Various open-source benchmarks by the Phoronix Test Suite v9.8.0 (Nesodden).
eVGA NVIDIA GeForce GTX 780 Processor: AMD Ryzen 7 1700X Eight-Core @ 3.40GHz (8 Cores / 16 Threads), Motherboard: MSI X470 GAMING PLUS MAX (MS-7B79) v3.0 (H.60 BIOS), Chipset: AMD 17h, Memory: 16GB, Disk: Samsung SSD 970 EVO Plus 500GB + 128GB ADATA SP900 + 120GB SSD2SC120G3LA726 + 3001GB Hitachi HUS72403, Graphics: eVGA NVIDIA GeForce GTX 780 3GB (941/3004MHz), Audio: NVIDIA GK110 HD Audio, Monitor: DELL 2208WFP + R241Y, Network: Realtek RTL8111/8168/8411
OS: Fedora 32, Kernel: 5.8.13-200.fc32.x86_64 (x86_64), Desktop: GNOME Shell 3.36.6, Display Server: X Server 1.20.8, Display Driver: NVIDIA 450.66, OpenGL: 4.6.0, Vulkan: 1.2.133, Compiler: GCC 10.2.1 20200723 + Clang 10.0.1, File-System: ext4, Screen Resolution: 1680x1050
Compiler Notes: --build=x86_64-redhat-linux --disable-libunwind-exceptions --enable-__cxa_atexit --enable-bootstrap --enable-cet --enable-checking=release --enable-gnu-indirect-function --enable-gnu-unique-object --enable-initfini-array --enable-languages=c,c++,fortran,objc,obj-c++,ada,go,d,lto --enable-multilib --enable-offload-targets=nvptx-none --enable-plugin --enable-shared --enable-threads=posix --mandir=/usr/share/man --with-arch_32=i686 --with-gcc-major-version-only --with-isl --with-linker-hash-style=gnu --with-tune=generic --without-cuda-driverProcessor Notes: Scaling Governor: acpi-cpufreq ondemand - CPU Microcode: 0x8001138OpenCL Notes: GPU Compute Cores: 2304Python Notes: Python 3.8.5Security Notes: SELinux + 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: disabled RSB filling + srbds: Not affected + tsx_async_abort: Not affected
NAMD 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. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org days/ns, Fewer Is Better NAMD 2.14 ATPase Simulation - 327,506 Atoms eVGA NVIDIA GeForce GTX 780 0.6984 1.3968 2.0952 2.7936 3.492 SE +/- 0.00194, N = 3 3.10422
Dolfyn Dolfyn is a Computational Fluid Dynamics (CFD) code of modern numerical simulation techniques. The Dolfyn test profile measures the execution time of the bundled computational fluid dynamics demos that are bundled with Dolfyn. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Seconds, Fewer Is Better Dolfyn 0.527 Computational Fluid Dynamics eVGA NVIDIA GeForce GTX 780 5 10 15 20 25 SE +/- 0.08, N = 3 22.53
FFTE FFTE is a package by Daisuke Takahashi to compute Discrete Fourier Transforms of 1-, 2- and 3- dimensional sequences of length (2^p)*(3^q)*(5^r). Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org MFLOPS, More Is Better FFTE 7.0 N=256, 3D Complex FFT Routine eVGA NVIDIA GeForce GTX 780 7K 14K 21K 28K 35K SE +/- 110.47, N = 3 32053.75 1. (F9X) gfortran options: -O3 -fomit-frame-pointer -fopenmp
Incompact3D Incompact3d is a Fortran-MPI based, finite difference high-performance code for solving the incompressible Navier-Stokes equation and as many as you need scalar transport equations. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Seconds, Fewer Is Better Incompact3D 2020-09-17 Input: Cylinder eVGA NVIDIA GeForce GTX 780 100 200 300 400 500 SE +/- 0.95, N = 3 453.26 1. (F9X) gfortran options: -cpp -funroll-loops -floop-optimize -fcray-pointer -fbacktrace -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi
Monte Carlo Simulations of Ionised Nebulae Mocassin is the Monte Carlo Simulations of Ionised Nebulae. MOCASSIN is a fully 3D or 2D photoionisation and dust radiative transfer code which employs a Monte Carlo approach to the transfer of radiation through media of arbitrary geometry and density distribution. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Seconds, Fewer Is Better Monte Carlo Simulations of Ionised Nebulae 2019-03-24 Input: Dust 2D tau100.0 eVGA NVIDIA GeForce GTX 780 60 120 180 240 300 SE +/- 3.52, N = 4 272 1. (F9X) gfortran options: -cpp -Jsource/ -ffree-line-length-0 -lm -std=legacy -O3 -O2 -pthread -lmpi_usempif08 -lmpi_mpifh -lmpi
WebP Image Encode This is a test of Google's libwebp with the cwebp image encode utility and using a sample 6000x4000 pixel JPEG image as the input. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Encode Time - Seconds, Fewer Is Better WebP Image Encode 1.1 Encode Settings: Default eVGA NVIDIA GeForce GTX 780 0.3692 0.7384 1.1076 1.4768 1.846 SE +/- 0.006, N = 3 1.641 1. (CC) gcc options: -fvisibility=hidden -O2 -pthread -lm -ljpeg -lpng16 -ltiff
OpenBenchmarking.org Encode Time - Seconds, Fewer Is Better WebP Image Encode 1.1 Encode Settings: Quality 100 eVGA NVIDIA GeForce GTX 780 0.5902 1.1804 1.7706 2.3608 2.951 SE +/- 0.013, N = 3 2.623 1. (CC) gcc options: -fvisibility=hidden -O2 -pthread -lm -ljpeg -lpng16 -ltiff
OpenBenchmarking.org Encode Time - Seconds, Fewer Is Better WebP Image Encode 1.1 Encode Settings: Quality 100, Lossless eVGA NVIDIA GeForce GTX 780 6 12 18 24 30 SE +/- 0.08, N = 3 23.07 1. (CC) gcc options: -fvisibility=hidden -O2 -pthread -lm -ljpeg -lpng16 -ltiff
OpenBenchmarking.org Encode Time - Seconds, Fewer Is Better WebP Image Encode 1.1 Encode Settings: Quality 100, Highest Compression eVGA NVIDIA GeForce GTX 780 3 6 9 12 15 SE +/- 0.025, N = 3 8.970 1. (CC) gcc options: -fvisibility=hidden -O2 -pthread -lm -ljpeg -lpng16 -ltiff
OpenBenchmarking.org Encode Time - Seconds, Fewer Is Better WebP Image Encode 1.1 Encode Settings: Quality 100, Lossless, Highest Compression eVGA NVIDIA GeForce GTX 780 11 22 33 44 55 SE +/- 0.19, N = 3 48.18 1. (CC) gcc options: -fvisibility=hidden -O2 -pthread -lm -ljpeg -lpng16 -ltiff
RNNoise RNNoise is a recurrent neural network for audio noise reduction developed by Mozilla and Xiph.Org. This test profile is a single-threaded test measuring the time to denoise a sample 26 minute long 16-bit RAW audio file using this recurrent neural network noise suppression library. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Seconds, Fewer Is Better RNNoise 2020-06-28 eVGA NVIDIA GeForce GTX 780 5 10 15 20 25 SE +/- 0.14, N = 3 22.88 1. (CC) gcc options: -O2 -pedantic -fvisibility=hidden -lm
OpenBenchmarking.org ms, Fewer Is Better PostgreSQL pgbench 13.0 Scaling Factor: 1 - Clients: 1 - Mode: Read Only - Average Latency eVGA NVIDIA GeForce GTX 780 0.0128 0.0256 0.0384 0.0512 0.064 SE +/- 0.000, N = 3 0.057 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
OpenBenchmarking.org TPS, More Is Better PostgreSQL pgbench 13.0 Scaling Factor: 1 - Clients: 1 - Mode: Read Write eVGA NVIDIA GeForce GTX 780 160 320 480 640 800 SE +/- 1.90, N = 3 736 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
OpenBenchmarking.org ms, Fewer Is Better PostgreSQL pgbench 13.0 Scaling Factor: 1 - Clients: 1 - Mode: Read Write - Average Latency eVGA NVIDIA GeForce GTX 780 0.3056 0.6112 0.9168 1.2224 1.528 SE +/- 0.004, N = 3 1.358 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
OpenBenchmarking.org TPS, More Is Better PostgreSQL pgbench 13.0 Scaling Factor: 1 - Clients: 50 - Mode: Read Only eVGA NVIDIA GeForce GTX 780 40K 80K 120K 160K 200K SE +/- 208.15, N = 3 193628 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
OpenBenchmarking.org ms, Fewer Is Better PostgreSQL pgbench 13.0 Scaling Factor: 1 - Clients: 50 - Mode: Read Only - Average Latency eVGA NVIDIA GeForce GTX 780 0.0581 0.1162 0.1743 0.2324 0.2905 SE +/- 0.000, N = 3 0.258 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
OpenBenchmarking.org TPS, More Is Better PostgreSQL pgbench 13.0 Scaling Factor: 1 - Clients: 100 - Mode: Read Only eVGA NVIDIA GeForce GTX 780 40K 80K 120K 160K 200K SE +/- 671.97, N = 3 197128 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
OpenBenchmarking.org ms, Fewer Is Better PostgreSQL pgbench 13.0 Scaling Factor: 1 - Clients: 100 - Mode: Read Only - Average Latency eVGA NVIDIA GeForce GTX 780 0.1141 0.2282 0.3423 0.4564 0.5705 SE +/- 0.002, N = 3 0.507 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
OpenBenchmarking.org TPS, More Is Better PostgreSQL pgbench 13.0 Scaling Factor: 1 - Clients: 250 - Mode: Read Only eVGA NVIDIA GeForce GTX 780 40K 80K 120K 160K 200K SE +/- 2896.56, N = 3 177176 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
OpenBenchmarking.org ms, Fewer Is Better PostgreSQL pgbench 13.0 Scaling Factor: 1 - Clients: 250 - Mode: Read Only - Average Latency eVGA NVIDIA GeForce GTX 780 0.3177 0.6354 0.9531 1.2708 1.5885 SE +/- 0.023, N = 3 1.412 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
OpenBenchmarking.org TPS, More Is Better PostgreSQL pgbench 13.0 Scaling Factor: 1 - Clients: 50 - Mode: Read Write eVGA NVIDIA GeForce GTX 780 200 400 600 800 1000 SE +/- 0.80, N = 3 919 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
OpenBenchmarking.org ms, Fewer Is Better PostgreSQL pgbench 13.0 Scaling Factor: 1 - Clients: 50 - Mode: Read Write - Average Latency eVGA NVIDIA GeForce GTX 780 12 24 36 48 60 SE +/- 0.05, N = 3 54.39 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
OpenBenchmarking.org TPS, More Is Better PostgreSQL pgbench 13.0 Scaling Factor: 100 - Clients: 1 - Mode: Read Only eVGA NVIDIA GeForce GTX 780 3K 6K 9K 12K 15K SE +/- 136.14, N = 3 15522 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
OpenBenchmarking.org ms, Fewer Is Better PostgreSQL pgbench 13.0 Scaling Factor: 100 - Clients: 1 - Mode: Read Only - Average Latency eVGA NVIDIA GeForce GTX 780 0.0144 0.0288 0.0432 0.0576 0.072 SE +/- 0.001, N = 3 0.064 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
OpenBenchmarking.org TPS, More Is Better PostgreSQL pgbench 13.0 Scaling Factor: 1 - Clients: 100 - Mode: Read Write eVGA NVIDIA GeForce GTX 780 200 400 600 800 1000 SE +/- 1.77, N = 3 874 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
OpenBenchmarking.org ms, Fewer Is Better PostgreSQL pgbench 13.0 Scaling Factor: 1 - Clients: 100 - Mode: Read Write - Average Latency eVGA NVIDIA GeForce GTX 780 30 60 90 120 150 SE +/- 0.23, N = 3 114.43 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
OpenBenchmarking.org TPS, More Is Better PostgreSQL pgbench 13.0 Scaling Factor: 1 - Clients: 250 - Mode: Read Write eVGA NVIDIA GeForce GTX 780 200 400 600 800 1000 SE +/- 10.84, N = 4 788 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
OpenBenchmarking.org ms, Fewer Is Better PostgreSQL pgbench 13.0 Scaling Factor: 1 - Clients: 250 - Mode: Read Write - Average Latency eVGA NVIDIA GeForce GTX 780 70 140 210 280 350 SE +/- 4.40, N = 4 317.42 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
OpenBenchmarking.org TPS, More Is Better PostgreSQL pgbench 13.0 Scaling Factor: 100 - Clients: 1 - Mode: Read Write eVGA NVIDIA GeForce GTX 780 110 220 330 440 550 SE +/- 16.40, N = 12 523 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
OpenBenchmarking.org ms, Fewer Is Better PostgreSQL pgbench 13.0 Scaling Factor: 100 - Clients: 1 - Mode: Read Write - Average Latency eVGA NVIDIA GeForce GTX 780 0.4349 0.8698 1.3047 1.7396 2.1745 SE +/- 0.061, N = 12 1.933 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
OpenBenchmarking.org TPS, More Is Better PostgreSQL pgbench 13.0 Scaling Factor: 100 - Clients: 50 - Mode: Read Only eVGA NVIDIA GeForce GTX 780 40K 80K 120K 160K 200K SE +/- 324.10, N = 3 163962 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
OpenBenchmarking.org ms, Fewer Is Better PostgreSQL pgbench 13.0 Scaling Factor: 100 - Clients: 50 - Mode: Read Only - Average Latency eVGA NVIDIA GeForce GTX 780 0.0686 0.1372 0.2058 0.2744 0.343 SE +/- 0.001, N = 3 0.305 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
OpenBenchmarking.org TPS, More Is Better PostgreSQL pgbench 13.0 Scaling Factor: 100 - Clients: 100 - Mode: Read Only eVGA NVIDIA GeForce GTX 780 30K 60K 90K 120K 150K SE +/- 131.50, N = 3 151694 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
OpenBenchmarking.org ms, Fewer Is Better PostgreSQL pgbench 13.0 Scaling Factor: 100 - Clients: 100 - Mode: Read Only - Average Latency eVGA NVIDIA GeForce GTX 780 0.1483 0.2966 0.4449 0.5932 0.7415 SE +/- 0.001, N = 3 0.659 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
OpenBenchmarking.org TPS, More Is Better PostgreSQL pgbench 13.0 Scaling Factor: 100 - Clients: 250 - Mode: Read Only eVGA NVIDIA GeForce GTX 780 30K 60K 90K 120K 150K SE +/- 356.47, N = 3 132122 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
OpenBenchmarking.org ms, Fewer Is Better PostgreSQL pgbench 13.0 Scaling Factor: 100 - Clients: 250 - Mode: Read Only - Average Latency eVGA NVIDIA GeForce GTX 780 0.4257 0.8514 1.2771 1.7028 2.1285 SE +/- 0.005, N = 3 1.892 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
OpenBenchmarking.org TPS, More Is Better PostgreSQL pgbench 13.0 Scaling Factor: 100 - Clients: 50 - Mode: Read Write eVGA NVIDIA GeForce GTX 780 1600 3200 4800 6400 8000 SE +/- 64.90, N = 15 7275 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
OpenBenchmarking.org ms, Fewer Is Better PostgreSQL pgbench 13.0 Scaling Factor: 100 - Clients: 50 - Mode: Read Write - Average Latency eVGA NVIDIA GeForce GTX 780 2 4 6 8 10 SE +/- 0.067, N = 15 6.882 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
OpenBenchmarking.org TPS, More Is Better PostgreSQL pgbench 13.0 Scaling Factor: 100 - Clients: 100 - Mode: Read Write eVGA NVIDIA GeForce GTX 780 2K 4K 6K 8K 10K SE +/- 62.41, N = 3 8692 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
OpenBenchmarking.org ms, Fewer Is Better PostgreSQL pgbench 13.0 Scaling Factor: 100 - Clients: 100 - Mode: Read Write - Average Latency eVGA NVIDIA GeForce GTX 780 3 6 9 12 15 SE +/- 0.08, N = 3 11.51 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
OpenBenchmarking.org TPS, More Is Better PostgreSQL pgbench 13.0 Scaling Factor: 100 - Clients: 250 - Mode: Read Write eVGA NVIDIA GeForce GTX 780 2K 4K 6K 8K 10K SE +/- 134.25, N = 4 8965 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
OpenBenchmarking.org ms, Fewer Is Better PostgreSQL pgbench 13.0 Scaling Factor: 100 - Clients: 250 - Mode: Read Write - Average Latency eVGA NVIDIA GeForce GTX 780 7 14 21 28 35 SE +/- 0.41, N = 4 27.91 1. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lpthread -lrt -ldl -lm
Mobile Neural Network MNN is the Mobile Neural Network as a highly efficient, lightweight deep learning framework developed by ALibaba. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org ms, Fewer Is Better Mobile Neural Network 2020-09-17 Model: SqueezeNetV1.0 eVGA NVIDIA GeForce GTX 780 3 6 9 12 15 SE +/- 0.14, N = 3 11.37 MIN: 11.01 / MAX: 24.3 1. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl
OpenBenchmarking.org ms, Fewer Is Better Mobile Neural Network 2020-09-17 Model: resnet-v2-50 eVGA NVIDIA GeForce GTX 780 14 28 42 56 70 SE +/- 0.48, N = 3 62.95 MIN: 61.74 / MAX: 80.43 1. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl
OpenBenchmarking.org ms, Fewer Is Better Mobile Neural Network 2020-09-17 Model: MobileNetV2_224 eVGA NVIDIA GeForce GTX 780 2 4 6 8 10 SE +/- 0.029, N = 3 6.357 MIN: 6.17 / MAX: 12.53 1. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl
OpenBenchmarking.org ms, Fewer Is Better Mobile Neural Network 2020-09-17 Model: mobilenet-v1-1.0 eVGA NVIDIA GeForce GTX 780 3 6 9 12 15 SE +/- 0.02, N = 3 12.09 MIN: 11.96 / MAX: 17.03 1. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl
OpenBenchmarking.org ms, Fewer Is Better Mobile Neural Network 2020-09-17 Model: inception-v3 eVGA NVIDIA GeForce GTX 780 15 30 45 60 75 SE +/- 1.78, N = 3 67.71 MIN: 64.71 / MAX: 156 1. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl
OpenBenchmarking.org ms, Fewer Is Better TNN 0.2.3 Target: CPU - Model: SqueezeNet v1.1 eVGA NVIDIA GeForce GTX 780 70 140 210 280 350 SE +/- 1.18, N = 3 300.00 MIN: 295.59 / MAX: 306.37 1. (CXX) g++ options: -fopenmp -pthread -fvisibility=hidden -O2 -rdynamic -ldl
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.org Throughput FoM, More Is Better Kripke 1.2.4 eVGA NVIDIA GeForce GTX 780 2M 4M 6M 8M 10M SE +/- 140177.31, N = 3 8596706 1. (CXX) g++ options: -O2 -fopenmp
eVGA NVIDIA GeForce GTX 780 Processor: AMD Ryzen 7 1700X Eight-Core @ 3.40GHz (8 Cores / 16 Threads), Motherboard: MSI X470 GAMING PLUS MAX (MS-7B79) v3.0 (H.60 BIOS), Chipset: AMD 17h, Memory: 16GB, Disk: Samsung SSD 970 EVO Plus 500GB + 128GB ADATA SP900 + 120GB SSD2SC120G3LA726 + 3001GB Hitachi HUS72403, Graphics: eVGA NVIDIA GeForce GTX 780 3GB (941/3004MHz), Audio: NVIDIA GK110 HD Audio, Monitor: DELL 2208WFP + R241Y, Network: Realtek RTL8111/8168/8411
OS: Fedora 32, Kernel: 5.8.13-200.fc32.x86_64 (x86_64), Desktop: GNOME Shell 3.36.6, Display Server: X Server 1.20.8, Display Driver: NVIDIA 450.66, OpenGL: 4.6.0, Vulkan: 1.2.133, Compiler: GCC 10.2.1 20200723 + Clang 10.0.1, File-System: ext4, Screen Resolution: 1680x1050
Compiler Notes: --build=x86_64-redhat-linux --disable-libunwind-exceptions --enable-__cxa_atexit --enable-bootstrap --enable-cet --enable-checking=release --enable-gnu-indirect-function --enable-gnu-unique-object --enable-initfini-array --enable-languages=c,c++,fortran,objc,obj-c++,ada,go,d,lto --enable-multilib --enable-offload-targets=nvptx-none --enable-plugin --enable-shared --enable-threads=posix --mandir=/usr/share/man --with-arch_32=i686 --with-gcc-major-version-only --with-isl --with-linker-hash-style=gnu --with-tune=generic --without-cuda-driverProcessor Notes: Scaling Governor: acpi-cpufreq ondemand - CPU Microcode: 0x8001138OpenCL Notes: GPU Compute Cores: 2304Python Notes: Python 3.8.5Security Notes: SELinux + 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: disabled RSB filling + srbds: Not affected + tsx_async_abort: Not affected
Testing initiated at 9 October 2020 07:21 by user svmlegacy.