3950x nvidia

AMD Ryzen 9 3950X 16-Core testing with a ASUS ROG CROSSHAIR VIII HERO (WI-FI) (1302 BIOS) and ASUS NVIDIA GeForce GTX 1650 SUPER 4GB 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 2009184-FI-3950XNVID64
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Result
Identifier
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Performance Per
Dollar
Date
Run
  Test
  Duration
ASUS NVIDIA GeForce GTX 1650 SUPER
September 18 2020
  2 Hours, 4 Minutes
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3950x nvidiaOpenBenchmarking.orgPhoronix Test SuiteAMD 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 MP600 + 2000GBASUS NVIDIA GeForce GTX 1650 SUPER 4GB (375/405MHz)NVIDIA TU116 HD AudioDELL P2415QRealtek RTL8125 2.5GbE + Intel I211 + Intel Wi-Fi 6 AX200Ubuntu 20.045.4.0-47-generic (x86_64)GNOME Shell 3.36.4X Server 1.20.8NVIDIA 450.664.6.0OpenCL 1.2 CUDA 11.0.228 + OpenCL 2.0 AMD-APP (3182.0)1.2.133GCC 9.3.0 + CUDA 11.0ext43840x2160ProcessorMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelDesktopDisplay ServerDisplay DriverOpenGLOpenCLVulkanCompilerFile-SystemScreen Resolution3950x Nvidia BenchmarksSystem Logs- --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 - Scaling Governor: acpi-cpufreq ondemand - CPU Microcode: 0x8701013- 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

3950x nvidianamd-cuda: ATPase Simulation - 327,506 Atomsncnn: CPU - squeezenet_int8ncnn: CPU - mobilenet_v3ncnn: CPU - squeezenetncnn: CPU - mnasnetncnn: CPU - blazefacencnn: CPU - googlenet_int8ncnn: CPU - vgg16_int8ncnn: CPU - resnet18_int8ncnn: CPU - alexnetncnn: CPU - resnet50_int8ncnn: CPU - mobilenetv2_yolov3kripke: ASUS NVIDIA GeForce GTX 1650 SUPER0.2426912.245.215.015.351.9733.8785.9517.2316.5450.8717.257468906OpenBenchmarking.org

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 AtomsASUS NVIDIA GeForce GTX 1650 SUPER0.05460.10920.16380.21840.273SE +/- 0.00013, N = 30.24269

NCNN

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: squeezenet_int8ASUS NVIDIA GeForce GTX 1650 SUPER3691215SE +/- 0.04, N = 312.24MIN: 12.03 / MAX: 13.911. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: mobilenet_v3ASUS NVIDIA GeForce GTX 1650 SUPER1.17232.34463.51694.68925.8615SE +/- 0.05, N = 35.21MIN: 5.06 / MAX: 5.771. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: squeezenetASUS NVIDIA GeForce GTX 1650 SUPER1.12732.25463.38194.50925.6365SE +/- 0.04, N = 35.01MIN: 4.88 / MAX: 5.231. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: mnasnetASUS NVIDIA GeForce GTX 1650 SUPER1.20382.40763.61144.81526.019SE +/- 0.16, N = 35.35MIN: 5.09 / MAX: 5.841. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: blazefaceASUS NVIDIA GeForce GTX 1650 SUPER0.44330.88661.32991.77322.2165SE +/- 0.02, N = 31.97MIN: 1.92 / MAX: 2.091. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: googlenet_int8ASUS NVIDIA GeForce GTX 1650 SUPER816243240SE +/- 0.27, N = 333.87MIN: 32.85 / MAX: 43.881. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: vgg16_int8ASUS NVIDIA GeForce GTX 1650 SUPER20406080100SE +/- 0.10, N = 385.95MIN: 84.89 / MAX: 92.351. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: resnet18_int8ASUS NVIDIA GeForce GTX 1650 SUPER48121620SE +/- 0.15, N = 317.23MIN: 16.44 / MAX: 45.431. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: alexnetASUS NVIDIA GeForce GTX 1650 SUPER48121620SE +/- 0.13, N = 316.54MIN: 16.19 / MAX: 24.461. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: resnet50_int8ASUS NVIDIA GeForce GTX 1650 SUPER1122334455SE +/- 0.06, N = 350.87MIN: 50.42 / MAX: 59.971. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20200916Target: CPU - Model: mobilenetv2_yolov3ASUS NVIDIA GeForce GTX 1650 SUPER48121620SE +/- 0.56, N = 317.25MIN: 16.43 / MAX: 19.981. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

Kripke

Kripke is a simple, scalable, 3D Sn deterministic particle transport code. Its primary purpose is to research how data layout, programming paradigms and architectures effect the implementation and performance of Sn transport. Kripke is developed by LLNL. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgThroughput FoM, More Is BetterKripke 1.2.4ASUS NVIDIA GeForce GTX 1650 SUPER1.6M3.2M4.8M6.4M8MSE +/- 30556.93, N = 374689061. (CXX) g++ options: -O3 -fopenmp