Vulkan GPU - resnet50
  Vulkan GPU - alexnet
  Vulkan GPU - resnet18
  Vulkan GPU - vgg16
  Vulkan GPU - googlenet
  Vulkan GPU - blazeface
  Vulkan GPU - efficientnet-b0
  Vulkan GPU - mnasnet
  Vulkan GPU - shufflenet-v2
  Vulkan GPU-v3-v3 - mobilenet-v3
  Vulkan GPU-v2-v2 - mobilenet-v2
  Vulkan GPU - mobilenet
LuxCoreRender
FAHBench
ViennaCL:
  CPU BLAS - dGEMM-TT
  CPU BLAS - dGEMM-TN
  CPU BLAS - dGEMM-NT
  CPU BLAS - dGEMM-NN
  CPU BLAS - dGEMV-T
  CPU BLAS - dGEMV-N
  CPU BLAS - dDOT
  CPU BLAS - dAXPY
  CPU BLAS - dCOPY
  CPU BLAS - sDOT
  CPU BLAS - sAXPY
  CPU BLAS - sCOPY
Blender
LuxCoreRender:
  Orange Juice - GPU
  Danish Mood - GPU
  DLSC - GPU
Blender:
  Barbershop - NVIDIA OptiX
  BMW27 - NVIDIA OptiX
Hashcat
LuxCoreRender
ViennaCL:
  OpenCL BLAS - dGEMM-TT
  OpenCL BLAS - dGEMM-TN
  OpenCL BLAS - dGEMM-NT
  OpenCL BLAS - dGEMM-NN
  OpenCL BLAS - dGEMV-T
  OpenCL BLAS - dGEMV-N
  OpenCL BLAS - dDOT
  OpenCL BLAS - dAXPY
  OpenCL BLAS - dCOPY
  OpenCL BLAS - sDOT
  OpenCL BLAS - sAXPY
  OpenCL BLAS - sCOPY
Blender
clpeak
Hashcat:
  SHA1
  SHA-512
Blender:
  Classroom - NVIDIA OptiX
  Fishy Cat - NVIDIA OptiX
Hashcat:
  TrueCrypt RIPEMD160 + XTS
  7-Zip
Mixbench:
  OpenCL - Integer
  OpenCL - Double Precision
  OpenCL - Single Precision
  NVIDIA CUDA - Integer
clpeak
Rodinia
Mixbench:
  NVIDIA CUDA - Half Precision
  NVIDIA CUDA - Double Precision
  NVIDIA CUDA - Single Precision
cl-mem:
  Copy
  Write
  Read
NeatBench
FinanceBench
clpeak:
  Single-Precision Float
  Integer Compute INT

test

Processor: 2 x Intel Xeon E5-2682 v4 @ 3.00GHz (32 Cores / 64 Threads), Motherboard: Supermicro X10DRG-Q v1.10 (3.2 BIOS), Chipset: Intel Xeon E7 v4/Xeon, Memory: 32GB, Disk: 1000GB Samsung SSD 870 + 4001GB Western Digital WD40EFPX-68C, Graphics: MSI NVIDIA GeForce RTX 3090 24GB, Audio: Realtek ALC888-VD, Network: 2 x Intel I350

OS: Ubuntu 22.04, Kernel: 5.15.0-102-generic (x86_64), Display Server: X Server 1.21.1.3, Display Driver: NVIDIA, Compiler: GCC 11.4.0 + Clang 14.0.0-1ubuntu1.1 + LLVM 14.0.0 + CUDA 12.4, File-System: ext4, Screen Resolution: 1024x768

Kernel Notes: Transparent Huge Pages: madvise
Environment Notes: NVM_CD_FLAGS=-q
Processor Notes: Scaling Governor: intel_cpufreq schedutil - CPU Microcode: 0xb000040
Python Notes: Python 3.10.14
Security Notes: gather_data_sampling: Not affected + itlb_multihit: KVM: Mitigation of VMX disabled + l1tf: Mitigation of PTE Inversion; VMX: conditional cache flushes SMT vulnerable + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Mitigation of PTI + mmio_stale_data: Mitigation of Clear buffers; SMT vulnerable + retbleed: Not affected + spec_rstack_overflow: 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 Retpolines IBPB: conditional IBRS_FW STIBP: conditional RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Mitigation of Clear buffers; SMT vulnerable

Testing initiated at 16 April 2024 08:25 by user guyi.

Test

Processor: 2 x Intel Xeon E5-2682 v4 @ 3.00GHz (32 Cores / 64 Threads), Motherboard: Supermicro SYS-7048GR-TR X10DRG-Q v1.10 (3.2 BIOS), Chipset: Intel Xeon E7 v4/Xeon, Memory: 2 x 16GB DDR4-2400MT/s, Disk: 1000GB Samsung SSD 870 + 4001GB Western Digital WD40EFPX-68C, Graphics: MSI NVIDIA GeForce RTX 3090 24GB, Audio: Realtek ALC888-VD, Network: 2 x Intel I350

OS: Ubuntu 22.04, Kernel: 5.15.0-102-generic (x86_64), Display Server: X Server 1.21.1.3, Display Driver: NVIDIA, OpenCL: OpenCL 3.0 CUDA 12.4.89, Compiler: GCC 11.4.0 + Clang 14.0.0-1ubuntu1.1 + LLVM 14.0.0 + CUDA 12.4, File-System: ext4, Screen Resolution: 1024x768

Kernel Notes: Transparent Huge Pages: madvise
Environment Notes: NVM_CD_FLAGS=-q
Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-cet --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++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-link-serialization=2 --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-11-XeT9lY/gcc-11-11.4.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-11-XeT9lY/gcc-11-11.4.0/debian/tmp-gcn/usr --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-build-config=bootstrap-lto-lean --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 Notes: Scaling Governor: intel_cpufreq schedutil - CPU Microcode: 0xb000040
Security Notes: gather_data_sampling: Not affected + itlb_multihit: KVM: Mitigation of VMX disabled + l1tf: Mitigation of PTE Inversion; VMX: conditional cache flushes SMT vulnerable + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Mitigation of PTI + mmio_stale_data: Mitigation of Clear buffers; SMT vulnerable + retbleed: Not affected + spec_rstack_overflow: 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 Retpolines IBPB: conditional IBRS_FW STIBP: conditional RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Mitigation of Clear buffers; SMT vulnerable

Testing initiated at 17 April 2024 03:38 by user guyi.

MSI NVIDIA GeForce RTX 3090

Processor: 2 x Intel Xeon E5-2682 v4 @ 3.00GHz (32 Cores / 64 Threads), Motherboard: Supermicro SYS-7048GR-TR X10DRG-Q v1.10 (3.2 BIOS), Chipset: Intel Xeon E7 v4/Xeon, Memory: 2 x 16GB DDR4-2400MT/s, Disk: 1000GB Samsung SSD 870 + 4001GB Western Digital WD40EFPX-68C, Graphics: MSI NVIDIA GeForce RTX 3090 24GB, Audio: Realtek ALC888-VD, Network: 2 x Intel I350

OS: Ubuntu 22.04, Kernel: 5.15.0-102-generic (x86_64), Display Server: X Server 1.21.1.3, Display Driver: NVIDIA, OpenCL: OpenCL 3.0 CUDA 12.4.89, Vulkan: 1.3.277, Compiler: GCC 11.4.0 + Clang 14.0.0-1ubuntu1.1 + LLVM 14.0.0 + CUDA 12.4, File-System: ext4, Screen Resolution: 1024x768

Kernel Notes: Transparent Huge Pages: madvise
Environment Notes: NVM_CD_FLAGS=-q
Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-cet --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++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-link-serialization=2 --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-11-XeT9lY/gcc-11-11.4.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-11-XeT9lY/gcc-11-11.4.0/debian/tmp-gcn/usr --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-build-config=bootstrap-lto-lean --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 Notes: Scaling Governor: intel_cpufreq performance - CPU Microcode: 0xb000040
Graphics Notes: BAR1 / Visible vRAM Size: 256 MiB - vBIOS Version: 94.02.59.00.8a
Python Notes: Python 3.10.12
Security Notes: gather_data_sampling: Not affected + itlb_multihit: KVM: Mitigation of VMX disabled + l1tf: Mitigation of PTE Inversion; VMX: conditional cache flushes SMT vulnerable + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Mitigation of PTI + mmio_stale_data: Mitigation of Clear buffers; SMT vulnerable + retbleed: Not affected + spec_rstack_overflow: 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 Retpolines IBPB: conditional IBRS_FW STIBP: conditional RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Mitigation of Clear buffers; SMT vulnerable

Testing initiated at 17 April 2024 03:51 by user guyi.