X3D Zen 4

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Ryzen 9 7900X3D
March 03 2023
  14 Hours, 36 Minutes
Ryzen 9 7900X
March 04 2023
  15 Hours, 29 Minutes
Ryzen 9 79500X3D
March 04 2023
  15 Hours, 2 Minutes
Ryzen 9 7950X
March 05 2023
  14 Hours, 35 Minutes
Invert Behavior (Only Show Selected Data)
  14 Hours, 56 Minutes

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Ryzen 9 7900X3D

Processor: AMD Ryzen 9 7900X3D 12-Core @ 4.40GHz (12 Cores / 24 Threads), Motherboard: ASUS ROG CROSSHAIR X670E HERO (9922 BIOS), Chipset: AMD Device 14d8, Memory: 32GB, Disk: Western Digital WD_BLACK SN850X 1000GB + 2000GB, Graphics: AMD Radeon RX 7900 XTX 24GB (2304/1249MHz), Audio: AMD Device ab30, Monitor: ASUS MG28U, Network: Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411

OS: Ubuntu 23.04, Kernel: 6.2.2-060202-generic (x86_64), Desktop: GNOME Shell 43.2, Display Server: X Server 1.21.1.6 + Wayland, OpenGL: 4.6 Mesa 23.1.0-devel (git-efcb639 2023-02-13 lunar-oibaf-ppa) (LLVM 15.0.7 DRM 3.49), Compiler: GCC 12.2.0, File-System: ext4, Screen Resolution: 3840x2160

Kernel Notes: Transparent Huge Pages: madvise
Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-cet --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-defaulted --enable-offload-targets=nvptx-none=/build/gcc-12-AKimc9/gcc-12-12.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-12-AKimc9/gcc-12-12.2.0/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-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: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0xa601203
Python Notes: Python 3.11.1
Security Notes: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Retpolines IBPB: conditional IBRS_FW STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected

Ryzen 9 7900X

Changed Processor to AMD Ryzen 9 7900X 12-Core @ 4.70GHz (12 Cores / 24 Threads).

Ryzen 9 79500X3D

Changed Processor to AMD Ryzen 9 7950X3D 16-Core @ 4.20GHz (16 Cores / 32 Threads).

Ryzen 9 7950X

Changed Processor to AMD Ryzen 9 7950X 16-Core @ 4.50GHz (16 Cores / 32 Threads).

X3D Zen 4OpenBenchmarking.orgPhoronix Test SuiteAMD Ryzen 9 7900X3D 12-Core @ 4.40GHz (12 Cores / 24 Threads)AMD Ryzen 9 7900X 12-Core @ 4.70GHz (12 Cores / 24 Threads)AMD Ryzen 9 7950X3D 16-Core @ 4.20GHz (16 Cores / 32 Threads)AMD Ryzen 9 7950X 16-Core @ 4.50GHz (16 Cores / 32 Threads)ASUS ROG CROSSHAIR X670E HERO (9922 BIOS)AMD Device 14d832GBWestern Digital WD_BLACK SN850X 1000GB + 2000GBAMD Radeon RX 7900 XTX 24GB (2304/1249MHz)AMD Device ab30ASUS MG28UIntel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411Ubuntu 23.046.2.2-060202-generic (x86_64)GNOME Shell 43.2X Server 1.21.1.6 + Wayland4.6 Mesa 23.1.0-devel (git-efcb639 2023-02-13 lunar-oibaf-ppa) (LLVM 15.0.7 DRM 3.49)GCC 12.2.0ext43840x2160ProcessorsMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelDesktopDisplay ServerOpenGLCompilerFile-SystemScreen ResolutionX3D Zen 4 BenchmarksSystem Logs- Transparent Huge Pages: madvise- --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-cet --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-defaulted --enable-offload-targets=nvptx-none=/build/gcc-12-AKimc9/gcc-12-12.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-12-AKimc9/gcc-12-12.2.0/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-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 performance (Boost: Enabled) - CPU Microcode: 0xa601203- Python 3.11.1- itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Retpolines IBPB: conditional IBRS_FW STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected

Ryzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950XResult OverviewPhoronix Test Suite100%118%135%153%CloverLeafPennantACES DGEMMEmbreeoneDNNASKAPXmrigKTX-Software toktxOpenVINOGPAWGROMACSTensorFlowOpenFOAMXcompact3d Incompact3dClickHouseONNX RuntimeLULESHsrsRANZstd CompressionNCNNLeelaChessZeroPyHPC Benchmarks

X3D Zen 4onnx: fcn-resnet101-11 - CPU - Standardaskap: tConvolve OpenMP - Degriddingcloverleaf: Lagrangian-Eulerian Hydrodynamicsonednn: IP Shapes 1D - bf16bf16bf16 - CPUopenvino: Vehicle Detection FP16 - CPUpennant: leblancbigopenvino: Weld Porosity Detection FP16-INT8 - CPUopenvino: Age Gender Recognition Retail 0013 FP16 - CPUopenvino: Age Gender Recognition Retail 0013 FP16-INT8 - CPUopenvino: Vehicle Detection FP16-INT8 - CPUopenvino: Face Detection FP16-INT8 - CPUopenvino: Weld Porosity Detection FP16 - CPUonednn: Deconvolution Batch shapes_3d - bf16bf16bf16 - CPUonednn: Deconvolution Batch shapes_1d - bf16bf16bf16 - CPUonednn: Matrix Multiply Batch Shapes Transformer - bf16bf16bf16 - CPUopenvino: Face Detection FP16 - CPUtoktx: UASTC 4 + Zstd Compression 19onnx: super-resolution-10 - CPU - Parallelopenvino: Person Vehicle Bike Detection FP16 - CPUonednn: IP Shapes 3D - bf16bf16bf16 - CPUonednn: Recurrent Neural Network Inference - bf16bf16bf16 - CPUonednn: Recurrent Neural Network Training - bf16bf16bf16 - CPUxmrig: Wownero - 1Mmt-dgemm: Sustained Floating-Point Rateopenvino: Person Detection FP16 - CPUpennant: sedovbigopenvino: Vehicle Detection FP16 - CPUopenfoam: drivaerFastback, Small Mesh Size - Execution Timeembree: Pathtracer ISPC - Crownaskap: tConvolve OpenMP - Griddingembree: Pathtracer - Crownopenvino: Person Detection FP32 - CPUtensorflow: CPU - 256 - AlexNetembree: Pathtracer - Asian Dragontoktx: UASTC 3onnx: fcn-resnet101-11 - CPU - Parallelembree: Pathtracer - Asian Dragon Objembree: Pathtracer ISPC - Asian Dragon Objonnx: ArcFace ResNet-100 - CPU - Parallelembree: Pathtracer ISPC - Asian Dragonopenvino: Machine Translation EN To DE FP16 - CPUtensorflow: CPU - 64 - AlexNetonnx: bertsquad-12 - CPU - Parallelcompress-zstd: 8 - Compression Speedonnx: yolov4 - CPU - Parallelaskap: Hogbom Clean OpenMPcompress-zstd: 8, Long Mode - Compression Speedsrsran: 4G PHY_DL_Test 100 PRB SISO 256-QAMonnx: ResNet50 v1-12-int8 - CPU - Parallelncnn: CPU - vision_transformercompress-zstd: 19, Long Mode - Compression Speedcompress-zstd: 12 - Compression Speedtoktx: UASTC 3 + Zstd Compression 19ncnn: CPU - regnety_400mgpaw: Carbon Nanotubegromacs: MPI CPU - water_GMX50_baretensorflow: CPU - 32 - AlexNetxmrig: Monero - 1Mtensorflow: CPU - 256 - GoogLeNettensorflow: CPU - 32 - GoogLeNetncnn: CPU - blazefaceonnx: CaffeNet 12-int8 - CPU - Paralleltensorflow: CPU - 16 - GoogLeNettensorflow: CPU - 64 - GoogLeNetincompact3d: input.i3d 129 Cells Per Directionncnn: CPU - alexnetclickhouse: 100M Rows Hits Dataset, Third Runincompact3d: input.i3d 193 Cells Per Directionopenfoam: drivaerFastback, Medium Mesh Size - Execution Timeonnx: GPT-2 - CPU - Standardtensorflow: CPU - 256 - ResNet-50clickhouse: 100M Rows Hits Dataset, Second Runopenfoam: drivaerFastback, Small Mesh Size - Mesh Timeaskap: tConvolve MT - Griddingsrsran: 4G PHY_DL_Test 100 PRB SISO 256-QAMtensorflow: CPU - 64 - ResNet-50compress-zstd: 3 - Compression Speedtensorflow: CPU - 32 - ResNet-50tensorflow: CPU - 16 - ResNet-50onnx: bertsquad-12 - CPU - Standardonnx: GPT-2 - CPU - Parallelopenfoam: drivaerFastback, Medium Mesh Size - Mesh Timeclickhouse: 100M Rows Hits Dataset, First Run / Cold Cacheopenvino: Age Gender Recognition Retail 0013 FP16-INT8 - CPUncnn: CPU - shufflenet-v2askap: tConvolve MPI - Griddingopenvino: Age Gender Recognition Retail 0013 FP16 - CPUtensorflow: CPU - 16 - AlexNetopenvino: Weld Porosity Detection FP16-INT8 - CPUopenvino: Machine Translation EN To DE FP16 - CPUopenvino: Vehicle Detection FP16-INT8 - CPUaskap: tConvolve MPI - Degriddingopenvino: Weld Porosity Detection FP16 - CPUopenvino: Face Detection FP16-INT8 - CPUaskap: tConvolve MT - Degriddingopenvino: Person Detection FP16 - CPUcompress-zstd: 19 - Compression Speedopenvino: Person Detection FP32 - CPUopenvino: Face Detection FP16 - CPUncnn: CPU-v2-v2 - mobilenet-v2ncnn: CPU - mnasnetncnn: CPU - mobilenetonnx: Faster R-CNN R-50-FPN-int8 - CPU - Parallelcompress-zstd: 3, Long Mode - Compression Speedncnn: CPU - efficientnet-b0ncnn: CPU - vgg16openvino: Person Vehicle Bike Detection FP16 - CPUlulesh: ncnn: CPU-v3-v3 - mobilenet-v3ncnn: CPU - resnet50ncnn: CPU - squeezenet_ssdsrsran: OFDM_Testsrsran: 4G PHY_DL_Test 100 PRB MIMO 64-QAMtoktx: Zstd Compression 19ncnn: CPU - yolov4-tinycompress-zstd: 19 - Decompression Speedsrsran: 4G PHY_DL_Test 100 PRB MIMO 64-QAMlczero: BLASsrsran: 4G PHY_DL_Test 100 PRB MIMO 256-QAMsrsran: 4G PHY_DL_Test 100 PRB MIMO 256-QAMcompress-zstd: 8, Long Mode - Decompression Speedpyhpc: CPU - Numpy - 4194304 - Equation of Statepyhpc: CPU - Numpy - 4194304 - Isoneutral Mixingsrsran: 4G PHY_DL_Test 100 PRB SISO 64-QAMcompress-zstd: 3 - Decompression Speedsrsran: 4G PHY_DL_Test 100 PRB SISO 64-QAMcompress-zstd: 8 - Decompression Speedcompress-zstd: 3, Long Mode - Decompression Speedlczero: Eigensrsran: 5G PHY_DL_NR Test 52 PRB SISO 64-QAMcompress-zstd: 12 - Decompression Speedncnn: CPU - FastestDetncnn: CPU - resnet18ncnn: CPU - googlenetsrsran: 5G PHY_DL_NR Test 52 PRB SISO 64-QAMonednn: Convolution Batch Shapes Auto - bf16bf16bf16 - CPUcompress-zstd: 19, Long Mode - Decompression Speedonnx: Faster R-CNN R-50-FPN-int8 - CPU - Parallelonnx: Faster R-CNN R-50-FPN-int8 - CPU - Standardonnx: Faster R-CNN R-50-FPN-int8 - CPU - Standardonnx: CaffeNet 12-int8 - CPU - Parallelonnx: CaffeNet 12-int8 - CPU - Standardonnx: CaffeNet 12-int8 - CPU - Standardonnx: ResNet50 v1-12-int8 - CPU - Parallelonnx: ResNet50 v1-12-int8 - CPU - Standardonnx: ResNet50 v1-12-int8 - CPU - Standardonnx: ArcFace ResNet-100 - CPU - Parallelonnx: ArcFace ResNet-100 - CPU - Standardonnx: ArcFace ResNet-100 - CPU - Standardonnx: GPT-2 - CPU - Parallelonnx: GPT-2 - CPU - Standardonnx: bertsquad-12 - CPU - Parallelonnx: bertsquad-12 - CPU - Standardonnx: super-resolution-10 - CPU - Parallelonnx: super-resolution-10 - CPU - Standardonnx: super-resolution-10 - CPU - Standardonnx: fcn-resnet101-11 - CPU - Parallelonnx: fcn-resnet101-11 - CPU - Standardonnx: yolov4 - CPU - Parallelonnx: yolov4 - CPU - Standardonnx: yolov4 - CPU - StandardRyzen 9 7900X3DRyzen 9 7900XRyzen 9 79500X3DRyzen 9 7950X2.8737710078.0631.281.07510801.8719.310421959.5230316.7517663.841257.3819.641000.472.029035.181720.30346410.15169.16599.05481188.171.16165803.7141560.8614966.18.2155525.6030.937667.48138.7360527.04596052.1624.22555.61328.3726.55256.3741.5053623.832426.960328.455531.4349107.76278.3012.89291026.57.97025545.861940.9215.8335.70592.6514.3298.310.03711.06143.1502.278223.0313564.7118.96126.271.49802.979124.65123.2612.69032104.60308.8161.96296031948.056195.76038.89303.4826.2090672100.99585.939.063710.739.0138.1118.8205157.292193.35589269.000.673.7312051.30.39158.976.1255.654.779923.935.99304.862906.781065.8225.21064.33589.393.573.259.3348.26451319.64.5725.945.048953.04613.1412.4711.57237333333614.911.52814.732082.1235.31882665.2250.32365.30.7261.081619.72162.4250.62352.92217.41767209.92453.84.367.089.03136.81.381441876.320.717714.509368.92071.244810.8655051155.142.978222.36463424.16935.142725.563839.73686.353625.1069077.567153.137210.09477.51702138.327664.593347.973125.467102.271110.078321.750535756.7749.630.979499666.3525.146122176.1133984.4019661.301358.9021.441089.161.798304.710130.26482610.95157.108112.4151265.141.51749731.3761434.0615870.68.2481205.9736.880989.00171.6184627.63925024.8924.67885.90353.6026.50795.9441.5796323.815826.494131.258230.8877112.02294.4913.8656857.48.60115440.183808.5264.6374.01184.5713.0248.89.69810.05150.8682.270232.3013863.0123.87127.671.38830.069128.74125.6214.61150104.98290.1468.21861272161.5558172.80940.36285.4125.0164072002.69669.440.204014.340.0038.919.7271146.338199.34498258.640.603.4611693.20.35162.665.5153.544.4110092.15.50279.482755.491000.8823.41012.48546.203.503.178.8449.49731393.74.3125.744.748484.56613.1312.3811.78237000000627.111.63714.242101.8240.61879677.8254.92410.40.7141.057622.72184251.12393.02249.41772211.62452.04.227.778.82145.31.812911997.420.201716.881460.10651.204271.014088998.8602.673092.33461430.95931.993623.944842.37886.831775.7943572.137450.69038.895055.85153173.784633.095571.286116.265101.171910.110333.5394111369.629.180.7295101003.4816.860822616.0840658.9623679.431706.6826.261330.531.507153.958860.22977313.53126.296124.5301658.151.08373623.3941209.1219562.911.2584067.3227.035247.97125.9854236.23796780.7932.07277.27418.9734.70355.1261.9134731.009234.164233.592739.7144135.50339.8014.80881053.79.44018548.2501004.2258.5384.71682.0315.0292.48.74711.96126.8992.695258.7715627.4137.77149.391.63947.635147.01145.2912.53925374.28321.7658.77319241863.9535185.38443.88316.8423.9068452293.31660.144.203959.644.2743.1920.1907164.532178.10769279.870.673.86124950.39176.226.1158.994.6810858.86.01304.022995.191085.0825.21094.43589.453.763.408.8749.66051338.34.6024.344.828987.93913.3111.8611.72245966667638.311.46014.282030.5243.81945686.0256.82422.10.7311.074616.32203.6252.02391.62254.01787211.52452.84.686.608.52144.21.086401872.420.140014.448670.15531.054360.9381491084.9072.598832.06799486.61229.770027.308137.39456.074385.3941667.547849.53568.029606.29145161.230522.692282.644105.929101.97409.996042.228366156.8247.000.664360784.2524.358772892.6344741.9726015.991843.328.371442.531.408493.607480.21280114.38119.500139.4251670.931.52232578.9111130.4420609.410.9839977.6534.8457710.19161.6749236.55496099.2232.53437.53439.5433.63244.8851.9638129.815331.778336.625637.2215138.14351.0716.2344837.49.95491448.459845.7261.8411.00775.7612.5253.68.40511.48138.0142.607264.3313188.9140.76147.081.54922.337146.99143.8814.62683684.86276.9466.21399432126.1028169.50244.87275.4522.7938082173.95665.844.584227.644.3943.0821.2755146.497190.93673250.500.613.6211211.20.35176.725.5357.854.3410788.85.54281.592833.491040.7223.31057.42554.423.623.238.7051.74241413.94.4024.614.788479.87763.1512.1712.14236600000617.811.22014.212104.4236.91915667.0250.72390.40.7271.057609.02170.1247.42379.12223.81773209.52439.94.467.468.58142.92.108311990.019.327414.265670.09101.083330.8169941224.002.432392.06309485.24127.303022.568244.79416.822615.8978261.610747.00197.171846.14984165.007509.325448.764100.4948100.747110.08625OpenBenchmarking.org

ONNX Runtime

ONNX Runtime is developed by Microsoft and partners as a open-source, cross-platform, high performance machine learning inferencing and training accelerator. This test profile runs the ONNX Runtime with various models available from the ONNX Model Zoo. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: fcn-resnet101-11 - Device: CPU - Executor: StandardRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X0.79641.59282.38923.18563.982SE +/- 0.00921, N = 3SE +/- 0.00156, N = 3SE +/- 0.04984, N = 3SE +/- 0.00558, N = 31.750532.873773.539412.228361. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: fcn-resnet101-11 - Device: CPU - Executor: StandardRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X120240360480600SE +/- 3.02, N = 3SE +/- 0.19, N = 3SE +/- 4.02, N = 3SE +/- 1.13, N = 3571.29347.97282.64448.761. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

ASKAP

ASKAP is a set of benchmarks from the Australian SKA Pathfinder. The principal ASKAP benchmarks are the Hogbom Clean Benchmark (tHogbomClean) and Convolutional Resamping Benchmark (tConvolve) as well as some previous ASKAP benchmarks being included as well for OpenCL and CUDA execution of tConvolve. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMillion Grid Points Per Second, More Is BetterASKAP 1.0Test: tConvolve OpenMP - DegriddingRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X2K4K6K8K10KSE +/- 107.63, N = 6SE +/- 76.62, N = 7SE +/- 97.44, N = 7SE +/- 35.18, N = 45756.7710078.0611369.606156.821. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp

CloverLeaf

CloverLeaf is a Lagrangian-Eulerian hydrodynamics benchmark. This test profile currently makes use of CloverLeaf's OpenMP version and benchmarked with the clover_bm.in input file (Problem 5). Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterCloverLeafLagrangian-Eulerian HydrodynamicsRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X1122334455SE +/- 0.50, N = 3SE +/- 0.07, N = 3SE +/- 0.10, N = 3SE +/- 0.12, N = 349.6331.2829.1847.001. (F9X) gfortran options: -O3 -march=native -funroll-loops -fopenmp

oneDNN

This is a test of the Intel oneDNN as an Intel-optimized library for Deep Neural Networks and making use of its built-in benchdnn functionality. The result is the total perf time reported. Intel oneDNN was formerly known as DNNL (Deep Neural Network Library) and MKL-DNN before being rebranded as part of the Intel oneAPI toolkit. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.0Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPURyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X0.24190.48380.72570.96761.2095SE +/- 0.004105, N = 4SE +/- 0.002405, N = 4SE +/- 0.010030, N = 15SE +/- 0.006372, N = 150.9794991.0751000.7295100.664360MIN: 0.91MIN: 1.03MIN: 0.63MIN: 0.591. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread

OpenVINO

This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Vehicle Detection FP16 - Device: CPURyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X2004006008001000SE +/- 9.18, N = 3SE +/- 2.18, N = 3SE +/- 3.11, N = 3SE +/- 3.17, N = 3666.35801.871003.48784.251. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

Pennant

Pennant is an application focused on hydrodynamics on general unstructured meshes in 2D. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgHydro Cycle Time - Seconds, Fewer Is BetterPennant 1.0.1Test: leblancbigRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X612182430SE +/- 0.01, N = 3SE +/- 0.03, N = 3SE +/- 0.03, N = 3SE +/- 0.02, N = 325.1519.3116.8624.361. (CXX) g++ options: -fopenmp -lmpi_cxx -lmpi

OpenVINO

This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Weld Porosity Detection FP16-INT8 - Device: CPURyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X6001200180024003000SE +/- 13.39, N = 3SE +/- 0.41, N = 3SE +/- 2.92, N = 3SE +/- 2.33, N = 32176.111959.522616.082892.631. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Age Gender Recognition Retail 0013 FP16 - Device: CPURyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X10K20K30K40K50KSE +/- 51.92, N = 3SE +/- 15.66, N = 3SE +/- 72.52, N = 3SE +/- 86.54, N = 333984.4030316.7540658.9644741.971. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPURyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X6K12K18K24K30KSE +/- 119.95, N = 3SE +/- 3.40, N = 3SE +/- 77.85, N = 3SE +/- 29.30, N = 319661.3017663.8423679.4326015.991. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Vehicle Detection FP16-INT8 - Device: CPURyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X400800120016002000SE +/- 6.32, N = 3SE +/- 0.73, N = 3SE +/- 3.94, N = 3SE +/- 2.59, N = 31358.901257.381706.681843.301. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Face Detection FP16-INT8 - Device: CPURyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X714212835SE +/- 0.07, N = 3SE +/- 0.01, N = 3SE +/- 0.09, N = 3SE +/- 0.09, N = 321.4419.6426.2628.371. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Weld Porosity Detection FP16 - Device: CPURyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X30060090012001500SE +/- 0.21, N = 3SE +/- 0.24, N = 3SE +/- 0.83, N = 3SE +/- 1.85, N = 31089.161000.471330.531442.531. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

oneDNN

This is a test of the Intel oneDNN as an Intel-optimized library for Deep Neural Networks and making use of its built-in benchdnn functionality. The result is the total perf time reported. Intel oneDNN was formerly known as DNNL (Deep Neural Network Library) and MKL-DNN before being rebranded as part of the Intel oneAPI toolkit. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.0Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPURyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X0.45650.9131.36951.8262.2825SE +/- 0.00295, N = 9SE +/- 0.00266, N = 9SE +/- 0.00172, N = 9SE +/- 0.00250, N = 91.798302.029031.507151.40849MIN: 1.7MIN: 1.97MIN: 1.46MIN: 1.341. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.0Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPURyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X1.16592.33183.49774.66365.8295SE +/- 0.04268, N = 3SE +/- 0.01434, N = 3SE +/- 0.03845, N = 3SE +/- 0.02903, N = 34.710135.181723.958863.60748MIN: 4.54MIN: 4.98MIN: 3.72MIN: 3.431. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.0Harness: Matrix Multiply Batch Shapes Transformer - Data Type: bf16bf16bf16 - Engine: CPURyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X0.06830.13660.20490.27320.3415SE +/- 0.000581, N = 4SE +/- 0.004459, N = 15SE +/- 0.000569, N = 4SE +/- 0.000189, N = 40.2648260.3034640.2297730.212801MIN: 0.25MIN: 0.29MIN: 0.22MIN: 0.21. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread

OpenVINO

This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Face Detection FP16 - Device: CPURyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X48121620SE +/- 0.02, N = 3SE +/- 0.00, N = 3SE +/- 0.03, N = 3SE +/- 0.02, N = 310.9510.1513.5314.381. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

KTX-Software toktx

This is a benchmark of The Khronos Group's KTX-Software library and tools. KTX-Software provides "toktx" for converting/creating in the KTX container format for image textures. This benchmark times how long it takes to convert to KTX 2.0 format with various settings using a reference PNG sample input. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterKTX-Software toktx 4.0Settings: UASTC 4 + Zstd Compression 19Ryzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X4080120160200SE +/- 0.13, N = 3SE +/- 0.05, N = 3SE +/- 0.03, N = 3SE +/- 0.21, N = 3157.11169.17126.30119.50

ONNX Runtime

ONNX Runtime is developed by Microsoft and partners as a open-source, cross-platform, high performance machine learning inferencing and training accelerator. This test profile runs the ONNX Runtime with various models available from the ONNX Model Zoo. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: super-resolution-10 - Device: CPU - Executor: ParallelRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X306090120150SE +/- 0.24, N = 3SE +/- 0.10, N = 3SE +/- 0.24, N = 3SE +/- 0.49, N = 3112.4299.05124.53139.431. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: super-resolution-10 - Device: CPU - Executor: ParallelRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X3691215SE +/- 0.01908, N = 3SE +/- 0.00988, N = 3SE +/- 0.01572, N = 3SE +/- 0.02538, N = 38.8950510.094708.029607.171841. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenVINO

This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Person Vehicle Bike Detection FP16 - Device: CPURyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X400800120016002000SE +/- 11.19, N = 3SE +/- 6.32, N = 3SE +/- 1.97, N = 3SE +/- 9.91, N = 31265.141188.171658.151670.931. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

oneDNN

This is a test of the Intel oneDNN as an Intel-optimized library for Deep Neural Networks and making use of its built-in benchdnn functionality. The result is the total perf time reported. Intel oneDNN was formerly known as DNNL (Deep Neural Network Library) and MKL-DNN before being rebranded as part of the Intel oneAPI toolkit. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.0Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPURyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X0.34250.6851.02751.371.7125SE +/- 0.01359, N = 5SE +/- 0.00690, N = 5SE +/- 0.00875, N = 5SE +/- 0.00933, N = 51.517491.161651.083731.52232MIN: 1.4MIN: 1.08MIN: 0.97MIN: 1.41. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.0Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPURyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X2004006008001000SE +/- 1.56, N = 3SE +/- 2.26, N = 3SE +/- 1.70, N = 3SE +/- 4.41, N = 3731.38803.71623.39578.91MIN: 721.81MIN: 796.39MIN: 614.18MIN: 566.671. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.0Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPURyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X30060090012001500SE +/- 1.79, N = 3SE +/- 1.50, N = 3SE +/- 2.36, N = 3SE +/- 1.31, N = 31434.061560.861209.121130.44MIN: 1423.92MIN: 1554.07MIN: 1195.27MIN: 1121.321. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread

Xmrig

Xmrig is an open-source cross-platform CPU/GPU miner for RandomX, KawPow, CryptoNight and AstroBWT. This test profile is setup to measure the Xmlrig CPU mining performance. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgH/s, More Is BetterXmrig 6.18.1Variant: Wownero - Hash Count: 1MRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X4K8K12K16K20KSE +/- 13.65, N = 3SE +/- 23.48, N = 3SE +/- 21.89, N = 3SE +/- 28.90, N = 315870.614966.119562.920609.41. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc

ACES DGEMM

This is a multi-threaded DGEMM benchmark. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGFLOP/s, More Is BetterACES DGEMM 1.0Sustained Floating-Point RateRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X3691215SE +/- 0.062303, N = 3SE +/- 0.008361, N = 3SE +/- 0.160508, N = 3SE +/- 0.134859, N = 38.2481208.21555211.25840610.9839971. (CC) gcc options: -O3 -march=native -fopenmp

OpenVINO

This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Person Detection FP16 - Device: CPURyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X246810SE +/- 0.05, N = 3SE +/- 0.02, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 35.975.607.327.651. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

Pennant

Pennant is an application focused on hydrodynamics on general unstructured meshes in 2D. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgHydro Cycle Time - Seconds, Fewer Is BetterPennant 1.0.1Test: sedovbigRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X816243240SE +/- 0.14, N = 3SE +/- 0.29, N = 3SE +/- 0.11, N = 3SE +/- 0.02, N = 336.8830.9427.0434.851. (CXX) g++ options: -fopenmp -lmpi_cxx -lmpi

OpenVINO

This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Vehicle Detection FP16 - Device: CPURyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X3691215SE +/- 0.12, N = 3SE +/- 0.02, N = 3SE +/- 0.02, N = 3SE +/- 0.04, N = 39.007.487.9710.19MIN: 4.65 / MAX: 19.47MIN: 4.3 / MAX: 42.8MIN: 4.7 / MAX: 18.6MIN: 4.41 / MAX: 24.51. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

OpenFOAM

OpenFOAM is the leading free, open-source software for computational fluid dynamics (CFD). This test profile currently uses the drivaerFastback test case for analyzing automotive aerodynamics or alternatively the older motorBike input. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterOpenFOAM 10Input: drivaerFastback, Small Mesh Size - Execution TimeRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X4080120160200171.62138.74125.99161.671. (CXX) g++ options: -std=c++14 -m64 -O3 -ftemplate-depth-100 -fPIC -fuse-ld=bfd -Xlinker --add-needed --no-as-needed -lfoamToVTK -ldynamicMesh -llagrangian -lgenericPatchFields -lfileFormats -lOpenFOAM -ldl -lm

Embree

Intel Embree is a collection of high-performance ray-tracing kernels for execution on CPUs (and GPUs via SYCL) and supporting instruction sets such as SSE, AVX, AVX2, and AVX-512. Embree also supports making use of the Intel SPMD Program Compiler (ISPC). Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.0Binary: Pathtracer ISPC - Model: CrownRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X816243240SE +/- 0.10, N = 3SE +/- 0.04, N = 3SE +/- 0.10, N = 3SE +/- 0.12, N = 327.6427.0536.2436.55MIN: 27.15 / MAX: 28.38MIN: 26.79 / MAX: 27.57MIN: 35.78 / MAX: 36.89MIN: 35.98 / MAX: 37.5

ASKAP

ASKAP is a set of benchmarks from the Australian SKA Pathfinder. The principal ASKAP benchmarks are the Hogbom Clean Benchmark (tHogbomClean) and Convolutional Resamping Benchmark (tConvolve) as well as some previous ASKAP benchmarks being included as well for OpenCL and CUDA execution of tConvolve. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMillion Grid Points Per Second, More Is BetterASKAP 1.0Test: tConvolve OpenMP - GriddingRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X15003000450060007500SE +/- 34.63, N = 6SE +/- 30.03, N = 7SE +/- 61.20, N = 7SE +/- 46.08, N = 65024.896052.166780.796099.221. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp

Embree

Intel Embree is a collection of high-performance ray-tracing kernels for execution on CPUs (and GPUs via SYCL) and supporting instruction sets such as SSE, AVX, AVX2, and AVX-512. Embree also supports making use of the Intel SPMD Program Compiler (ISPC). Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.0Binary: Pathtracer - Model: CrownRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X816243240SE +/- 0.03, N = 3SE +/- 0.03, N = 3SE +/- 0.16, N = 3SE +/- 0.05, N = 324.6824.2332.0732.53MIN: 24.44 / MAX: 25.19MIN: 23.99 / MAX: 24.64MIN: 31.5 / MAX: 32.66MIN: 32.17 / MAX: 33.24

OpenVINO

This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Person Detection FP32 - Device: CPURyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X246810SE +/- 0.02, N = 3SE +/- 0.02, N = 3SE +/- 0.04, N = 3SE +/- 0.06, N = 35.905.617.277.531. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries too. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12-rc0Device: CPU - Batch Size: 256 - Model: AlexNetRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X100200300400500SE +/- 0.11, N = 3SE +/- 0.33, N = 3SE +/- 0.24, N = 3SE +/- 0.19, N = 3353.60328.37418.97439.54

Embree

Intel Embree is a collection of high-performance ray-tracing kernels for execution on CPUs (and GPUs via SYCL) and supporting instruction sets such as SSE, AVX, AVX2, and AVX-512. Embree also supports making use of the Intel SPMD Program Compiler (ISPC). Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.0Binary: Pathtracer - Model: Asian DragonRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X816243240SE +/- 0.04, N = 3SE +/- 0.01, N = 3SE +/- 0.05, N = 3SE +/- 0.03, N = 326.5126.5534.7033.63MIN: 26.37 / MAX: 26.79MIN: 26.42 / MAX: 26.93MIN: 34.46 / MAX: 35.13MIN: 33.39 / MAX: 34.01

KTX-Software toktx

This is a benchmark of The Khronos Group's KTX-Software library and tools. KTX-Software provides "toktx" for converting/creating in the KTX container format for image textures. This benchmark times how long it takes to convert to KTX 2.0 format with various settings using a reference PNG sample input. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterKTX-Software toktx 4.0Settings: UASTC 3Ryzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X246810SE +/- 0.006, N = 7SE +/- 0.004, N = 6SE +/- 0.019, N = 7SE +/- 0.003, N = 75.9446.3745.1264.885

ONNX Runtime

ONNX Runtime is developed by Microsoft and partners as a open-source, cross-platform, high performance machine learning inferencing and training accelerator. This test profile runs the ONNX Runtime with various models available from the ONNX Model Zoo. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: fcn-resnet101-11 - Device: CPU - Executor: ParallelRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X0.44190.88381.32571.76762.2095SE +/- 0.00841, N = 3SE +/- 0.01582, N = 5SE +/- 0.01691, N = 3SE +/- 0.02061, N = 31.579631.505361.913471.963811. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: fcn-resnet101-11 - Device: CPU - Executor: ParallelRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X140280420560700SE +/- 3.35, N = 3SE +/- 7.18, N = 5SE +/- 4.59, N = 3SE +/- 5.36, N = 3633.10664.59522.69509.331. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

Embree

Intel Embree is a collection of high-performance ray-tracing kernels for execution on CPUs (and GPUs via SYCL) and supporting instruction sets such as SSE, AVX, AVX2, and AVX-512. Embree also supports making use of the Intel SPMD Program Compiler (ISPC). Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.0Binary: Pathtracer - Model: Asian Dragon ObjRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X714212835SE +/- 0.02, N = 3SE +/- 0.00, N = 3SE +/- 0.03, N = 3SE +/- 0.04, N = 323.8223.8331.0129.82MIN: 23.68 / MAX: 24.06MIN: 23.72 / MAX: 24.15MIN: 30.82 / MAX: 31.62MIN: 29.53 / MAX: 30.29

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.0Binary: Pathtracer ISPC - Model: Asian Dragon ObjRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X816243240SE +/- 0.04, N = 3SE +/- 0.01, N = 3SE +/- 0.07, N = 3SE +/- 0.01, N = 326.4926.9634.1631.78MIN: 26.24 / MAX: 27.06MIN: 26.76 / MAX: 27.4MIN: 33.76 / MAX: 35.23MIN: 31.44 / MAX: 32.76

ONNX Runtime

ONNX Runtime is developed by Microsoft and partners as a open-source, cross-platform, high performance machine learning inferencing and training accelerator. This test profile runs the ONNX Runtime with various models available from the ONNX Model Zoo. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: ArcFace ResNet-100 - Device: CPU - Executor: ParallelRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X816243240SE +/- 0.21, N = 3SE +/- 0.11, N = 3SE +/- 0.21, N = 3SE +/- 0.11, N = 331.2628.4633.5936.631. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: ArcFace ResNet-100 - Device: CPU - Executor: ParallelRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X816243240SE +/- 0.21, N = 3SE +/- 0.13, N = 3SE +/- 0.19, N = 3SE +/- 0.08, N = 331.9935.1429.7727.301. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

Embree

Intel Embree is a collection of high-performance ray-tracing kernels for execution on CPUs (and GPUs via SYCL) and supporting instruction sets such as SSE, AVX, AVX2, and AVX-512. Embree also supports making use of the Intel SPMD Program Compiler (ISPC). Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.0Binary: Pathtracer ISPC - Model: Asian DragonRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X918273645SE +/- 0.01, N = 3SE +/- 0.02, N = 3SE +/- 0.04, N = 4SE +/- 0.01, N = 330.8931.4339.7137.22MIN: 30.69 / MAX: 31.38MIN: 31.23 / MAX: 32MIN: 39.34 / MAX: 40.55MIN: 36.85 / MAX: 38.38

OpenVINO

This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Machine Translation EN To DE FP16 - Device: CPURyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X306090120150SE +/- 0.21, N = 3SE +/- 0.45, N = 3SE +/- 0.53, N = 3SE +/- 0.55, N = 3112.02107.76135.50138.141. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries too. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12-rc0Device: CPU - Batch Size: 64 - Model: AlexNetRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X80160240320400SE +/- 0.30, N = 3SE +/- 0.09, N = 3SE +/- 0.40, N = 3SE +/- 0.64, N = 3294.49278.30339.80351.07

ONNX Runtime

ONNX Runtime is developed by Microsoft and partners as a open-source, cross-platform, high performance machine learning inferencing and training accelerator. This test profile runs the ONNX Runtime with various models available from the ONNX Model Zoo. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: bertsquad-12 - Device: CPU - Executor: ParallelRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X48121620SE +/- 0.15, N = 3SE +/- 0.08, N = 3SE +/- 0.15, N = 4SE +/- 0.18, N = 313.8712.8914.8116.231. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: bertsquad-12 - Device: CPU - Executor: ParallelRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X20406080100SE +/- 0.81, N = 3SE +/- 0.50, N = 3SE +/- 0.70, N = 4SE +/- 0.67, N = 372.1477.5767.5561.611. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

Zstd Compression

This test measures the time needed to compress/decompress a sample file (silesia.tar) using Zstd (Zstandard) compression with options for different compression levels / settings. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.5.4Compression Level: 8 - Compression SpeedRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X2004006008001000SE +/- 1.87, N = 3SE +/- 7.21, N = 3SE +/- 9.05, N = 15SE +/- 3.61, N = 3857.41026.51053.7837.41. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

ONNX Runtime

ONNX Runtime is developed by Microsoft and partners as a open-source, cross-platform, high performance machine learning inferencing and training accelerator. This test profile runs the ONNX Runtime with various models available from the ONNX Model Zoo. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: yolov4 - Device: CPU - Executor: ParallelRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X3691215SE +/- 0.03144, N = 3SE +/- 0.02410, N = 3SE +/- 0.01779, N = 3SE +/- 0.10261, N = 58.601157.970259.440189.954911. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: yolov4 - Device: CPU - Executor: ParallelRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X306090120150SE +/- 0.42, N = 3SE +/- 0.38, N = 3SE +/- 0.20, N = 3SE +/- 1.07, N = 5116.27125.47105.93100.491. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

ASKAP

ASKAP is a set of benchmarks from the Australian SKA Pathfinder. The principal ASKAP benchmarks are the Hogbom Clean Benchmark (tHogbomClean) and Convolutional Resamping Benchmark (tConvolve) as well as some previous ASKAP benchmarks being included as well for OpenCL and CUDA execution of tConvolve. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgIterations Per Second, More Is BetterASKAP 1.0Test: Hogbom Clean OpenMPRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X120240360480600SE +/- 2.17, N = 5SE +/- 1.12, N = 5SE +/- 0.74, N = 5SE +/- 1.79, N = 5440.18545.86548.25448.461. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp

Zstd Compression

This test measures the time needed to compress/decompress a sample file (silesia.tar) using Zstd (Zstandard) compression with options for different compression levels / settings. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.5.4Compression Level: 8, Long Mode - Compression SpeedRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X2004006008001000SE +/- 0.92, N = 3SE +/- 4.92, N = 3SE +/- 1.52, N = 3SE +/- 0.72, N = 3808.5940.91004.2845.71. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

srsRAN

srsRAN is an open-source LTE/5G software radio suite created by Software Radio Systems (SRS). The srsRAN radio suite was formerly known as srsLTE and can be used for building your own software-defined radio (SDR) 4G/5G mobile network. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgUE Mb/s, More Is BettersrsRAN 22.04.1Test: 4G PHY_DL_Test 100 PRB SISO 256-QAMRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X60120180240300SE +/- 0.59, N = 4SE +/- 0.42, N = 15SE +/- 1.65, N = 4SE +/- 0.18, N = 4264.6215.8258.5261.81. (CXX) g++ options: -std=c++14 -fno-strict-aliasing -march=native -mfpmath=sse -mavx2 -fvisibility=hidden -O3 -fno-trapping-math -fno-math-errno -mavx512f -mavx512cd -mavx512bw -mavx512dq -ldl -lpthread -lm

ONNX Runtime

ONNX Runtime is developed by Microsoft and partners as a open-source, cross-platform, high performance machine learning inferencing and training accelerator. This test profile runs the ONNX Runtime with various models available from the ONNX Model Zoo. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: ResNet50 v1-12-int8 - Device: CPU - Executor: ParallelRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X90180270360450SE +/- 1.41, N = 3SE +/- 1.54, N = 3SE +/- 2.07, N = 3SE +/- 0.99, N = 3374.01335.71384.72411.011. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: ResNet50 v1-12-int8 - Device: CPU - Executor: ParallelRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X0.67011.34022.01032.68043.3505SE +/- 0.01009, N = 3SE +/- 0.01374, N = 3SE +/- 0.01408, N = 3SE +/- 0.00583, N = 32.673092.978222.598832.432391. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

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 20220729Target: CPU - Model: vision_transformerRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X20406080100SE +/- 0.26, N = 3SE +/- 0.54, N = 3SE +/- 1.49, N = 3SE +/- 0.63, N = 784.5792.6582.0375.76MIN: 83.77 / MAX: 112.37MIN: 91.31 / MAX: 100.98MIN: 80.21 / MAX: 86.13MIN: 74.12 / MAX: 90.631. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

Zstd Compression

This test measures the time needed to compress/decompress a sample file (silesia.tar) using Zstd (Zstandard) compression with options for different compression levels / settings. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.5.4Compression Level: 19, Long Mode - Compression SpeedRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X48121620SE +/- 0.12, N = 15SE +/- 0.15, N = 15SE +/- 0.03, N = 3SE +/- 0.03, N = 313.014.315.012.51. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.5.4Compression Level: 12 - Compression SpeedRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X60120180240300SE +/- 0.55, N = 3SE +/- 2.69, N = 3SE +/- 1.20, N = 3SE +/- 1.42, N = 3248.8298.3292.4253.61. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

KTX-Software toktx

This is a benchmark of The Khronos Group's KTX-Software library and tools. KTX-Software provides "toktx" for converting/creating in the KTX container format for image textures. This benchmark times how long it takes to convert to KTX 2.0 format with various settings using a reference PNG sample input. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterKTX-Software toktx 4.0Settings: UASTC 3 + Zstd Compression 19Ryzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X3691215SE +/- 0.013, N = 5SE +/- 0.014, N = 5SE +/- 0.012, N = 5SE +/- 0.005, N = 59.69810.0378.7478.405

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 20220729Target: CPU - Model: regnety_400mRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X3691215SE +/- 0.12, N = 3SE +/- 0.02, N = 3SE +/- 0.02, N = 3SE +/- 0.09, N = 710.0511.0611.9611.48MIN: 9.63 / MAX: 43.59MIN: 10.51 / MAX: 18MIN: 11.54 / MAX: 15.93MIN: 10.72 / MAX: 48.41. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

GPAW

GPAW is a density-functional theory (DFT) Python code based on the projector-augmented wave (PAW) method and the atomic simulation environment (ASE). Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterGPAW 22.1Input: Carbon NanotubeRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X306090120150SE +/- 0.21, N = 3SE +/- 0.15, N = 3SE +/- 0.16, N = 3SE +/- 0.12, N = 3150.87143.15126.90138.011. (CC) gcc options: -shared -fwrapv -O2 -lxc -lblas -lmpi

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.

OpenBenchmarking.orgNs Per Day, More Is BetterGROMACS 2023Implementation: MPI CPU - Input: water_GMX50_bareRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X0.60641.21281.81922.42563.032SE +/- 0.004, N = 3SE +/- 0.002, N = 3SE +/- 0.002, N = 3SE +/- 0.004, N = 32.2702.2782.6952.6071. (CXX) g++ options: -O3

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries too. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12-rc0Device: CPU - Batch Size: 32 - Model: AlexNetRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X60120180240300SE +/- 0.05, N = 4SE +/- 0.10, N = 3SE +/- 0.06, N = 4SE +/- 0.14, N = 4232.30223.03258.77264.33

Xmrig

Xmrig is an open-source cross-platform CPU/GPU miner for RandomX, KawPow, CryptoNight and AstroBWT. This test profile is setup to measure the Xmlrig CPU mining performance. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgH/s, More Is BetterXmrig 6.18.1Variant: Monero - Hash Count: 1MRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X3K6K9K12K15KSE +/- 111.27, N = 3SE +/- 76.91, N = 3SE +/- 69.71, N = 3SE +/- 39.19, N = 313863.013564.715627.413188.91. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries too. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12-rc0Device: CPU - Batch Size: 256 - Model: GoogLeNetRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X306090120150SE +/- 0.02, N = 3SE +/- 0.04, N = 3SE +/- 0.03, N = 3SE +/- 0.03, N = 3123.87118.96137.77140.76

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12-rc0Device: CPU - Batch Size: 32 - Model: GoogLeNetRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X306090120150SE +/- 0.13, N = 3SE +/- 0.03, N = 3SE +/- 0.15, N = 3SE +/- 0.17, N = 3127.67126.27149.39147.08

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 20220729Target: CPU - Model: blazefaceRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X0.36680.73361.10041.46721.834SE +/- 0.01, N = 3SE +/- 0.02, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 71.381.491.631.54MIN: 1.31 / MAX: 7.52MIN: 1.4 / MAX: 8.23MIN: 1.57 / MAX: 4.47MIN: 1.46 / MAX: 8.061. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

ONNX Runtime

ONNX Runtime is developed by Microsoft and partners as a open-source, cross-platform, high performance machine learning inferencing and training accelerator. This test profile runs the ONNX Runtime with various models available from the ONNX Model Zoo. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: CaffeNet 12-int8 - Device: CPU - Executor: ParallelRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X2004006008001000SE +/- 9.08, N = 5SE +/- 11.49, N = 3SE +/- 7.64, N = 3SE +/- 6.96, N = 3830.07802.98947.64922.341. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: CaffeNet 12-int8 - Device: CPU - Executor: ParallelRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X0.28010.56020.84031.12041.4005SE +/- 0.01294, N = 5SE +/- 0.01782, N = 3SE +/- 0.00846, N = 3SE +/- 0.00816, N = 31.204271.244811.054361.083331. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries too. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12-rc0Device: CPU - Batch Size: 16 - Model: GoogLeNetRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X306090120150SE +/- 0.09, N = 4SE +/- 0.02, N = 4SE +/- 0.07, N = 4SE +/- 0.14, N = 4128.74124.65147.01146.99

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12-rc0Device: CPU - Batch Size: 64 - Model: GoogLeNetRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X306090120150SE +/- 0.06, N = 3SE +/- 0.03, N = 3SE +/- 0.14, N = 3SE +/- 0.10, N = 3125.62123.26145.29143.88

Xcompact3d Incompact3d

Xcompact3d 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.orgSeconds, Fewer Is BetterXcompact3d Incompact3d 2021-03-11Input: input.i3d 129 Cells Per DirectionRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X48121620SE +/- 0.05, N = 4SE +/- 0.05, N = 4SE +/- 0.02, N = 4SE +/- 0.04, N = 414.6112.6912.5414.631. (F9X) gfortran options: -cpp -O2 -funroll-loops -floop-optimize -fcray-pointer -fbacktrace -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -levent_core -levent_pthreads -lm -lz

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 20220729Target: CPU - Model: alexnetRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X1.12052.2413.36154.4825.6025SE +/- 0.06, N = 3SE +/- 0.05, N = 3SE +/- 0.03, N = 3SE +/- 0.08, N = 74.984.604.284.86MIN: 4.73 / MAX: 10.59MIN: 4.43 / MAX: 11.35MIN: 4.13 / MAX: 10.29MIN: 4.63 / MAX: 9.891. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

ClickHouse

ClickHouse is an open-source, high performance OLAP data management system. This test profile uses ClickHouse's standard benchmark recommendations per https://clickhouse.com/docs/en/operations/performance-test/ / https://github.com/ClickHouse/ClickBench/tree/main/clickhouse with the 100 million rows web analytics dataset. The reported value is the query processing time using the geometric mean of all separate queries performed as an aggregate. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgQueries Per Minute, Geo Mean, More Is BetterClickHouse 22.12.3.5100M Rows Hits Dataset, Third RunRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X70140210280350SE +/- 3.74, N = 3SE +/- 1.13, N = 3SE +/- 3.76, N = 3SE +/- 0.25, N = 3290.14308.81321.76276.94MIN: 16.06 / MAX: 12000MIN: 14.79 / MAX: 12000MIN: 15.82 / MAX: 10000MIN: 15.4 / MAX: 10000

Xcompact3d Incompact3d

Xcompact3d 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.orgSeconds, Fewer Is BetterXcompact3d Incompact3d 2021-03-11Input: input.i3d 193 Cells Per DirectionRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X1530456075SE +/- 0.82, N = 3SE +/- 0.70, N = 4SE +/- 0.66, N = 4SE +/- 0.31, N = 368.2261.9658.7766.211. (F9X) gfortran options: -cpp -O2 -funroll-loops -floop-optimize -fcray-pointer -fbacktrace -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -levent_core -levent_pthreads -lm -lz

OpenFOAM

OpenFOAM is the leading free, open-source software for computational fluid dynamics (CFD). This test profile currently uses the drivaerFastback test case for analyzing automotive aerodynamics or alternatively the older motorBike input. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterOpenFOAM 10Input: drivaerFastback, Medium Mesh Size - Execution TimeRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X50010001500200025002161.561948.061863.952126.101. (CXX) g++ options: -std=c++14 -m64 -O3 -ftemplate-depth-100 -fPIC -fuse-ld=bfd -Xlinker --add-needed --no-as-needed -lfoamToVTK -ldynamicMesh -llagrangian -lgenericPatchFields -lfileFormats -lOpenFOAM -ldl -lm

ONNX Runtime

ONNX Runtime is developed by Microsoft and partners as a open-source, cross-platform, high performance machine learning inferencing and training accelerator. This test profile runs the ONNX Runtime with various models available from the ONNX Model Zoo. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: GPT-2 - Device: CPU - Executor: StandardRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X4080120160200SE +/- 1.80, N = 15SE +/- 1.34, N = 3SE +/- 2.46, N = 3SE +/- 0.39, N = 3172.81195.76185.38169.501. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: GPT-2 - Device: CPU - Executor: StandardRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X1.3272.6543.9815.3086.635SE +/- 0.06489, N = 15SE +/- 0.03513, N = 3SE +/- 0.07238, N = 3SE +/- 0.01353, N = 35.794355.106905.394165.897821. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries too. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12-rc0Device: CPU - Batch Size: 256 - Model: ResNet-50Ryzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X1020304050SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 340.3638.8943.8844.87

ClickHouse

ClickHouse is an open-source, high performance OLAP data management system. This test profile uses ClickHouse's standard benchmark recommendations per https://clickhouse.com/docs/en/operations/performance-test/ / https://github.com/ClickHouse/ClickBench/tree/main/clickhouse with the 100 million rows web analytics dataset. The reported value is the query processing time using the geometric mean of all separate queries performed as an aggregate. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgQueries Per Minute, Geo Mean, More Is BetterClickHouse 22.12.3.5100M Rows Hits Dataset, Second RunRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X70140210280350SE +/- 0.26, N = 3SE +/- 0.93, N = 3SE +/- 2.16, N = 3SE +/- 3.10, N = 3285.41303.48316.84275.45MIN: 16.08 / MAX: 12000MIN: 14.85 / MAX: 10000MIN: 16.12 / MAX: 10000MIN: 16.28 / MAX: 12000

OpenFOAM

OpenFOAM is the leading free, open-source software for computational fluid dynamics (CFD). This test profile currently uses the drivaerFastback test case for analyzing automotive aerodynamics or alternatively the older motorBike input. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterOpenFOAM 10Input: drivaerFastback, Small Mesh Size - Mesh TimeRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X61218243025.0226.2123.9122.791. (CXX) g++ options: -std=c++14 -m64 -O3 -ftemplate-depth-100 -fPIC -fuse-ld=bfd -Xlinker --add-needed --no-as-needed -lfoamToVTK -ldynamicMesh -llagrangian -lgenericPatchFields -lfileFormats -lOpenFOAM -ldl -lm

ASKAP

ASKAP is a set of benchmarks from the Australian SKA Pathfinder. The principal ASKAP benchmarks are the Hogbom Clean Benchmark (tHogbomClean) and Convolutional Resamping Benchmark (tConvolve) as well as some previous ASKAP benchmarks being included as well for OpenCL and CUDA execution of tConvolve. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMillion Grid Points Per Second, More Is BetterASKAP 1.0Test: tConvolve MT - GriddingRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X5001000150020002500SE +/- 11.79, N = 3SE +/- 11.10, N = 3SE +/- 8.06, N = 3SE +/- 8.23, N = 32002.692100.992293.312173.951. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp

srsRAN

srsRAN is an open-source LTE/5G software radio suite created by Software Radio Systems (SRS). The srsRAN radio suite was formerly known as srsLTE and can be used for building your own software-defined radio (SDR) 4G/5G mobile network. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgeNb Mb/s, More Is BettersrsRAN 22.04.1Test: 4G PHY_DL_Test 100 PRB SISO 256-QAMRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X140280420560700SE +/- 2.31, N = 4SE +/- 3.59, N = 15SE +/- 3.65, N = 4SE +/- 2.30, N = 4669.4585.9660.1665.81. (CXX) g++ options: -std=c++14 -fno-strict-aliasing -march=native -mfpmath=sse -mavx2 -fvisibility=hidden -O3 -fno-trapping-math -fno-math-errno -mavx512f -mavx512cd -mavx512bw -mavx512dq -ldl -lpthread -lm

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries too. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12-rc0Device: CPU - Batch Size: 64 - Model: ResNet-50Ryzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X1020304050SE +/- 0.01, N = 3SE +/- 0.02, N = 3SE +/- 0.04, N = 3SE +/- 0.02, N = 340.2039.0644.2044.58

Zstd Compression

This test measures the time needed to compress/decompress a sample file (silesia.tar) using Zstd (Zstandard) compression with options for different compression levels / settings. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.5.4Compression Level: 3 - Compression SpeedRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X9001800270036004500SE +/- 10.25, N = 3SE +/- 10.85, N = 3SE +/- 2.07, N = 3SE +/- 22.63, N = 34014.33710.73959.64227.61. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries too. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12-rc0Device: CPU - Batch Size: 32 - Model: ResNet-50Ryzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X1020304050SE +/- 0.01, N = 3SE +/- 0.06, N = 3SE +/- 0.06, N = 3SE +/- 0.03, N = 340.0039.0144.2744.39

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12-rc0Device: CPU - Batch Size: 16 - Model: ResNet-50Ryzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X1020304050SE +/- 0.00, N = 3SE +/- 0.04, N = 3SE +/- 0.08, N = 3SE +/- 0.02, N = 338.9038.1143.1943.08

ONNX Runtime

ONNX Runtime is developed by Microsoft and partners as a open-source, cross-platform, high performance machine learning inferencing and training accelerator. This test profile runs the ONNX Runtime with various models available from the ONNX Model Zoo. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: bertsquad-12 - Device: CPU - Executor: StandardRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X510152025SE +/- 0.03, N = 3SE +/- 0.12, N = 3SE +/- 0.19, N = 3SE +/- 0.07, N = 319.7318.8220.1921.281. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: bertsquad-12 - Device: CPU - Executor: StandardRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X1224364860SE +/- 0.07, N = 3SE +/- 0.34, N = 3SE +/- 0.47, N = 3SE +/- 0.16, N = 350.6953.1449.5447.001. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: GPT-2 - Device: CPU - Executor: ParallelRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X4080120160200SE +/- 1.56, N = 3SE +/- 0.56, N = 3SE +/- 0.66, N = 3SE +/- 0.20, N = 3146.34157.29164.53146.501. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: GPT-2 - Device: CPU - Executor: ParallelRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X246810SE +/- 0.07342, N = 3SE +/- 0.02269, N = 3SE +/- 0.02467, N = 3SE +/- 0.00930, N = 36.831776.353626.074386.822611. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenFOAM

OpenFOAM is the leading free, open-source software for computational fluid dynamics (CFD). This test profile currently uses the drivaerFastback test case for analyzing automotive aerodynamics or alternatively the older motorBike input. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterOpenFOAM 10Input: drivaerFastback, Medium Mesh Size - Mesh TimeRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X4080120160200199.34193.36178.11190.941. (CXX) g++ options: -std=c++14 -m64 -O3 -ftemplate-depth-100 -fPIC -fuse-ld=bfd -Xlinker --add-needed --no-as-needed -lfoamToVTK -ldynamicMesh -llagrangian -lgenericPatchFields -lfileFormats -lOpenFOAM -ldl -lm

ClickHouse

ClickHouse is an open-source, high performance OLAP data management system. This test profile uses ClickHouse's standard benchmark recommendations per https://clickhouse.com/docs/en/operations/performance-test/ / https://github.com/ClickHouse/ClickBench/tree/main/clickhouse with the 100 million rows web analytics dataset. The reported value is the query processing time using the geometric mean of all separate queries performed as an aggregate. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgQueries Per Minute, Geo Mean, More Is BetterClickHouse 22.12.3.5100M Rows Hits Dataset, First Run / Cold CacheRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X60120180240300SE +/- 1.44, N = 3SE +/- 1.41, N = 3SE +/- 1.59, N = 3SE +/- 0.81, N = 3258.64269.00279.87250.50MIN: 15.82 / MAX: 10000MIN: 14.44 / MAX: 8571.43MIN: 13.15 / MAX: 7500MIN: 12.61 / MAX: 10000

OpenVINO

This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPURyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X0.15080.30160.45240.60320.754SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 30.600.670.670.61MIN: 0.33 / MAX: 7.83MIN: 0.37 / MAX: 45.37MIN: 0.35 / MAX: 9.57MIN: 0.34 / MAX: 7.641. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

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 20220729Target: CPU - Model: shufflenet-v2Ryzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X0.86851.7372.60553.4744.3425SE +/- 0.03, N = 3SE +/- 0.02, N = 3SE +/- 0.01, N = 3SE +/- 0.02, N = 73.463.733.863.62MIN: 3.36 / MAX: 9.94MIN: 3.55 / MAX: 9.54MIN: 3.71 / MAX: 9.56MIN: 3.44 / MAX: 10.541. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

ASKAP

ASKAP is a set of benchmarks from the Australian SKA Pathfinder. The principal ASKAP benchmarks are the Hogbom Clean Benchmark (tHogbomClean) and Convolutional Resamping Benchmark (tConvolve) as well as some previous ASKAP benchmarks being included as well for OpenCL and CUDA execution of tConvolve. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMpix/sec, More Is BetterASKAP 1.0Test: tConvolve MPI - GriddingRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X3K6K9K12K15KSE +/- 116.93, N = 3SE +/- 124.23, N = 3SE +/- 0.00, N = 3SE +/- 111.37, N = 611693.212051.312495.011211.21. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp

OpenVINO

This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Age Gender Recognition Retail 0013 FP16 - Device: CPURyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X0.08780.17560.26340.35120.439SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 30.350.390.390.35MIN: 0.21 / MAX: 8.31MIN: 0.24 / MAX: 61.73MIN: 0.22 / MAX: 8.71MIN: 0.21 / MAX: 7.041. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries too. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12-rc0Device: CPU - Batch Size: 16 - Model: AlexNetRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X4080120160200SE +/- 0.22, N = 4SE +/- 0.07, N = 4SE +/- 0.18, N = 5SE +/- 0.11, N = 5162.66158.97176.22176.72

OpenVINO

This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Weld Porosity Detection FP16-INT8 - Device: CPURyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X246810SE +/- 0.03, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 35.516.126.115.53MIN: 2.96 / MAX: 12.69MIN: 3.22 / MAX: 17.67MIN: 3.19 / MAX: 13.31MIN: 2.99 / MAX: 13.651. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Machine Translation EN To DE FP16 - Device: CPURyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X1326395265SE +/- 0.10, N = 3SE +/- 0.23, N = 3SE +/- 0.23, N = 3SE +/- 0.22, N = 353.5455.6558.9957.85MIN: 31.21 / MAX: 70.2MIN: 26.86 / MAX: 87.31MIN: 30.71 / MAX: 70.41MIN: 27.45 / MAX: 68.11. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Vehicle Detection FP16-INT8 - Device: CPURyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X1.07332.14663.21994.29325.3665SE +/- 0.02, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 34.414.774.684.34MIN: 2.6 / MAX: 12.74MIN: 2.89 / MAX: 23.9MIN: 2.79 / MAX: 16.02MIN: 2.71 / MAX: 12.091. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

ASKAP

ASKAP is a set of benchmarks from the Australian SKA Pathfinder. The principal ASKAP benchmarks are the Hogbom Clean Benchmark (tHogbomClean) and Convolutional Resamping Benchmark (tConvolve) as well as some previous ASKAP benchmarks being included as well for OpenCL and CUDA execution of tConvolve. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMpix/sec, More Is BetterASKAP 1.0Test: tConvolve MPI - DegriddingRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X2K4K6K8K10KSE +/- 0.00, N = 3SE +/- 84.09, N = 3SE +/- 74.40, N = 3SE +/- 106.21, N = 610092.109923.9310858.8010788.801. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp

OpenVINO

This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Weld Porosity Detection FP16 - Device: CPURyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X246810SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 35.505.996.015.54MIN: 2.79 / MAX: 16.27MIN: 3.12 / MAX: 18.55MIN: 3.17 / MAX: 13.52MIN: 2.85 / MAX: 12.561. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Face Detection FP16-INT8 - Device: CPURyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X70140210280350SE +/- 0.86, N = 3SE +/- 0.08, N = 3SE +/- 1.12, N = 3SE +/- 0.86, N = 3279.48304.86304.02281.59MIN: 148.87 / MAX: 292.1MIN: 160.61 / MAX: 318.49MIN: 154.56 / MAX: 315.21MIN: 146.44 / MAX: 293.541. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

ASKAP

ASKAP is a set of benchmarks from the Australian SKA Pathfinder. The principal ASKAP benchmarks are the Hogbom Clean Benchmark (tHogbomClean) and Convolutional Resamping Benchmark (tConvolve) as well as some previous ASKAP benchmarks being included as well for OpenCL and CUDA execution of tConvolve. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMillion Grid Points Per Second, More Is BetterASKAP 1.0Test: tConvolve MT - DegriddingRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X6001200180024003000SE +/- 39.07, N = 3SE +/- 24.29, N = 3SE +/- 7.84, N = 3SE +/- 6.59, N = 32755.492906.782995.192833.491. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp

OpenVINO

This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Person Detection FP16 - Device: CPURyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X2004006008001000SE +/- 7.16, N = 3SE +/- 3.14, N = 3SE +/- 2.36, N = 3SE +/- 1.82, N = 31000.881065.821085.081040.72MIN: 603.97 / MAX: 1146.51MIN: 618.47 / MAX: 1180.09MIN: 997.16 / MAX: 1282.69MIN: 623.58 / MAX: 1238.551. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

Zstd Compression

This test measures the time needed to compress/decompress a sample file (silesia.tar) using Zstd (Zstandard) compression with options for different compression levels / settings. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.5.4Compression Level: 19 - Compression SpeedRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X612182430SE +/- 0.03, N = 3SE +/- 0.31, N = 15SE +/- 0.37, N = 15SE +/- 0.09, N = 323.425.225.223.31. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

OpenVINO

This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Person Detection FP32 - Device: CPURyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X2004006008001000SE +/- 3.50, N = 3SE +/- 2.18, N = 3SE +/- 6.09, N = 3SE +/- 8.14, N = 31012.481064.331094.431057.42MIN: 584.86 / MAX: 1150.29MIN: 940.91 / MAX: 1184.64MIN: 672.11 / MAX: 1267.85MIN: 582.42 / MAX: 1238.031. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Face Detection FP16 - Device: CPURyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X130260390520650SE +/- 0.69, N = 3SE +/- 0.29, N = 3SE +/- 0.95, N = 3SE +/- 0.39, N = 3546.20589.39589.45554.42MIN: 275.75 / MAX: 574.42MIN: 309.39 / MAX: 685.91MIN: 407.34 / MAX: 615.98MIN: 280.02 / MAX: 579.261. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

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 20220729Target: CPU-v2-v2 - Model: mobilenet-v2Ryzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X0.8461.6922.5383.3844.23SE +/- 0.04, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.02, N = 73.503.573.763.62MIN: 3.31 / MAX: 10.67MIN: 3.49 / MAX: 7.6MIN: 3.66 / MAX: 7.74MIN: 3.49 / MAX: 11.581. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU - Model: mnasnetRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X0.7651.532.2953.063.825SE +/- 0.08, N = 3SE +/- 0.02, N = 3SE +/- 0.01, N = 3SE +/- 0.02, N = 73.173.253.403.23MIN: 3 / MAX: 45.73MIN: 3.13 / MAX: 9.66MIN: 3.28 / MAX: 7.36MIN: 3.12 / MAX: 10.321. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU - Model: mobilenetRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X3691215SE +/- 0.10, N = 3SE +/- 0.06, N = 3SE +/- 0.02, N = 3SE +/- 0.08, N = 78.849.338.878.70MIN: 8.3 / MAX: 71.01MIN: 9.06 / MAX: 16.18MIN: 8.73 / MAX: 12.08MIN: 8.36 / MAX: 15.031. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

ONNX Runtime

ONNX Runtime is developed by Microsoft and partners as a open-source, cross-platform, high performance machine learning inferencing and training accelerator. This test profile runs the ONNX Runtime with various models available from the ONNX Model Zoo. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: Faster R-CNN R-50-FPN-int8 - Device: CPU - Executor: ParallelRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X1224364860SE +/- 0.05, N = 3SE +/- 0.10, N = 3SE +/- 0.55, N = 3SE +/- 0.42, N = 349.5048.2649.6651.741. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: Faster R-CNN R-50-FPN-int8 - Device: CPU - Executor: ParallelRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X510152025SE +/- 0.02, N = 3SE +/- 0.04, N = 3SE +/- 0.23, N = 3SE +/- 0.16, N = 320.2020.7220.1419.331. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

Zstd Compression

This test measures the time needed to compress/decompress a sample file (silesia.tar) using Zstd (Zstandard) compression with options for different compression levels / settings. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.5.4Compression Level: 3, Long Mode - Compression SpeedRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X30060090012001500SE +/- 1.62, N = 3SE +/- 7.40, N = 3SE +/- 1.80, N = 3SE +/- 3.37, N = 31393.71319.61338.31413.91. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

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 20220729Target: CPU - Model: efficientnet-b0Ryzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X1.0352.073.1054.145.175SE +/- 0.09, N = 3SE +/- 0.08, N = 3SE +/- 0.01, N = 3SE +/- 0.02, N = 74.314.574.604.40MIN: 4.09 / MAX: 69.92MIN: 4.29 / MAX: 38.08MIN: 4.49 / MAX: 8.48MIN: 4.27 / MAX: 12.061. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU - Model: vgg16Ryzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X612182430SE +/- 0.35, N = 3SE +/- 0.43, N = 3SE +/- 0.45, N = 3SE +/- 0.40, N = 725.7425.9424.3424.61MIN: 24.62 / MAX: 110.19MIN: 24.38 / MAX: 80.6MIN: 23.49 / MAX: 49.31MIN: 23.44 / MAX: 36.141. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenVINO

This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Person Vehicle Bike Detection FP16 - Device: CPURyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X1.1342.2683.4024.5365.67SE +/- 0.04, N = 3SE +/- 0.03, N = 3SE +/- 0.01, N = 3SE +/- 0.03, N = 34.745.044.824.78MIN: 3.18 / MAX: 12.15MIN: 3.53 / MAX: 13.4MIN: 3.33 / MAX: 13.06MIN: 3.45 / MAX: 12.821. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared

LULESH

LULESH is the Livermore Unstructured Lagrangian Explicit Shock Hydrodynamics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgz/s, More Is BetterLULESH 2.0.3Ryzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X2K4K6K8K10KSE +/- 18.50, N = 6SE +/- 19.85, N = 7SE +/- 15.81, N = 7SE +/- 22.43, N = 68484.578953.058987.948479.881. (CXX) g++ options: -O3 -fopenmp -lm -lmpi_cxx -lmpi

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 20220729Target: CPU-v3-v3 - Model: mobilenet-v3Ryzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X0.74481.48962.23442.97923.724SE +/- 0.07, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 73.133.143.313.15MIN: 2.81 / MAX: 65.6MIN: 3.07 / MAX: 7.15MIN: 3.21 / MAX: 7.38MIN: 3.05 / MAX: 9.871. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU - Model: resnet50Ryzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X3691215SE +/- 0.19, N = 3SE +/- 0.18, N = 3SE +/- 0.27, N = 3SE +/- 0.12, N = 712.3812.4711.8612.17MIN: 11.55 / MAX: 20.74MIN: 11.8 / MAX: 20.06MIN: 11.44 / MAX: 44.27MIN: 11.51 / MAX: 20.611. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU - Model: squeezenet_ssdRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X3691215SE +/- 0.14, N = 3SE +/- 0.26, N = 3SE +/- 0.06, N = 3SE +/- 0.08, N = 711.7811.5711.7212.14MIN: 11.23 / MAX: 63.22MIN: 10.88 / MAX: 89.31MIN: 11.48 / MAX: 18.6MIN: 11.7 / MAX: 20.561. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

srsRAN

srsRAN is an open-source LTE/5G software radio suite created by Software Radio Systems (SRS). The srsRAN radio suite was formerly known as srsLTE and can be used for building your own software-defined radio (SDR) 4G/5G mobile network. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSamples / Second, More Is BettersrsRAN 22.04.1Test: OFDM_TestRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X50M100M150M200M250MSE +/- 1266227.99, N = 3SE +/- 1519137.18, N = 3SE +/- 1072898.46, N = 3SE +/- 1178982.61, N = 32370000002373333332459666672366000001. (CXX) g++ options: -std=c++14 -fno-strict-aliasing -march=native -mfpmath=sse -mavx2 -fvisibility=hidden -O3 -fno-trapping-math -fno-math-errno -mavx512f -mavx512cd -mavx512bw -mavx512dq -ldl -lpthread -lm

OpenBenchmarking.orgeNb Mb/s, More Is BettersrsRAN 22.04.1Test: 4G PHY_DL_Test 100 PRB MIMO 64-QAMRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X140280420560700SE +/- 1.85, N = 3SE +/- 4.54, N = 11SE +/- 1.67, N = 3SE +/- 0.43, N = 3627.1614.9638.3617.81. (CXX) g++ options: -std=c++14 -fno-strict-aliasing -march=native -mfpmath=sse -mavx2 -fvisibility=hidden -O3 -fno-trapping-math -fno-math-errno -mavx512f -mavx512cd -mavx512bw -mavx512dq -ldl -lpthread -lm

KTX-Software toktx

This is a benchmark of The Khronos Group's KTX-Software library and tools. KTX-Software provides "toktx" for converting/creating in the KTX container format for image textures. This benchmark times how long it takes to convert to KTX 2.0 format with various settings using a reference PNG sample input. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterKTX-Software toktx 4.0Settings: Zstd Compression 19Ryzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X3691215SE +/- 0.07, N = 4SE +/- 0.03, N = 4SE +/- 0.06, N = 5SE +/- 0.05, N = 511.6411.5311.4611.22

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 20220729Target: CPU - Model: yolov4-tinyRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X48121620SE +/- 0.14, N = 3SE +/- 0.47, N = 3SE +/- 0.06, N = 3SE +/- 0.06, N = 714.2414.7314.2814.21MIN: 13.88 / MAX: 55.6MIN: 13.78 / MAX: 20.88MIN: 13.99 / MAX: 17.85MIN: 13.76 / MAX: 41.481. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

Zstd Compression

This test measures the time needed to compress/decompress a sample file (silesia.tar) using Zstd (Zstandard) compression with options for different compression levels / settings. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.5.4Compression Level: 19 - Decompression SpeedRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X5001000150020002500SE +/- 31.89, N = 3SE +/- 14.47, N = 15SE +/- 25.89, N = 15SE +/- 4.22, N = 32101.82082.12030.52104.41. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

srsRAN

srsRAN is an open-source LTE/5G software radio suite created by Software Radio Systems (SRS). The srsRAN radio suite was formerly known as srsLTE and can be used for building your own software-defined radio (SDR) 4G/5G mobile network. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgUE Mb/s, More Is BettersrsRAN 22.04.1Test: 4G PHY_DL_Test 100 PRB MIMO 64-QAMRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X50100150200250SE +/- 0.87, N = 3SE +/- 2.56, N = 11SE +/- 0.33, N = 3SE +/- 0.72, N = 3240.6235.3243.8236.91. (CXX) g++ options: -std=c++14 -fno-strict-aliasing -march=native -mfpmath=sse -mavx2 -fvisibility=hidden -O3 -fno-trapping-math -fno-math-errno -mavx512f -mavx512cd -mavx512bw -mavx512dq -ldl -lpthread -lm

LeelaChessZero

LeelaChessZero (lc0 / lczero) is a chess engine automated vian neural networks. This test profile can be used for OpenCL, CUDA + cuDNN, and BLAS (CPU-based) benchmarking. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgNodes Per Second, More Is BetterLeelaChessZero 0.28Backend: BLASRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X400800120016002000SE +/- 14.80, N = 3SE +/- 23.20, N = 4SE +/- 13.05, N = 3SE +/- 14.71, N = 318791882194519151. (CXX) g++ options: -flto -pthread

srsRAN

srsRAN is an open-source LTE/5G software radio suite created by Software Radio Systems (SRS). The srsRAN radio suite was formerly known as srsLTE and can be used for building your own software-defined radio (SDR) 4G/5G mobile network. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgeNb Mb/s, More Is BettersrsRAN 22.04.1Test: 4G PHY_DL_Test 100 PRB MIMO 256-QAMRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X150300450600750SE +/- 1.63, N = 3SE +/- 7.85, N = 3SE +/- 1.62, N = 3SE +/- 0.74, N = 3677.8665.2686.0667.01. (CXX) g++ options: -std=c++14 -fno-strict-aliasing -march=native -mfpmath=sse -mavx2 -fvisibility=hidden -O3 -fno-trapping-math -fno-math-errno -mavx512f -mavx512cd -mavx512bw -mavx512dq -ldl -lpthread -lm

OpenBenchmarking.orgUE Mb/s, More Is BettersrsRAN 22.04.1Test: 4G PHY_DL_Test 100 PRB MIMO 256-QAMRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X60120180240300SE +/- 1.39, N = 3SE +/- 2.06, N = 3SE +/- 0.67, N = 3SE +/- 0.25, N = 3254.9250.3256.8250.71. (CXX) g++ options: -std=c++14 -fno-strict-aliasing -march=native -mfpmath=sse -mavx2 -fvisibility=hidden -O3 -fno-trapping-math -fno-math-errno -mavx512f -mavx512cd -mavx512bw -mavx512dq -ldl -lpthread -lm

Zstd Compression

This test measures the time needed to compress/decompress a sample file (silesia.tar) using Zstd (Zstandard) compression with options for different compression levels / settings. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.5.4Compression Level: 8, Long Mode - Decompression SpeedRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X5001000150020002500SE +/- 0.74, N = 3SE +/- 4.07, N = 3SE +/- 12.98, N = 3SE +/- 0.47, N = 32410.42365.32422.12390.41. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

PyHPC Benchmarks

PyHPC-Benchmarks is a suite of Python high performance computing benchmarks for execution on CPUs and GPUs using various popular Python HPC libraries. The PyHPC CPU-based benchmarks focus on sequential CPU performance. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterPyHPC Benchmarks 3.0Device: CPU - Backend: Numpy - Project Size: 4194304 - Benchmark: Equation of StateRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X0.16450.3290.49350.6580.8225SE +/- 0.001, N = 3SE +/- 0.011, N = 12SE +/- 0.000, N = 3SE +/- 0.001, N = 30.7140.7260.7310.727

OpenBenchmarking.orgSeconds, Fewer Is BetterPyHPC Benchmarks 3.0Device: CPU - Backend: Numpy - Project Size: 4194304 - Benchmark: Isoneutral MixingRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X0.24320.48640.72960.97281.216SE +/- 0.001, N = 3SE +/- 0.002, N = 3SE +/- 0.008, N = 3SE +/- 0.001, N = 31.0571.0811.0741.057

srsRAN

srsRAN is an open-source LTE/5G software radio suite created by Software Radio Systems (SRS). The srsRAN radio suite was formerly known as srsLTE and can be used for building your own software-defined radio (SDR) 4G/5G mobile network. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgeNb Mb/s, More Is BettersrsRAN 22.04.1Test: 4G PHY_DL_Test 100 PRB SISO 64-QAMRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X130260390520650SE +/- 1.26, N = 5SE +/- 1.40, N = 5SE +/- 4.56, N = 5SE +/- 6.18, N = 5622.7619.7616.3609.01. (CXX) g++ options: -std=c++14 -fno-strict-aliasing -march=native -mfpmath=sse -mavx2 -fvisibility=hidden -O3 -fno-trapping-math -fno-math-errno -mavx512f -mavx512cd -mavx512bw -mavx512dq -ldl -lpthread -lm

Zstd Compression

This test measures the time needed to compress/decompress a sample file (silesia.tar) using Zstd (Zstandard) compression with options for different compression levels / settings. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.5.4Compression Level: 3 - Decompression SpeedRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X5001000150020002500SE +/- 5.24, N = 3SE +/- 7.53, N = 3SE +/- 6.56, N = 3SE +/- 3.32, N = 32184.02162.42203.62170.11. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

srsRAN

srsRAN is an open-source LTE/5G software radio suite created by Software Radio Systems (SRS). The srsRAN radio suite was formerly known as srsLTE and can be used for building your own software-defined radio (SDR) 4G/5G mobile network. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgUE Mb/s, More Is BettersrsRAN 22.04.1Test: 4G PHY_DL_Test 100 PRB SISO 64-QAMRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X60120180240300SE +/- 0.34, N = 5SE +/- 0.45, N = 5SE +/- 0.83, N = 5SE +/- 0.90, N = 5251.1250.6252.0247.41. (CXX) g++ options: -std=c++14 -fno-strict-aliasing -march=native -mfpmath=sse -mavx2 -fvisibility=hidden -O3 -fno-trapping-math -fno-math-errno -mavx512f -mavx512cd -mavx512bw -mavx512dq -ldl -lpthread -lm

Zstd Compression

This test measures the time needed to compress/decompress a sample file (silesia.tar) using Zstd (Zstandard) compression with options for different compression levels / settings. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.5.4Compression Level: 8 - Decompression SpeedRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X5001000150020002500SE +/- 6.76, N = 3SE +/- 4.93, N = 3SE +/- 15.85, N = 15SE +/- 7.71, N = 32393.02352.92391.62379.11. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.5.4Compression Level: 3, Long Mode - Decompression SpeedRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X5001000150020002500SE +/- 3.63, N = 3SE +/- 5.96, N = 3SE +/- 3.72, N = 3SE +/- 4.39, N = 32249.42217.42254.02223.81. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

LeelaChessZero

LeelaChessZero (lc0 / lczero) is a chess engine automated vian neural networks. This test profile can be used for OpenCL, CUDA + cuDNN, and BLAS (CPU-based) benchmarking. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgNodes Per Second, More Is BetterLeelaChessZero 0.28Backend: EigenRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X400800120016002000SE +/- 19.78, N = 3SE +/- 19.01, N = 4SE +/- 13.42, N = 3SE +/- 4.00, N = 317721767178717731. (CXX) g++ options: -flto -pthread

srsRAN

srsRAN is an open-source LTE/5G software radio suite created by Software Radio Systems (SRS). The srsRAN radio suite was formerly known as srsLTE and can be used for building your own software-defined radio (SDR) 4G/5G mobile network. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgeNb Mb/s, More Is BettersrsRAN 22.04.1Test: 5G PHY_DL_NR Test 52 PRB SISO 64-QAMRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X50100150200250SE +/- 0.81, N = 5SE +/- 1.58, N = 5SE +/- 1.38, N = 5SE +/- 0.56, N = 5211.6209.9211.5209.51. (CXX) g++ options: -std=c++14 -fno-strict-aliasing -march=native -mfpmath=sse -mavx2 -fvisibility=hidden -O3 -fno-trapping-math -fno-math-errno -mavx512f -mavx512cd -mavx512bw -mavx512dq -ldl -lpthread -lm

Zstd Compression

This test measures the time needed to compress/decompress a sample file (silesia.tar) using Zstd (Zstandard) compression with options for different compression levels / settings. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.5.4Compression Level: 12 - Decompression SpeedRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X5001000150020002500SE +/- 16.52, N = 3SE +/- 2.91, N = 3SE +/- 9.67, N = 3SE +/- 6.83, N = 32452.02453.82452.82439.91. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

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 20220729Target: CPU - Model: FastestDetRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X1.0532.1063.1594.2125.265SE +/- 0.19, N = 3SE +/- 0.07, N = 3SE +/- 0.02, N = 3SE +/- 0.03, N = 74.224.364.684.46MIN: 3.94 / MAX: 4.84MIN: 4.18 / MAX: 4.8MIN: 4.55 / MAX: 6.08MIN: 4.27 / MAX: 5.741. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU - Model: resnet18Ryzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X246810SE +/- 0.25, N = 3SE +/- 0.31, N = 3SE +/- 0.01, N = 3SE +/- 0.10, N = 77.777.086.607.46MIN: 7.02 / MAX: 14.55MIN: 6.25 / MAX: 13.9MIN: 6.42 / MAX: 12.76MIN: 7.15 / MAX: 14.271. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20220729Target: CPU - Model: googlenetRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X3691215SE +/- 0.23, N = 3SE +/- 0.35, N = 3SE +/- 0.00, N = 3SE +/- 0.15, N = 78.829.038.528.58MIN: 7.98 / MAX: 72.14MIN: 7.88 / MAX: 43.33MIN: 8.28 / MAX: 14.26MIN: 8.16 / MAX: 15.241. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

PyHPC Benchmarks

PyHPC-Benchmarks is a suite of Python high performance computing benchmarks for execution on CPUs and GPUs using various popular Python HPC libraries. The PyHPC CPU-based benchmarks focus on sequential CPU performance. Learn more via the OpenBenchmarking.org test page.

Device: CPU - Backend: TensorFlow - Project Size: 4194304 - Benchmark: Isoneutral Mixing

Ryzen 9 7900X3D: The test run did not produce a result.

Ryzen 9 7900X: The test run did not produce a result.

Ryzen 9 79500X3D: The test run did not produce a result.

Ryzen 9 7950X: The test run did not produce a result.

Device: CPU - Backend: TensorFlow - Project Size: 4194304 - Benchmark: Equation of State

Ryzen 9 7900X3D: The test run did not produce a result.

Ryzen 9 7900X: The test run did not produce a result.

Ryzen 9 79500X3D: The test run did not produce a result.

Ryzen 9 7950X: The test run did not produce a result.

Device: CPU - Backend: PyTorch - Project Size: 4194304 - Benchmark: Isoneutral Mixing

Ryzen 9 7900X3D: The test run did not produce a result.

Ryzen 9 7900X: The test run did not produce a result.

Ryzen 9 79500X3D: The test run did not produce a result.

Ryzen 9 7950X: The test run did not produce a result.

Device: CPU - Backend: PyTorch - Project Size: 4194304 - Benchmark: Equation of State

Ryzen 9 7900X3D: The test run did not produce a result.

Ryzen 9 7900X: The test run did not produce a result.

Ryzen 9 79500X3D: The test run did not produce a result.

Ryzen 9 7950X: The test run did not produce a result.

Device: CPU - Backend: Numba - Project Size: 4194304 - Benchmark: Isoneutral Mixing

Ryzen 9 7900X3D: The test run did not produce a result.

Ryzen 9 7900X: The test run did not produce a result.

Ryzen 9 79500X3D: The test run did not produce a result.

Ryzen 9 7950X: The test run did not produce a result.

Device: CPU - Backend: Numba - Project Size: 4194304 - Benchmark: Equation of State

Ryzen 9 7900X3D: The test run did not produce a result.

Ryzen 9 7900X: The test run did not produce a result.

Ryzen 9 79500X3D: The test run did not produce a result.

Ryzen 9 7950X: The test run did not produce a result.

Device: CPU - Backend: JAX - Project Size: 4194304 - Benchmark: Isoneutral Mixing

Ryzen 9 7900X3D: The test run did not produce a result.

Ryzen 9 7900X: The test run did not produce a result.

Ryzen 9 79500X3D: The test run did not produce a result.

Ryzen 9 7950X: The test run did not produce a result.

Device: CPU - Backend: JAX - Project Size: 4194304 - Benchmark: Equation of State

Ryzen 9 7900X3D: The test run did not produce a result.

Ryzen 9 7900X: The test run did not produce a result.

Ryzen 9 79500X3D: The test run did not produce a result.

Ryzen 9 7950X: The test run did not produce a result.

Device: CPU - Backend: Aesara - Project Size: 4194304 - Benchmark: Isoneutral Mixing

Ryzen 9 7900X3D: The test run did not produce a result.

Ryzen 9 7900X: The test run did not produce a result.

Ryzen 9 79500X3D: The test run did not produce a result.

Ryzen 9 7950X: The test run did not produce a result.

Device: CPU - Backend: Aesara - Project Size: 4194304 - Benchmark: Equation of State

Ryzen 9 7900X3D: The test run did not produce a result.

Ryzen 9 7900X: The test run did not produce a result.

Ryzen 9 79500X3D: The test run did not produce a result.

Ryzen 9 7950X: The test run did not produce a result.

srsRAN

srsRAN is an open-source LTE/5G software radio suite created by Software Radio Systems (SRS). The srsRAN radio suite was formerly known as srsLTE and can be used for building your own software-defined radio (SDR) 4G/5G mobile network. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgUE Mb/s, More Is BettersrsRAN 22.04.1Test: 5G PHY_DL_NR Test 52 PRB SISO 64-QAMRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X306090120150SE +/- 0.21, N = 5SE +/- 4.42, N = 5SE +/- 0.93, N = 5SE +/- 0.23, N = 5145.3136.8144.2142.91. (CXX) g++ options: -std=c++14 -fno-strict-aliasing -march=native -mfpmath=sse -mavx2 -fvisibility=hidden -O3 -fno-trapping-math -fno-math-errno -mavx512f -mavx512cd -mavx512bw -mavx512dq -ldl -lpthread -lm

KTX-Software toktx

This is a benchmark of The Khronos Group's KTX-Software library and tools. KTX-Software provides "toktx" for converting/creating in the KTX container format for image textures. This benchmark times how long it takes to convert to KTX 2.0 format with various settings using a reference PNG sample input. Learn more via the OpenBenchmarking.org test page.

Settings: Zstd Compression 9

Ryzen 9 7900X3D: The test run did not produce a result.

Ryzen 9 7900X: The test run did not produce a result.

Ryzen 9 79500X3D: The test run did not produce a result.

Ryzen 9 7950X: The test run did not produce a result.

Open Porous Media Git

This is a test of Open Porous Media, a set of open-source tools concerning simulation of flow and transport of fluids in porous media. This test profile builds OPM and its dependencies from upstream Git. Learn more via the OpenBenchmarking.org test page.

OPM Benchmark: PUNQ-S3 - Threads: 16

Ryzen 9 7900X3D: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16

Ryzen 9 7900X: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16

Ryzen 9 79500X3D: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access

Ryzen 9 7950X: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access

OPM Benchmark: Smeaheia - Threads: 16

Ryzen 9 7900X3D: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16

Ryzen 9 7900X: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16

Ryzen 9 79500X3D: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access

Ryzen 9 7950X: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access

OPM Benchmark: SPE10 Model 2 - Threads: 16

Ryzen 9 7900X3D: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16

Ryzen 9 7900X: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16

Ryzen 9 79500X3D: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access

Ryzen 9 7950X: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access

OPM Benchmark: SPE10 Model 1 - Threads: 16

Ryzen 9 7900X3D: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16

Ryzen 9 7900X: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16

Ryzen 9 79500X3D: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access

Ryzen 9 7950X: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access

OPM Benchmark: Drogon - Threads: 16

Ryzen 9 7900X3D: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16

Ryzen 9 7900X: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16

Ryzen 9 79500X3D: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access

Ryzen 9 7950X: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access

OPM Benchmark: Flow MPI Extra - Threads: 16

Ryzen 9 7900X3D: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16

Ryzen 9 7900X: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16

Ryzen 9 79500X3D: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access

Ryzen 9 7950X: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access

OPM Benchmark: Flow MPI Norne-4C MSW - Threads: 16

Ryzen 9 7900X3D: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16

Ryzen 9 7900X: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16

Ryzen 9 79500X3D: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access

Ryzen 9 7950X: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access

OPM Benchmark: Flow MPI Norne - Threads: 16

Ryzen 9 7900X3D: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16

Ryzen 9 7900X: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16

Ryzen 9 79500X3D: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access

Ryzen 9 7950X: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access

OPM Benchmark: Upscale-Relperm - Threads: 16

Ryzen 9 7900X3D: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16

Ryzen 9 7900X: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16

Ryzen 9 79500X3D: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access

Ryzen 9 7950X: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access

oneDNN

This is a test of the Intel oneDNN as an Intel-optimized library for Deep Neural Networks and making use of its built-in benchdnn functionality. The result is the total perf time reported. Intel oneDNN was formerly known as DNNL (Deep Neural Network Library) and MKL-DNN before being rebranded as part of the Intel oneAPI toolkit. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.0Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPURyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X0.47440.94881.42321.89762.372SE +/- 0.00247, N = 7SE +/- 0.00176, N = 7SE +/- 0.00908, N = 7SE +/- 0.37855, N = 151.812911.381441.086402.10831MIN: 1.74MIN: 1.34MIN: 1.01MIN: 1.631. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread

Zstd Compression

This test measures the time needed to compress/decompress a sample file (silesia.tar) using Zstd (Zstandard) compression with options for different compression levels / settings. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.5.4Compression Level: 19, Long Mode - Decompression SpeedRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X400800120016002000SE +/- 8.37, N = 15SE +/- 29.67, N = 15SE +/- 16.22, N = 3SE +/- 6.34, N = 31997.41876.31872.41990.01. (CC) gcc options: -O3 -pthread -lz -llzma -llz4

ONNX Runtime

ONNX Runtime is developed by Microsoft and partners as a open-source, cross-platform, high performance machine learning inferencing and training accelerator. This test profile runs the ONNX Runtime with various models available from the ONNX Model Zoo. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: Faster R-CNN R-50-FPN-int8 - Device: CPU - Executor: StandardRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X48121620SE +/- 0.55, N = 15SE +/- 0.08, N = 3SE +/- 0.48, N = 15SE +/- 0.02, N = 316.8814.5114.4514.271. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: Faster R-CNN R-50-FPN-int8 - Device: CPU - Executor: StandardRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X1632486480SE +/- 1.94, N = 15SE +/- 0.38, N = 3SE +/- 2.04, N = 15SE +/- 0.09, N = 360.1168.9270.1670.091. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: Faster R-CNN R-50-FPN-int8 - Device: CPU - Executor: StandardRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X48121620SE +/- 0.55, N = 15SE +/- 0.08, N = 3SE +/- 0.48, N = 15SE +/- 0.02, N = 316.8814.5114.4514.271. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: CaffeNet 12-int8 - Device: CPU - Executor: StandardRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X0.22820.45640.68460.91281.141SE +/- 0.029891, N = 15SE +/- 0.005430, N = 3SE +/- 0.033238, N = 15SE +/- 0.007823, N = 61.0140880.8655050.9381490.8169941. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: CaffeNet 12-int8 - Device: CPU - Executor: StandardRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X30060090012001500SE +/- 31.87, N = 15SE +/- 7.21, N = 3SE +/- 39.20, N = 15SE +/- 11.41, N = 6998.861155.141084.911224.001. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: CaffeNet 12-int8 - Device: CPU - Executor: StandardRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X0.22820.45640.68460.91281.141SE +/- 0.029891, N = 15SE +/- 0.005430, N = 3SE +/- 0.033238, N = 15SE +/- 0.007823, N = 61.0140880.8655050.9381490.8169941. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: ResNet50 v1-12-int8 - Device: CPU - Executor: StandardRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X0.5321.0641.5962.1282.66SE +/- 0.05616, N = 12SE +/- 0.03587, N = 15SE +/- 0.04809, N = 15SE +/- 0.02087, N = 152.334612.364632.067992.063091. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: ResNet50 v1-12-int8 - Device: CPU - Executor: StandardRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X110220330440550SE +/- 10.29, N = 12SE +/- 6.30, N = 15SE +/- 9.53, N = 15SE +/- 4.65, N = 15430.96424.17486.61485.241. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: ResNet50 v1-12-int8 - Device: CPU - Executor: StandardRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X0.5321.0641.5962.1282.66SE +/- 0.05616, N = 12SE +/- 0.03587, N = 15SE +/- 0.04809, N = 15SE +/- 0.02087, N = 152.334612.364632.067992.063091. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: ArcFace ResNet-100 - Device: CPU - Executor: StandardRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X612182430SE +/- 0.86, N = 15SE +/- 1.05, N = 12SE +/- 1.02, N = 15SE +/- 0.66, N = 1523.9425.5627.3122.571. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: ArcFace ResNet-100 - Device: CPU - Executor: StandardRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X1020304050SE +/- 1.23, N = 15SE +/- 1.38, N = 12SE +/- 1.50, N = 15SE +/- 1.19, N = 1542.3839.7437.3944.791. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: ArcFace ResNet-100 - Device: CPU - Executor: StandardRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X612182430SE +/- 0.86, N = 15SE +/- 1.05, N = 12SE +/- 1.02, N = 15SE +/- 0.66, N = 1523.9425.5627.3122.571. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: super-resolution-10 - Device: CPU - Executor: StandardRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X246810SE +/- 0.22770, N = 15SE +/- 0.40239, N = 15SE +/- 0.18428, N = 15SE +/- 0.19969, N = 135.851537.517026.291456.149841. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: super-resolution-10 - Device: CPU - Executor: StandardRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X4080120160200SE +/- 5.34, N = 15SE +/- 7.10, N = 15SE +/- 5.64, N = 15SE +/- 6.30, N = 13173.78138.33161.23165.011. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: super-resolution-10 - Device: CPU - Executor: StandardRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X246810SE +/- 0.22770, N = 15SE +/- 0.40239, N = 15SE +/- 0.18428, N = 15SE +/- 0.19969, N = 135.851537.517026.291456.149841. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: yolov4 - Device: CPU - Executor: StandardRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X20406080100SE +/- 4.06, N = 15SE +/- 4.87, N = 15SE +/- 3.62, N = 15SE +/- 3.19, N = 15101.17102.27101.97100.751. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: yolov4 - Device: CPU - Executor: StandardRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X3691215SE +/- 0.40412, N = 15SE +/- 0.45158, N = 15SE +/- 0.38311, N = 15SE +/- 0.36261, N = 1510.1103310.078329.9960410.086251. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
OpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.14Model: yolov4 - Device: CPU - Executor: StandardRyzen 9 7900XRyzen 9 7900X3DRyzen 9 79500X3DRyzen 9 7950X20406080100SE +/- 4.06, N = 15SE +/- 4.87, N = 15SE +/- 3.62, N = 15SE +/- 3.19, N = 15101.17102.27101.97100.751. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

149 Results Shown

ONNX Runtime
ASKAP
CloverLeaf
oneDNN
OpenVINO
Pennant
OpenVINO:
  Weld Porosity Detection FP16-INT8 - CPU
  Age Gender Recognition Retail 0013 FP16 - CPU
  Age Gender Recognition Retail 0013 FP16-INT8 - CPU
  Vehicle Detection FP16-INT8 - CPU
  Face Detection FP16-INT8 - CPU
  Weld Porosity Detection FP16 - CPU
oneDNN:
  Deconvolution Batch shapes_3d - bf16bf16bf16 - CPU
  Deconvolution Batch shapes_1d - bf16bf16bf16 - CPU
  Matrix Multiply Batch Shapes Transformer - bf16bf16bf16 - CPU
OpenVINO
KTX-Software toktx
ONNX Runtime
OpenVINO
oneDNN:
  IP Shapes 3D - bf16bf16bf16 - CPU
  Recurrent Neural Network Inference - bf16bf16bf16 - CPU
  Recurrent Neural Network Training - bf16bf16bf16 - CPU
Xmrig
ACES DGEMM
OpenVINO
Pennant
OpenVINO
OpenFOAM
Embree
ASKAP
Embree
OpenVINO
TensorFlow
Embree
KTX-Software toktx
ONNX Runtime
Embree:
  Pathtracer - Asian Dragon Obj
  Pathtracer ISPC - Asian Dragon Obj
ONNX Runtime
Embree
OpenVINO
TensorFlow
ONNX Runtime
Zstd Compression
ONNX Runtime
ASKAP
Zstd Compression
srsRAN
ONNX Runtime
NCNN
Zstd Compression:
  19, Long Mode - Compression Speed
  12 - Compression Speed
KTX-Software toktx
NCNN
GPAW
GROMACS
TensorFlow
Xmrig
TensorFlow:
  CPU - 256 - GoogLeNet
  CPU - 32 - GoogLeNet
NCNN
ONNX Runtime
TensorFlow:
  CPU - 16 - GoogLeNet
  CPU - 64 - GoogLeNet
Xcompact3d Incompact3d
NCNN
ClickHouse
Xcompact3d Incompact3d
OpenFOAM
ONNX Runtime
TensorFlow
ClickHouse
OpenFOAM
ASKAP
srsRAN
TensorFlow
Zstd Compression
TensorFlow:
  CPU - 32 - ResNet-50
  CPU - 16 - ResNet-50
ONNX Runtime:
  bertsquad-12 - CPU - Standard
  GPT-2 - CPU - Parallel
OpenFOAM
ClickHouse
OpenVINO
NCNN
ASKAP
OpenVINO
TensorFlow
OpenVINO:
  Weld Porosity Detection FP16-INT8 - CPU
  Machine Translation EN To DE FP16 - CPU
  Vehicle Detection FP16-INT8 - CPU
ASKAP
OpenVINO:
  Weld Porosity Detection FP16 - CPU
  Face Detection FP16-INT8 - CPU
ASKAP
OpenVINO
Zstd Compression
OpenVINO:
  Person Detection FP32 - CPU
  Face Detection FP16 - CPU
NCNN:
  CPU-v2-v2 - mobilenet-v2
  CPU - mnasnet
  CPU - mobilenet
ONNX Runtime
Zstd Compression
NCNN:
  CPU - efficientnet-b0
  CPU - vgg16
OpenVINO
LULESH
NCNN:
  CPU-v3-v3 - mobilenet-v3
  CPU - resnet50
  CPU - squeezenet_ssd
srsRAN:
  OFDM_Test
  4G PHY_DL_Test 100 PRB MIMO 64-QAM
KTX-Software toktx
NCNN
Zstd Compression
srsRAN
LeelaChessZero
srsRAN:
  4G PHY_DL_Test 100 PRB MIMO 256-QAM:
    eNb Mb/s
    UE Mb/s
Zstd Compression
PyHPC Benchmarks:
  CPU - Numpy - 4194304 - Equation of State
  CPU - Numpy - 4194304 - Isoneutral Mixing
srsRAN
Zstd Compression
srsRAN
Zstd Compression:
  8 - Decompression Speed
  3, Long Mode - Decompression Speed
LeelaChessZero
srsRAN
Zstd Compression
NCNN:
  CPU - FastestDet
  CPU - resnet18
  CPU - googlenet
srsRAN
oneDNN
Zstd Compression
ONNX Runtime:
  Faster R-CNN R-50-FPN-int8 - CPU - Standard:
    Inference Time Cost (ms)
    Inferences Per Second
  CaffeNet 12-int8 - CPU - Standard:
    Inference Time Cost (ms)
    Inferences Per Second
  ResNet50 v1-12-int8 - CPU - Standard:
    Inference Time Cost (ms)
    Inferences Per Second
  ArcFace ResNet-100 - CPU - Standard:
    Inference Time Cost (ms)
    Inferences Per Second
  super-resolution-10 - CPU - Standard:
    Inference Time Cost (ms)
    Inferences Per Second
  yolov4 - CPU - Standard:
    Inference Time Cost (ms)
    Inferences Per Second

Ryzen 9 7900X3D

Processor: AMD Ryzen 9 7900X3D 12-Core @ 4.40GHz (12 Cores / 24 Threads), Motherboard: ASUS ROG CROSSHAIR X670E HERO (9922 BIOS), Chipset: AMD Device 14d8, Memory: 32GB, Disk: Western Digital WD_BLACK SN850X 1000GB + 2000GB, Graphics: AMD Radeon RX 7900 XTX 24GB (2304/1249MHz), Audio: AMD Device ab30, Monitor: ASUS MG28U, Network: Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411

OS: Ubuntu 23.04, Kernel: 6.2.2-060202-generic (x86_64), Desktop: GNOME Shell 43.2, Display Server: X Server 1.21.1.6 + Wayland, OpenGL: 4.6 Mesa 23.1.0-devel (git-efcb639 2023-02-13 lunar-oibaf-ppa) (LLVM 15.0.7 DRM 3.49), Compiler: GCC 12.2.0, File-System: ext4, Screen Resolution: 3840x2160

Kernel Notes: Transparent Huge Pages: madvise
Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-cet --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-defaulted --enable-offload-targets=nvptx-none=/build/gcc-12-AKimc9/gcc-12-12.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-12-AKimc9/gcc-12-12.2.0/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-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: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0xa601203
Python Notes: Python 3.11.1
Security Notes: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Retpolines IBPB: conditional IBRS_FW STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected

Testing initiated at 3 March 2023 20:08 by user phoronix.

Ryzen 9 7900X

Processor: AMD Ryzen 9 7900X 12-Core @ 4.70GHz (12 Cores / 24 Threads), Motherboard: ASUS ROG CROSSHAIR X670E HERO (9922 BIOS), Chipset: AMD Device 14d8, Memory: 32GB, Disk: Western Digital WD_BLACK SN850X 1000GB + 2000GB, Graphics: AMD Radeon RX 7900 XTX 24GB (2304/1249MHz), Audio: AMD Device ab30, Monitor: ASUS MG28U, Network: Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411

OS: Ubuntu 23.04, Kernel: 6.2.2-060202-generic (x86_64), Desktop: GNOME Shell 43.2, Display Server: X Server 1.21.1.6 + Wayland, OpenGL: 4.6 Mesa 23.1.0-devel (git-efcb639 2023-02-13 lunar-oibaf-ppa) (LLVM 15.0.7 DRM 3.49), Compiler: GCC 12.2.0, File-System: ext4, Screen Resolution: 3840x2160

Kernel Notes: Transparent Huge Pages: madvise
Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-cet --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-defaulted --enable-offload-targets=nvptx-none=/build/gcc-12-AKimc9/gcc-12-12.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-12-AKimc9/gcc-12-12.2.0/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-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: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0xa601203
Python Notes: Python 3.11.1
Security Notes: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Retpolines IBPB: conditional IBRS_FW STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected

Testing initiated at 4 March 2023 06:58 by user phoronix.

Ryzen 9 79500X3D

Processor: AMD Ryzen 9 7950X3D 16-Core @ 4.20GHz (16 Cores / 32 Threads), Motherboard: ASUS ROG CROSSHAIR X670E HERO (9922 BIOS), Chipset: AMD Device 14d8, Memory: 32GB, Disk: Western Digital WD_BLACK SN850X 1000GB + 2000GB, Graphics: AMD Radeon RX 7900 XTX 24GB (2304/1249MHz), Audio: AMD Device ab30, Monitor: ASUS MG28U, Network: Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411

OS: Ubuntu 23.04, Kernel: 6.2.2-060202-generic (x86_64), Desktop: GNOME Shell 43.2, Display Server: X Server 1.21.1.6 + Wayland, OpenGL: 4.6 Mesa 23.1.0-devel (git-efcb639 2023-02-13 lunar-oibaf-ppa) (LLVM 15.0.7 DRM 3.49), Compiler: GCC 12.2.0, File-System: ext4, Screen Resolution: 3840x2160

Kernel Notes: Transparent Huge Pages: madvise
Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-cet --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-defaulted --enable-offload-targets=nvptx-none=/build/gcc-12-AKimc9/gcc-12-12.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-12-AKimc9/gcc-12-12.2.0/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-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: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0xa601203
Python Notes: Python 3.11.1
Security Notes: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Retpolines IBPB: conditional IBRS_FW STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected

Testing initiated at 4 March 2023 21:15 by user phoronix.

Ryzen 9 7950X

Processor: AMD Ryzen 9 7950X 16-Core @ 4.50GHz (16 Cores / 32 Threads), Motherboard: ASUS ROG CROSSHAIR X670E HERO (9922 BIOS), Chipset: AMD Device 14d8, Memory: 32GB, Disk: Western Digital WD_BLACK SN850X 1000GB + 2000GB, Graphics: AMD Radeon RX 7900 XTX 24GB (2304/1249MHz), Audio: AMD Device ab30, Monitor: ASUS MG28U, Network: Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411

OS: Ubuntu 23.04, Kernel: 6.2.2-060202-generic (x86_64), Desktop: GNOME Shell 43.2, Display Server: X Server 1.21.1.6 + Wayland, OpenGL: 4.6 Mesa 23.1.0-devel (git-efcb639 2023-02-13 lunar-oibaf-ppa) (LLVM 15.0.7 DRM 3.49), Compiler: GCC 12.2.0, File-System: ext4, Screen Resolution: 3840x2160

Kernel Notes: Transparent Huge Pages: madvise
Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-cet --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-defaulted --enable-offload-targets=nvptx-none=/build/gcc-12-AKimc9/gcc-12-12.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-12-AKimc9/gcc-12-12.2.0/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-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: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0xa601203
Python Notes: Python 3.11.1
Security Notes: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Retpolines IBPB: conditional IBRS_FW STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected

Testing initiated at 5 March 2023 06:57 by user phoronix.