AMD Ryzen 9 7950X / Ryzen 9 9950X AVX-512 Comparison

AMD Ryzen 9 7950X and Ryzen 9 9950X AVX-512 on/off comparison benchmarks by Michael Larabel for a future article.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2408145-NE-RYZEN999549
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Ryzen 9 9950X: AVX-512 On
August 11
  5 Hours, 44 Minutes
Ryzen 9 9950X: AVX-512 Off
August 12
  5 Hours, 22 Minutes
Ryzen 9 7950X: AVX-512 On
August 12
  5 Hours, 35 Minutes
Ryzen 9 7950X: AVX-512 Off
August 12
  5 Hours, 39 Minutes
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AMD Ryzen 9 7950X / Ryzen 9 9950X AVX-512 ComparisonOpenBenchmarking.orgPhoronix Test SuiteAMD Ryzen 9 9950X 16-Core @ 5.75GHz (16 Cores / 32 Threads)AMD Ryzen 9 7950X 16-Core @ 5.88GHz (16 Cores / 32 Threads)ASUS ROG STRIX X670E-E GAMING WIFI (2124 BIOS)AMD Device 14d82 x 16GB DDR5-6000MT/s G Skill F5-6000J3038F16G2000GB Corsair MP700 PROAMD Radeon RX 7900 GRE 16GBAMD Navi 31 HDMI/DPDELL U2723QEIntel I225-V + Intel Wi-Fi 6EUbuntu 24.046.10.0-phx (x86_64)GNOME Shell 46.0X Server + Wayland4.6 Mesa 24.2~git2406040600.8112d4~oibaf~n (git-8112d44 2024-06-04 noble-oibaf-ppa) (LLVM 17.0.6 DRM 3.57)GCC 13.2.0ext43840x2160ProcessorsMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelDesktopDisplay ServerOpenGLCompilerFile-SystemScreen ResolutionAMD Ryzen 9 7950X / Ryzen 9 9950X AVX-512 Comparison 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-backtrace --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-13-uJ7kn6/gcc-13-13.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-13-uJ7kn6/gcc-13-13.2.0/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 - Ryzen 9 9950X: AVX-512 On: Scaling Governor: amd-pstate-epp powersave (EPP: balance_performance) - CPU Microcode: 0xb40401a- Ryzen 9 9950X: AVX-512 Off: Scaling Governor: amd-pstate-epp powersave (EPP: balance_performance) - CPU Microcode: 0xb40401a- Ryzen 9 7950X: AVX-512 Off: Scaling Governor: amd-pstate-epp powersave (EPP: balance_performance) - CPU Microcode: 0xa601206- Ryzen 9 7950X: AVX-512 On: Scaling Governor: amd-pstate-epp powersave (EPP: balance_performance) - CPU Microcode: 0xa601206- Python 3.12.3- Ryzen 9 9950X: AVX-512 On: gather_data_sampling: Not affected + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + reg_file_data_sampling: Not affected + retbleed: Not affected + spec_rstack_overflow: 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 Enhanced / Automatic IBRS; IBPB: conditional; STIBP: always-on; RSB filling; PBRSB-eIBRS: Not affected; BHI: Not affected + srbds: Not affected + tsx_async_abort: Not affected - Ryzen 9 9950X: AVX-512 Off: gather_data_sampling: Not affected + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + reg_file_data_sampling: Not affected + retbleed: Not affected + spec_rstack_overflow: 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 Enhanced / Automatic IBRS; IBPB: conditional; STIBP: always-on; RSB filling; PBRSB-eIBRS: Not affected; BHI: Not affected + srbds: Not affected + tsx_async_abort: Not affected - Ryzen 9 7950X: AVX-512 Off: gather_data_sampling: Not affected + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + reg_file_data_sampling: Not affected + retbleed: Not affected + spec_rstack_overflow: Mitigation of Safe RET + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Enhanced / Automatic IBRS; IBPB: conditional; STIBP: always-on; RSB filling; PBRSB-eIBRS: Not affected; BHI: Not affected + srbds: Not affected + tsx_async_abort: Not affected - Ryzen 9 7950X: AVX-512 On: gather_data_sampling: Not affected + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + reg_file_data_sampling: Not affected + retbleed: Not affected + spec_rstack_overflow: Mitigation of Safe RET + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Enhanced / Automatic IBRS; IBPB: conditional; STIBP: always-on; RSB filling; PBRSB-eIBRS: Not affected; BHI: Not affected + srbds: Not affected + tsx_async_abort: Not affected

openvkl: vklBenchmarkCPU ISPClczero: BLASlczero: Eigenxnnpack: QU8MobileNetV3Largexnnpack: QU8MobileNetV2tensorflow: CPU - 64 - ResNet-50simdjson: PartialTweetsospray-studio: 3 - 4K - 32 - Path Tracer - CPUospray: particle_volume/pathtracer/real_timeospray-studio: 1 - 4K - 32 - Path Tracer - CPUonnx: CaffeNet 12-int8 - CPU - Standardonnx: CaffeNet 12-int8 - CPU - Standardmnn: resnet-v2-50simdjson: Kostyanamd: STMV with 1,066,628 Atomsnumpy: ospray-studio: 3 - 4K - 16 - Path Tracer - CPUsimdjson: LargeRandospray-studio: 3 - 4K - 1 - Path Tracer - CPUospray-studio: 1 - 4K - 1 - Path Tracer - CPUonednn: Recurrent Neural Network Training - CPUonednn: Recurrent Neural Network Inference - CPUsimdjson: DistinctUserIDospray-studio: 1 - 4K - 16 - Path Tracer - CPUsimdjson: TopTweetgromacs: MPI CPU - water_GMX50_bareospray: gravity_spheres_volume/dim_512/scivis/real_timeospray: gravity_spheres_volume/dim_512/ao/real_timeopenvino: Face Detection FP16 - CPUopenvino: Face Detection FP16 - CPUonnx: fcn-resnet101-11 - CPU - Standardonnx: fcn-resnet101-11 - CPU - Standardopenvino: Machine Translation EN To DE FP16 - CPUopenvino: Machine Translation EN To DE FP16 - CPUopenvino: Person Detection FP16 - CPUopenvino: Person Detection FP16 - CPUopenvino: Noise Suppression Poconet-Like FP16 - CPUopenvino: Noise Suppression Poconet-Like FP16 - CPUopenvino: Road Segmentation ADAS FP16-INT8 - CPUopenvino: Road Segmentation ADAS FP16-INT8 - CPUonnx: ArcFace ResNet-100 - CPU - Standardonnx: ArcFace ResNet-100 - CPU - Standardopenvino: Person Vehicle Bike Detection FP16 - CPUopenvino: Person Vehicle Bike Detection FP16 - CPUopenvino: Person Re-Identification Retail FP16 - CPUopenvino: Person Re-Identification Retail FP16 - CPUopenvino: Handwritten English Recognition FP16 - CPUopenvino: Handwritten English Recognition FP16 - CPUopenvino: Age Gender Recognition Retail 0013 FP16 - CPUopenvino: Age Gender Recognition Retail 0013 FP16 - CPUopenvino: Vehicle Detection FP16 - CPUopenvino: Vehicle Detection FP16 - CPUopenvino: Weld Porosity Detection FP16 - CPUopenvino: Weld Porosity Detection FP16 - CPUopenvino: Face Detection Retail FP16 - CPUopenvino: Face Detection Retail FP16 - CPUonnx: ResNet50 v1-12-int8 - CPU - Standardonnx: ResNet50 v1-12-int8 - CPU - Standardonnx: super-resolution-10 - CPU - Standardonnx: super-resolution-10 - CPU - Standardospray: gravity_spheres_volume/dim_512/pathtracer/real_timepytorch: CPU - 64 - ResNet-50namd: ATPase with 327,506 Atomsembree: Pathtracer ISPC - Asian Dragon Objembree: Pathtracer ISPC - Crownonednn: IP Shapes 1D - CPUonednn: Deconvolution Batch shapes_1d - CPUembree: Pathtracer ISPC - Asian Dragonpytorch: CPU - 1 - ResNet-50minibude: OpenMP - BM1minibude: OpenMP - BM1y-cruncher: 1Btensorflow: CPU - 1 - ResNet-50y-cruncher: 500Monednn: IP Shapes 3D - CPUonednn: Deconvolution Batch shapes_3d - CPURyzen 9 9950XRyzen 9 7950X AVX-512 On AVX-512 Off AVX-512 Off AVX-512 On765220220115478551.7412.38124596277.2801057981.14595872.94010.0487.470.987071054.92634762.0738293225759.934404.69713.055402212.953.1359.532779.72700342.8123.29205.9804.8548845.10177.1173.12109.298.431867.6012.50638.6718.018155.50783.722133.762.593027.6816.56962.920.2555883.548.77908.966.822327.181.534938.981.74942571.4684.39253227.64611.030057.893.4833835.507136.65150.6648751.7884641.351585.1477.1901929.75316.49016.827.5703.075301.36386656205162117785638.999.99138397261.1561177121.24400803.44211.3176.430.484921010.59703641.90423535941258.80635.73210.445995810.332.6696.469206.706621168.946.80277.7513.60032102.8677.69131.6060.6913.181201.7316.74476.8820.076949.806510.06792.037.671034.5446.11346.430.7519062.5815.29521.7023.57675.853.922015.672.23540447.2386.62128151.0239.0837647.051.6975734.081434.62721.058552.4119239.532770.1438.469961.72720.23012.989.0736.167212.59761507168142113087019.737.20195460210.8501668051.65024605.77112.6554.800.42614731.83994751.58602051311303.16664.1547.59852777.642.5924.208254.442331158.016.87292.7073.41636104.1176.77127.2662.8013.571166.2422.22359.2620.899547.847310.08791.267.611048.4948.98326.300.8017640.8416.50483.5923.67674.773.942015.993.33639299.6697.29254137.1266.3575543.871.4935426.716928.78281.211952.8025131.037863.2338.401960.03718.05712.228.3956.602932.72463647171177109480744.089.47154740239.2971316051.43682695.73110.8756.010.82581794.79792711.81473540041245.28629.59810.286761110.482.7407.937308.07646556.0014.33281.8673.5477557.56138.7978.75101.519.361680.4216.58481.0420.895847.85254.771667.923.872059.5220.61775.120.436493.6010.02795.7010.971454.522.283357.782.38498419.1866.90690144.7779.1796250.233.0587729.546933.76651.006612.7534634.711174.4653.1221328.05016.02916.237.6963.115082.38830OpenBenchmarking.org

OpenVKL

OpenVKL is the Intel Open Volume Kernel Library that offers high-performance volume computation kernels and part of the Intel oneAPI rendering toolkit. Learn more via the OpenBenchmarking.org test page.

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgItems / Sec, More Is BetterOpenVKL 2.0.0Benchmark: vklBenchmarkCPU ISPCAVX-512 OnAVX-512 Off160320480640800SE +/- 0.33, N = 3SE +/- 0.33, N = 3SE +/- 0.33, N = 3SE +/- 0.33, N = 3765656507647

LeelaChessZero

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgNodes Per Second, More Is BetterLeelaChessZero 0.31.1Backend: BLASAVX-512 OnAVX-512 Off50100150200250SE +/- 1.76, N = 3SE +/- 2.40, N = 3SE +/- 0.33, N = 3SE +/- 1.65, N = 62202051681711. (CXX) g++ options: -flto -pthread

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgNodes Per Second, More Is BetterLeelaChessZero 0.31.1Backend: EigenAVX-512 OnAVX-512 Off50100150200250SE +/- 1.76, N = 3SE +/- 1.53, N = 3SE +/- 1.67, N = 3SE +/- 2.03, N = 32201621421771. (CXX) g++ options: -flto -pthread

XNNPACK

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgus, Fewer Is BetterXNNPACK 2cd86bModel: QU8MobileNetV3LargeAVX-512 OnAVX-512 Off30060090012001500SE +/- 1.15, N = 3SE +/- 2.03, N = 3SE +/- 3.84, N = 3SE +/- 3.38, N = 311541177113010941. (CXX) g++ options: -O3 -lrt -lm

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgus, Fewer Is BetterXNNPACK 2cd86bModel: QU8MobileNetV2AVX-512 OnAVX-512 Off2004006008001000SE +/- 3.93, N = 3SE +/- 0.58, N = 3SE +/- 1.45, N = 3SE +/- 0.67, N = 37858568708071. (CXX) g++ options: -O3 -lrt -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 if desired for complementary metrics. Learn more via the OpenBenchmarking.org test page.

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 64 - Model: ResNet-50AVX-512 OnAVX-512 Off1224364860SE +/- 0.04, N = 3SE +/- 0.02, N = 3SE +/- 0.02, N = 3SE +/- 0.02, N = 351.7438.9919.7344.08

simdjson

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgGB/s, More Is Bettersimdjson 3.10Throughput Test: PartialTweetsAVX-512 OnAVX-512 Off3691215SE +/- 0.12, N = 15SE +/- 0.08, N = 9SE +/- 0.07, N = 3SE +/- 0.02, N = 312.389.997.209.471. (CXX) g++ options: -O3 -lrt

OSPRay Studio

Intel OSPRay Studio is an open-source, interactive visualization and ray-tracing software package. OSPRay Studio makes use of Intel OSPRay, a portable ray-tracing engine for high-performance, high-fidelity visualizations. OSPRay builds off Intel's Embree and Intel SPMD Program Compiler (ISPC) components as part of the oneAPI rendering toolkit. Learn more via the OpenBenchmarking.org test page.

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 1.0Camera: 3 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPUAVX-512 OnAVX-512 Off40K80K120K160K200KSE +/- 55.03, N = 3SE +/- 188.82, N = 3SE +/- 475.57, N = 3SE +/- 26.96, N = 3124596138397195460154740

OSPRay

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgItems Per Second, More Is BetterOSPRay 3.2Benchmark: particle_volume/pathtracer/real_timeAVX-512 OnAVX-512 Off60120180240300SE +/- 0.40, N = 3SE +/- 0.58, N = 3SE +/- 0.33, N = 3SE +/- 0.60, N = 3277.28261.16210.85239.30

OSPRay Studio

Intel OSPRay Studio is an open-source, interactive visualization and ray-tracing software package. OSPRay Studio makes use of Intel OSPRay, a portable ray-tracing engine for high-performance, high-fidelity visualizations. OSPRay builds off Intel's Embree and Intel SPMD Program Compiler (ISPC) components as part of the oneAPI rendering toolkit. Learn more via the OpenBenchmarking.org test page.

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 1.0Camera: 1 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPUAVX-512 OnAVX-512 Off40K80K120K160K200KSE +/- 68.30, N = 3SE +/- 147.11, N = 3SE +/- 116.94, N = 3SE +/- 209.54, N = 3105798117712166805131605

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.

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.17Model: CaffeNet 12-int8 - Device: CPU - Executor: StandardAVX-512 OnAVX-512 Off0.37130.74261.11391.48521.8565SE +/- 0.01010, N = 15SE +/- 0.00071, N = 3SE +/- 0.00147, N = 3SE +/- 0.00680, N = 31.145951.244001.650241.436821. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.17Model: CaffeNet 12-int8 - Device: CPU - Executor: StandardAVX-512 OnAVX-512 Off2004006008001000SE +/- 7.80, N = 15SE +/- 0.45, N = 3SE +/- 0.54, N = 3SE +/- 3.29, N = 3872.94803.44605.77695.731. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt

Mobile Neural Network

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgms, Fewer Is BetterMobile Neural Network 2.9.b11b7037dModel: resnet-v2-50AVX-512 OnAVX-512 Off3691215SE +/- 0.04, N = 3SE +/- 0.06, N = 3SE +/- 0.10, N = 3SE +/- 0.11, N = 310.0511.3212.6610.881. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -pthread -ldl

simdjson

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgGB/s, More Is Bettersimdjson 3.10Throughput Test: KostyaAVX-512 OnAVX-512 Off246810SE +/- 0.04, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.05, N = 37.476.434.806.011. (CXX) g++ options: -O3 -lrt

NAMD

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgns/day, More Is BetterNAMD 3.0b6Input: STMV with 1,066,628 AtomsAVX-512 OnAVX-512 Off0.22210.44420.66630.88841.1105SE +/- 0.00150, N = 3SE +/- 0.00040, N = 3SE +/- 0.00052, N = 3SE +/- 0.00092, N = 30.987070.484920.426140.82581

Numpy Benchmark

This is a test to obtain the general Numpy performance. Learn more via the OpenBenchmarking.org test page.

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgScore, More Is BetterNumpy BenchmarkAVX-512 OnAVX-512 Off2004006008001000SE +/- 6.93, N = 3SE +/- 2.31, N = 3SE +/- 2.88, N = 3SE +/- 6.26, N = 31054.921010.59731.83794.79

OSPRay Studio

Intel OSPRay Studio is an open-source, interactive visualization and ray-tracing software package. OSPRay Studio makes use of Intel OSPRay, a portable ray-tracing engine for high-performance, high-fidelity visualizations. OSPRay builds off Intel's Embree and Intel SPMD Program Compiler (ISPC) components as part of the oneAPI rendering toolkit. Learn more via the OpenBenchmarking.org test page.

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 1.0Camera: 3 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPUAVX-512 OnAVX-512 Off20K40K60K80K100KSE +/- 49.41, N = 3SE +/- 36.23, N = 3SE +/- 91.66, N = 3SE +/- 199.04, N = 363476703649947579271

simdjson

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgGB/s, More Is Bettersimdjson 3.10Throughput Test: LargeRandomAVX-512 OnAVX-512 Off0.46580.93161.39741.86322.329SE +/- 0.00, N = 3SE +/- 0.03, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 32.071.901.581.811. (CXX) g++ options: -O3 -lrt

OSPRay Studio

Intel OSPRay Studio is an open-source, interactive visualization and ray-tracing software package. OSPRay Studio makes use of Intel OSPRay, a portable ray-tracing engine for high-performance, high-fidelity visualizations. OSPRay builds off Intel's Embree and Intel SPMD Program Compiler (ISPC) components as part of the oneAPI rendering toolkit. Learn more via the OpenBenchmarking.org test page.

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 1.0Camera: 3 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPUAVX-512 OnAVX-512 Off13002600390052006500SE +/- 1.53, N = 3SE +/- 4.33, N = 3SE +/- 9.87, N = 3SE +/- 10.17, N = 33829423560204735

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 1.0Camera: 1 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPUAVX-512 OnAVX-512 Off11002200330044005500SE +/- 1.00, N = 3SE +/- 2.03, N = 3SE +/- 5.00, N = 3SE +/- 2.85, N = 33225359451314004

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.

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.4Harness: Recurrent Neural Network Training - Engine: CPUAVX-512 OnAVX-512 Off30060090012001500SE +/- 1.13, N = 3SE +/- 0.50, N = 3SE +/- 0.80, N = 3SE +/- 0.97, N = 3759.931258.801303.161245.281. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.4Harness: Recurrent Neural Network Inference - Engine: CPUAVX-512 OnAVX-512 Off140280420560700SE +/- 0.61, N = 3SE +/- 0.28, N = 3SE +/- 0.46, N = 3SE +/- 0.67, N = 3404.70635.73664.15629.601. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

simdjson

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgGB/s, More Is Bettersimdjson 3.10Throughput Test: DistinctUserIDAVX-512 OnAVX-512 Off3691215SE +/- 0.07, N = 3SE +/- 0.08, N = 3SE +/- 0.05, N = 3SE +/- 0.02, N = 313.0510.447.5910.281. (CXX) g++ options: -O3 -lrt

OSPRay Studio

Intel OSPRay Studio is an open-source, interactive visualization and ray-tracing software package. OSPRay Studio makes use of Intel OSPRay, a portable ray-tracing engine for high-performance, high-fidelity visualizations. OSPRay builds off Intel's Embree and Intel SPMD Program Compiler (ISPC) components as part of the oneAPI rendering toolkit. Learn more via the OpenBenchmarking.org test page.

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 1.0Camera: 1 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPUAVX-512 OnAVX-512 Off20K40K60K80K100KSE +/- 42.15, N = 3SE +/- 25.03, N = 3SE +/- 106.67, N = 3SE +/- 142.41, N = 354022599588527767611

simdjson

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgGB/s, More Is Bettersimdjson 3.10Throughput Test: TopTweetAVX-512 OnAVX-512 Off3691215SE +/- 0.14, N = 3SE +/- 0.02, N = 3SE +/- 0.01, N = 3SE +/- 0.09, N = 312.9510.337.6410.481. (CXX) g++ options: -O3 -lrt

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.

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgNs Per Day, More Is BetterGROMACS 2024Implementation: MPI CPU - Input: water_GMX50_bareAVX-512 OnAVX-512 Off0.70541.41082.11622.82163.527SE +/- 0.004, N = 3SE +/- 0.004, N = 3SE +/- 0.006, N = 3SE +/- 0.001, N = 33.1352.6692.5922.7401. (CXX) g++ options: -O3 -lm

OSPRay

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgItems Per Second, More Is BetterOSPRay 3.2Benchmark: gravity_spheres_volume/dim_512/scivis/real_timeAVX-512 OnAVX-512 Off3691215SE +/- 0.01315, N = 3SE +/- 0.01723, N = 3SE +/- 0.00671, N = 3SE +/- 0.00679, N = 39.532776.469204.208257.93730

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgItems Per Second, More Is BetterOSPRay 3.2Benchmark: gravity_spheres_volume/dim_512/ao/real_timeAVX-512 OnAVX-512 Off3691215SE +/- 0.00263, N = 3SE +/- 0.00321, N = 3SE +/- 0.00077, N = 3SE +/- 0.01996, N = 39.727006.706624.442338.07646

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.

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2024.0Model: Face Detection FP16 - Device: CPUAVX-512 OnAVX-512 Off30060090012001500SE +/- 0.13, N = 3SE +/- 3.79, N = 3SE +/- 0.43, N = 3SE +/- 0.04, N = 3342.811168.941158.01556.001. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgFPS, More Is BetterOpenVINO 2024.0Model: Face Detection FP16 - Device: CPUAVX-512 OnAVX-512 Off612182430SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 323.296.806.8714.331. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

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.

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.17Model: fcn-resnet101-11 - Device: CPU - Executor: StandardAVX-512 OnAVX-512 Off60120180240300SE +/- 0.61, N = 3SE +/- 0.14, N = 3SE +/- 0.25, N = 3SE +/- 0.28, N = 3205.98277.75292.71281.871. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.17Model: fcn-resnet101-11 - Device: CPU - Executor: StandardAVX-512 OnAVX-512 Off1.09232.18463.27694.36925.4615SE +/- 0.01446, N = 3SE +/- 0.00187, N = 3SE +/- 0.00295, N = 3SE +/- 0.00354, N = 34.854883.600323.416363.547751. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -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.

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2024.0Model: Machine Translation EN To DE FP16 - Device: CPUAVX-512 OnAVX-512 Off20406080100SE +/- 0.15, N = 3SE +/- 0.49, N = 3SE +/- 0.55, N = 3SE +/- 0.30, N = 345.10102.86104.1157.561. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgFPS, More Is BetterOpenVINO 2024.0Model: Machine Translation EN To DE FP16 - Device: CPUAVX-512 OnAVX-512 Off4080120160200SE +/- 0.57, N = 3SE +/- 0.38, N = 3SE +/- 0.41, N = 3SE +/- 0.72, N = 3177.1177.6976.77138.791. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2024.0Model: Person Detection FP16 - Device: CPUAVX-512 OnAVX-512 Off306090120150SE +/- 0.22, N = 3SE +/- 0.43, N = 3SE +/- 0.21, N = 3SE +/- 0.82, N = 373.12131.60127.2678.751. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgFPS, More Is BetterOpenVINO 2024.0Model: Person Detection FP16 - Device: CPUAVX-512 OnAVX-512 Off20406080100SE +/- 0.34, N = 3SE +/- 0.20, N = 3SE +/- 0.10, N = 3SE +/- 1.04, N = 3109.2960.6962.80101.511. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2024.0Model: Noise Suppression Poconet-Like FP16 - Device: CPUAVX-512 OnAVX-512 Off3691215SE +/- 0.02, N = 3SE +/- 0.03, N = 3SE +/- 0.03, N = 3SE +/- 0.02, N = 38.4313.1813.579.361. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgFPS, More Is BetterOpenVINO 2024.0Model: Noise Suppression Poconet-Like FP16 - Device: CPUAVX-512 OnAVX-512 Off400800120016002000SE +/- 3.92, N = 3SE +/- 2.28, N = 3SE +/- 2.29, N = 3SE +/- 2.92, N = 31867.601201.731166.241680.421. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2024.0Model: Road Segmentation ADAS FP16-INT8 - Device: CPUAVX-512 OnAVX-512 Off510152025SE +/- 0.06, N = 3SE +/- 0.13, N = 3SE +/- 0.03, N = 3SE +/- 0.04, N = 312.5016.7422.2216.581. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgFPS, More Is BetterOpenVINO 2024.0Model: Road Segmentation ADAS FP16-INT8 - Device: CPUAVX-512 OnAVX-512 Off140280420560700SE +/- 3.09, N = 3SE +/- 3.66, N = 3SE +/- 0.48, N = 3SE +/- 1.08, N = 3638.67476.88359.26481.041. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

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.

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.17Model: ArcFace ResNet-100 - Device: CPU - Executor: StandardAVX-512 OnAVX-512 Off510152025SE +/- 0.20, N = 3SE +/- 0.09, N = 3SE +/- 0.12, N = 3SE +/- 0.07, N = 318.0220.0820.9020.901. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.17Model: ArcFace ResNet-100 - Device: CPU - Executor: StandardAVX-512 OnAVX-512 Off1224364860SE +/- 0.61, N = 3SE +/- 0.22, N = 3SE +/- 0.28, N = 3SE +/- 0.15, N = 355.5149.8147.8547.851. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -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.

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2024.0Model: Person Vehicle Bike Detection FP16 - Device: CPUAVX-512 OnAVX-512 Off3691215SE +/- 0.01, N = 3SE +/- 0.04, N = 3SE +/- 0.11, N = 3SE +/- 0.03, N = 33.7210.0610.084.771. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgFPS, More Is BetterOpenVINO 2024.0Model: Person Vehicle Bike Detection FP16 - Device: CPUAVX-512 OnAVX-512 Off5001000150020002500SE +/- 5.99, N = 3SE +/- 3.56, N = 3SE +/- 8.20, N = 3SE +/- 10.71, N = 32133.76792.03791.261667.921. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2024.0Model: Person Re-Identification Retail FP16 - Device: CPUAVX-512 OnAVX-512 Off246810SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 32.597.677.613.871. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgFPS, More Is BetterOpenVINO 2024.0Model: Person Re-Identification Retail FP16 - Device: CPUAVX-512 OnAVX-512 Off6001200180024003000SE +/- 2.87, N = 3SE +/- 0.29, N = 3SE +/- 1.51, N = 3SE +/- 1.23, N = 33027.681034.541048.492059.521. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2024.0Model: Handwritten English Recognition FP16 - Device: CPUAVX-512 OnAVX-512 Off1122334455SE +/- 0.02, N = 3SE +/- 0.04, N = 3SE +/- 0.09, N = 3SE +/- 0.13, N = 316.5646.1148.9820.611. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgFPS, More Is BetterOpenVINO 2024.0Model: Handwritten English Recognition FP16 - Device: CPUAVX-512 OnAVX-512 Off2004006008001000SE +/- 1.39, N = 3SE +/- 0.29, N = 3SE +/- 0.62, N = 3SE +/- 4.65, N = 3962.92346.43326.30775.121. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2024.0Model: Age Gender Recognition Retail 0013 FP16 - Device: CPUAVX-512 OnAVX-512 Off0.180.360.540.720.9SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 30.250.750.800.401. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgFPS, More Is BetterOpenVINO 2024.0Model: Age Gender Recognition Retail 0013 FP16 - Device: CPUAVX-512 OnAVX-512 Off12K24K36K48K60KSE +/- 40.07, N = 3SE +/- 18.06, N = 3SE +/- 30.09, N = 3SE +/- 34.76, N = 355883.5419062.5817640.8436493.601. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2024.0Model: Vehicle Detection FP16 - Device: CPUAVX-512 OnAVX-512 Off48121620SE +/- 0.01, N = 3SE +/- 0.07, N = 3SE +/- 0.05, N = 3SE +/- 0.08, N = 38.7715.2916.5010.021. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgFPS, More Is BetterOpenVINO 2024.0Model: Vehicle Detection FP16 - Device: CPUAVX-512 OnAVX-512 Off2004006008001000SE +/- 0.91, N = 3SE +/- 2.33, N = 3SE +/- 1.66, N = 3SE +/- 6.59, N = 3908.96521.70483.59795.701. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2024.0Model: Weld Porosity Detection FP16 - Device: CPUAVX-512 OnAVX-512 Off612182430SE +/- 0.00, N = 3SE +/- 0.02, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 36.8223.5723.6710.971. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgFPS, More Is BetterOpenVINO 2024.0Model: Weld Porosity Detection FP16 - Device: CPUAVX-512 OnAVX-512 Off5001000150020002500SE +/- 1.07, N = 3SE +/- 0.69, N = 3SE +/- 0.19, N = 3SE +/- 0.51, N = 32327.18675.85674.771454.521. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2024.0Model: Face Detection Retail FP16 - Device: CPUAVX-512 OnAVX-512 Off0.88651.7732.65953.5464.4325SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 31.533.923.942.281. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgFPS, More Is BetterOpenVINO 2024.0Model: Face Detection Retail FP16 - Device: CPUAVX-512 OnAVX-512 Off11002200330044005500SE +/- 7.46, N = 3SE +/- 7.10, N = 3SE +/- 4.63, N = 3SE +/- 2.51, N = 34938.982015.672015.993357.781. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

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.

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.17Model: ResNet50 v1-12-int8 - Device: CPU - Executor: StandardAVX-512 OnAVX-512 Off0.75071.50142.25213.00283.7535SE +/- 0.00302, N = 3SE +/- 0.00529, N = 3SE +/- 0.00299, N = 3SE +/- 0.00598, N = 31.749422.235403.336392.384981. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.17Model: ResNet50 v1-12-int8 - Device: CPU - Executor: StandardAVX-512 OnAVX-512 Off120240360480600SE +/- 0.98, N = 3SE +/- 1.07, N = 3SE +/- 0.27, N = 3SE +/- 1.03, N = 3571.47447.24299.67419.191. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgInference Time Cost (ms), Fewer Is BetterONNX Runtime 1.17Model: super-resolution-10 - Device: CPU - Executor: StandardAVX-512 OnAVX-512 Off246810SE +/- 0.00355, N = 3SE +/- 0.00170, N = 3SE +/- 0.02791, N = 3SE +/- 0.00447, N = 34.392536.621287.292546.906901. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.17Model: super-resolution-10 - Device: CPU - Executor: StandardAVX-512 OnAVX-512 Off50100150200250SE +/- 0.18, N = 3SE +/- 0.04, N = 3SE +/- 0.52, N = 3SE +/- 0.09, N = 3227.65151.02137.13144.781. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt

OSPRay

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgItems Per Second, More Is BetterOSPRay 3.2Benchmark: gravity_spheres_volume/dim_512/pathtracer/real_timeAVX-512 OnAVX-512 Off3691215SE +/- 0.00324, N = 3SE +/- 0.00447, N = 3SE +/- 0.00125, N = 3SE +/- 0.01877, N = 311.030009.083766.357559.17962

PyTorch

This is a benchmark of PyTorch making use of pytorch-benchmark [https://github.com/LukasHedegaard/pytorch-benchmark]. Learn more via the OpenBenchmarking.org test page.

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 64 - Model: ResNet-50AVX-512 OnAVX-512 Off1326395265SE +/- 0.41, N = 3SE +/- 0.36, N = 3SE +/- 0.11, N = 3SE +/- 0.30, N = 357.8947.0543.8750.23

NAMD

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgns/day, More Is BetterNAMD 3.0b6Input: ATPase with 327,506 AtomsAVX-512 OnAVX-512 Off0.78381.56762.35143.13523.919SE +/- 0.02808, N = 3SE +/- 0.01059, N = 3SE +/- 0.00219, N = 3SE +/- 0.02678, N = 33.483381.697571.493543.05877

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.

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.3Binary: Pathtracer ISPC - Model: Asian Dragon ObjAVX-512 OnAVX-512 Off816243240SE +/- 0.01, N = 3SE +/- 0.04, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 335.5134.0826.7229.55

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.3Binary: Pathtracer ISPC - Model: CrownAVX-512 OnAVX-512 Off816243240SE +/- 0.04, N = 3SE +/- 0.02, N = 3SE +/- 0.07, N = 3SE +/- 0.08, N = 336.6534.6328.7833.77

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.

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.4Harness: IP Shapes 1D - Engine: CPUAVX-512 OnAVX-512 Off0.27270.54540.81811.09081.3635SE +/- 0.006767, N = 6SE +/- 0.002635, N = 4SE +/- 0.000909, N = 4SE +/- 0.000816, N = 40.6648751.0585501.2119501.0066101. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.4Harness: Deconvolution Batch shapes_1d - Engine: CPUAVX-512 OnAVX-512 Off0.63061.26121.89182.52243.153SE +/- 0.00399, N = 3SE +/- 0.00490, N = 3SE +/- 0.00224, N = 3SE +/- 0.00663, N = 31.788462.411922.802512.753461. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

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.

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.3Binary: Pathtracer ISPC - Model: Asian DragonAVX-512 OnAVX-512 Off918273645SE +/- 0.01, N = 3SE +/- 0.05, N = 3SE +/- 0.01, N = 3SE +/- 0.03, N = 341.3539.5331.0434.71

PyTorch

This is a benchmark of PyTorch making use of pytorch-benchmark [https://github.com/LukasHedegaard/pytorch-benchmark]. Learn more via the OpenBenchmarking.org test page.

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 1 - Model: ResNet-50AVX-512 OnAVX-512 Off20406080100SE +/- 0.88, N = 4SE +/- 0.81, N = 4SE +/- 0.33, N = 3SE +/- 0.54, N = 385.1470.1463.2374.46

miniBUDE

MiniBUDE is a mini application for the the core computation of the Bristol University Docking Engine (BUDE). This test profile currently makes use of the OpenMP implementation of miniBUDE for CPU benchmarking. Learn more via the OpenBenchmarking.org test page.

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgBillion Interactions/s, More Is BetterminiBUDE 20210901Implementation: OpenMP - Input Deck: BM1AVX-512 OnAVX-512 Off20406080100SE +/- 0.06, N = 5SE +/- 0.02, N = 3SE +/- 0.33, N = 3SE +/- 0.00, N = 477.1938.4738.4053.121. (CC) gcc options: -std=c99 -Ofast -ffast-math -fopenmp -march=native -lm

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgGFInst/s, More Is BetterminiBUDE 20210901Implementation: OpenMP - Input Deck: BM1AVX-512 OnAVX-512 Off400800120016002000SE +/- 1.54, N = 5SE +/- 0.52, N = 3SE +/- 8.36, N = 3SE +/- 0.05, N = 41929.75961.73960.041328.051. (CC) gcc options: -std=c99 -Ofast -ffast-math -fopenmp -march=native -lm

Y-Cruncher

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgSeconds, Fewer Is BetterY-Cruncher 0.8.5Pi Digits To Calculate: 1BAVX-512 OnAVX-512 Off510152025SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.02, N = 316.4920.2318.0616.03

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 if desired for complementary metrics. Learn more via the OpenBenchmarking.org test page.

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 1 - Model: ResNet-50AVX-512 OnAVX-512 Off48121620SE +/- 0.04, N = 5SE +/- 0.01, N = 5SE +/- 0.02, N = 4SE +/- 0.03, N = 516.8212.9812.2216.23

Y-Cruncher

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgSeconds, Fewer Is BetterY-Cruncher 0.8.5Pi Digits To Calculate: 500MAVX-512 OnAVX-512 Off3691215SE +/- 0.002, N = 5SE +/- 0.008, N = 5SE +/- 0.009, N = 5SE +/- 0.007, N = 57.5709.0738.3957.696

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.

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.4Harness: IP Shapes 3D - Engine: CPUAVX-512 OnAVX-512 Off246810SE +/- 0.00113, N = 5SE +/- 0.00900, N = 5SE +/- 0.00179, N = 5SE +/- 0.00401, N = 53.075306.167216.602933.115081. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.4Harness: Deconvolution Batch shapes_3d - Engine: CPUAVX-512 OnAVX-512 Off0.6131.2261.8392.4523.065SE +/- 0.00309, N = 9SE +/- 0.01154, N = 9SE +/- 0.00474, N = 9SE +/- 0.00055, N = 91.363862.597612.724632.388301. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

CPU Temperature Monitor

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgCelsiusCPU Temperature MonitorPhoronix Test Suite System MonitoringAVX-512 OnAVX-512 Off20406080100Min: 40.5 / Avg: 73.15 / Max: 89.13Min: 39.5 / Avg: 75.07 / Max: 94.5Min: 37.25 / Avg: 83.51 / Max: 95.88Min: 37.63 / Avg: 80.57 / Max: 96.13

CPU Power Consumption Monitor

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgWattsCPU Power Consumption MonitorPhoronix Test Suite System MonitoringAVX-512 OnAVX-512 Off4080120160200Min: 22.78 / Avg: 148.64 / Max: 205.19Min: 13.82 / Avg: 152.26 / Max: 203.94Min: 11.34 / Avg: 172.33 / Max: 237.26Min: 10.68 / Avg: 169.29 / Max: 237.09

CPU Peak Freq (Highest CPU Core Frequency) Monitor

Ryzen 9 9950XRyzen 9 7950XOpenBenchmarking.orgMegahertzCPU Peak Freq (Highest CPU Core Frequency) MonitorPhoronix Test Suite System MonitoringAVX-512 OnAVX-512 Off10002000300040005000Min: 2477 / Avg: 5097.18 / Max: 5799Min: 600 / Avg: 4986.91 / Max: 5728Min: 545 / Avg: 4954.31 / Max: 5725Min: 545 / Avg: 5001.33 / Max: 5725

79 Results Shown

OpenVKL
LeelaChessZero:
  BLAS
  Eigen
XNNPACK:
  QU8MobileNetV3Large
  QU8MobileNetV2
TensorFlow
simdjson
OSPRay Studio
OSPRay
OSPRay Studio
ONNX Runtime:
  CaffeNet 12-int8 - CPU - Standard:
    Inference Time Cost (ms)
    Inferences Per Second
Mobile Neural Network
simdjson
NAMD
Numpy Benchmark
OSPRay Studio
simdjson
OSPRay Studio:
  3 - 4K - 1 - Path Tracer - CPU
  1 - 4K - 1 - Path Tracer - CPU
oneDNN:
  Recurrent Neural Network Training - CPU
  Recurrent Neural Network Inference - CPU
simdjson
OSPRay Studio
simdjson
GROMACS
OSPRay:
  gravity_spheres_volume/dim_512/scivis/real_time
  gravity_spheres_volume/dim_512/ao/real_time
OpenVINO:
  Face Detection FP16 - CPU:
    ms
    FPS
ONNX Runtime:
  fcn-resnet101-11 - CPU - Standard:
    Inference Time Cost (ms)
    Inferences Per Second
OpenVINO:
  Machine Translation EN To DE FP16 - CPU:
    ms
    FPS
  Person Detection FP16 - CPU:
    ms
    FPS
  Noise Suppression Poconet-Like FP16 - CPU:
    ms
    FPS
  Road Segmentation ADAS FP16-INT8 - CPU:
    ms
    FPS
ONNX Runtime:
  ArcFace ResNet-100 - CPU - Standard:
    Inference Time Cost (ms)
    Inferences Per Second
OpenVINO:
  Person Vehicle Bike Detection FP16 - CPU:
    ms
    FPS
  Person Re-Identification Retail FP16 - CPU:
    ms
    FPS
  Handwritten English Recognition FP16 - CPU:
    ms
    FPS
  Age Gender Recognition Retail 0013 FP16 - CPU:
    ms
    FPS
  Vehicle Detection FP16 - CPU:
    ms
    FPS
  Weld Porosity Detection FP16 - CPU:
    ms
    FPS
  Face Detection Retail FP16 - CPU:
    ms
    FPS
ONNX Runtime:
  ResNet50 v1-12-int8 - CPU - Standard:
    Inference Time Cost (ms)
    Inferences Per Second
  super-resolution-10 - CPU - Standard:
    Inference Time Cost (ms)
    Inferences Per Second
OSPRay
PyTorch
NAMD
Embree:
  Pathtracer ISPC - Asian Dragon Obj
  Pathtracer ISPC - Crown
oneDNN:
  IP Shapes 1D - CPU
  Deconvolution Batch shapes_1d - CPU
Embree
PyTorch
miniBUDE:
  OpenMP - BM1:
    Billion Interactions/s
    GFInst/s
Y-Cruncher
TensorFlow
Y-Cruncher
oneDNN:
  IP Shapes 3D - CPU
  Deconvolution Batch shapes_3d - CPU
CPU Temperature Monitor:
  Phoronix Test Suite System Monitoring:
    Celsius
    Watts
    Megahertz