8500g new

AMD Ryzen 5 8500G testing with a ASRock B650 Pro RS (2.08.AS01 BIOS) and AMD Phoenix2 512MB on Ubuntu 23.10 via the Phoronix Test Suite.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2403084-NE-8500GNEW648
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a
March 08
  1 Hour, 6 Minutes
b
March 08
  1 Hour, 6 Minutes
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  1 Hour, 6 Minutes
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8500g newOpenBenchmarking.orgPhoronix Test SuiteAMD Ryzen 5 8500G @ 5.08GHz (6 Cores / 12 Threads)ASRock B650 Pro RS (2.08.AS01 BIOS)AMD Device 14e82 x 16GB DRAM-6400MT/s F5-6400J3239G16GWestern Digital WD_BLACK SN850X 2000GBAMD Phoenix2 512MBAMD Rembrandt Radeon HD AudioMX279Realtek RTL8125 2.5GbEUbuntu 23.106.7.3-060703-generic (x86_64)GNOME Shell 45.2X Server + Wayland4.6 Mesa 24.1~git2402040600.8368a9~oibaf~m (git-8368a97 2024-02-04 mantic-oibaf-ppa) (LLVM 16.0.6 DRM 3.57)GCC 13.2.0ext41920x1080ProcessorMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelDesktopDisplay ServerOpenGLCompilerFile-SystemScreen Resolution8500g New BenchmarksSystem Logs- Transparent Huge Pages: madvise- --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-cet --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-link-serialization=2 --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-defaulted --enable-offload-targets=nvptx-none=/build/gcc-13-XYspKM/gcc-13-13.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-13-XYspKM/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-build-config=bootstrap-lto-lean --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -v - Scaling Governor: amd-pstate-epp powersave (EPP: balance_performance) - CPU Microcode: 0xa708004- BAR1 / Visible vRAM Size: 512 MB- Python 3.11.6- gather_data_sampling: Not affected + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: 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 + srbds: Not affected + tsx_async_abort: Not affected

a vs. b ComparisonPhoronix Test SuiteBaseline+11.9%+11.9%+23.8%+23.8%+35.7%+35.7%40.3%38.3%19.2%12.4%8.4%6.5%5.5%2.8%1920 x 1080 - FurMark Vulkan - 247.4%1920 x 1080 - FurMark OpenGL - Off1920 x 1080 - F.K.O - 21920 x 1080 - FurMark OpenGL - 131.2%1920 x 1080 - F.K.O - 126.8%11920 x 1080 - F.K.V - 21920 x 1080 - FurMark OpenGL - 21920 x 1080 - FurMark Vulkan - 17.6%1920 x 1080 - FurMark Vulkan - Off1920 x 1080 - F.K.O - Off6.4%1920 x 1080 - F.K.V - OffM.T.E.T.D.F - CPU3.9%M.T.E.T.D.F - CPU3.8%1920 x 1080 - F.K.V - 1H.E.R.F.I - CPU2.2%H.E.R.F.I - CPU2.2%FurMarkFurMarkFurMarkFurMarkFurMarkJPEG-XL Decoding libjxlFurMarkFurMarkFurMarkFurMarkFurMarkFurMarkOpenVINOOpenVINOFurMarkOpenVINOOpenVINOab

8500g newfurmark: 1920 x 1080 - FurMark Vulkan - 2furmark: 1920 x 1080 - FurMark OpenGL - Offfurmark: 1920 x 1080 - FurMark Knot OpenGL - 2furmark: 1920 x 1080 - FurMark OpenGL - 1furmark: 1920 x 1080 - FurMark Knot OpenGL - 1jpegxl-decode: 1furmark: 1920 x 1080 - Furmark Knot Vulkan - 2furmark: 1920 x 1080 - FurMark OpenGL - 2furmark: 1920 x 1080 - FurMark Vulkan - 1furmark: 1920 x 1080 - FurMark Vulkan - Offfurmark: 1920 x 1080 - FurMark Knot OpenGL - Offfurmark: 1920 x 1080 - Furmark Knot Vulkan - Offopenvino: Machine Translation EN To DE FP16 - CPUopenvino: Machine Translation EN To DE FP16 - CPUfurmark: 1920 x 1080 - Furmark Knot Vulkan - 1openvino: Handwritten English Recognition FP16-INT8 - CPUopenvino: Handwritten English Recognition FP16-INT8 - CPUopenvino: Person Detection FP32 - CPUopenvino: Person Detection FP32 - CPUjpegxl-decode: Allopenvino: Person Detection FP16 - CPUopenvino: Person Detection FP16 - CPUopenvino: Road Segmentation ADAS FP16 - CPUopenvino: Road Segmentation ADAS FP16 - CPUopenvino: Handwritten English Recognition FP16 - CPUopenvino: Handwritten English Recognition FP16 - CPUopenvino: Road Segmentation ADAS FP16-INT8 - CPUopenvino: Road Segmentation ADAS FP16-INT8 - CPUonednn: Convolution Batch Shapes Auto - CPUencode-wavpack: WAV To WavPackjpegxl: PNG - 80jpegxl: JPEG - 80openvino: Age Gender Recognition Retail 0013 FP16-INT8 - CPUjpegxl: PNG - 90openvino: Person Re-Identification Retail FP16 - CPUopenvino: Person Re-Identification Retail FP16 - CPUopenvino: Face Detection FP16-INT8 - CPUopenvino: Noise Suppression Poconet-Like FP16 - CPUjpegxl: PNG - 100onednn: Deconvolution Batch shapes_1d - CPUopenvino: Noise Suppression Poconet-Like FP16 - CPUopenvino: Vehicle Detection FP16-INT8 - CPUonednn: IP Shapes 3D - CPUopenvino: Vehicle Detection FP16 - CPUopenvino: Vehicle Detection FP16 - CPUopenvino: Face Detection FP16 - CPUopenvino: Face Detection Retail FP16 - CPUopenvino: Vehicle Detection FP16-INT8 - CPUopenvino: Person Vehicle Bike Detection FP16 - CPUjpegxl: JPEG - 90openvino: Face Detection FP16-INT8 - CPUopenvino: Weld Porosity Detection FP16 - CPUopenvino: Face Detection FP16 - CPUopenvino: Age Gender Recognition Retail 0013 FP16 - CPUopenvino: Weld Porosity Detection FP16 - CPUonednn: IP Shapes 1D - CPUopenvino: Face Detection Retail FP16 - CPUopenvino: Person Vehicle Bike Detection FP16 - CPUopenvino: Face Detection Retail FP16-INT8 - CPUonednn: Recurrent Neural Network Training - CPUonednn: Recurrent Neural Network Inference - CPUopenvino: Weld Porosity Detection FP16-INT8 - CPUonednn: Deconvolution Batch shapes_3d - CPUjpegxl: JPEG - 100v-ray: CPUopenvino: Age Gender Recognition Retail 0013 FP16-INT8 - CPUopenvino: Age Gender Recognition Retail 0013 FP16 - CPUopenvino: Weld Porosity Detection FP16-INT8 - CPUopenvino: Face Detection Retail FP16-INT8 - CPUab15.57213216.3428124.2844823.284836.58109860.5284.56171816.40780824.78666923.4159877.2253037.23768279.1450.57.736106243.1924.6536.7108.85314.2836.59109.17114.7634.8234.8425.5326.34151.598.383576.10626.12825.95516040.2924.2717.25548.717.5310.4310.2316.54831570.04458.794.2503714.74270.923.874.128.689.0824.479529.92398.221025.0711212.915.023.40944965.46439.051399.884083.292107.15780.327.4467510.207142060.360.517.664.2610.56238122.9217415.92643317.7446755.19110172.1225.12876417.7782523.03247824.9462076.792497.63826282.1948.637.95105237.8625.1937.4106.86319.94237.17107.47113.4235.21237.4625.2526.6150.118.30216.15826.34326.16115918.9624.0967.29546.17.5610.3910.276.52596571.9460.254.2375614.7271.633.864.118.669.124.524528.99398.871026.6311229.15153.41376966.6438.561398.934081.182106.08780.637.4452210.205142060.360.517.664.26OpenBenchmarking.org

FurMark

FurMark 2 is a cross-platform GPU stress test that can exercise both OpenGL and Vulkan drivers/GPUs. FurMark 2 is the successor to the original FurMark benchmark. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterFurMark 2.1Resolution: 1920 x 1080 - Demo: FurMark Vulkan - MSAA: 2ab4812162015.5710.56MIN: 15 / MAX: 20MAX: 16

OpenBenchmarking.orgFPS, More Is BetterFurMark 2.1Resolution: 1920 x 1080 - Demo: FurMark OpenGL - MSAA: Offba51015202522.9216.34MIN: 22.23 / MAX: 24MIN: 16 / MAX: 18

OpenBenchmarking.orgFPS, More Is BetterFurMark 2.1Resolution: 1920 x 1080 - Demo: FurMark Knot OpenGL - MSAA: 2ba1.33342.66684.00025.33366.6675.9264334.284480MAX: 8MAX: 6

OpenBenchmarking.orgFPS, More Is BetterFurMark 2.1Resolution: 1920 x 1080 - Demo: FurMark OpenGL - MSAA: 1ab61218243023.2817.74MIN: 22.67 / MAX: 24MIN: 17.54 / MAX: 19

OpenBenchmarking.orgFPS, More Is BetterFurMark 2.1Resolution: 1920 x 1080 - Demo: FurMark Knot OpenGL - MSAA: 1ab2468106.5810985.191101MAX: 8MAX: 7

JPEG-XL Decoding libjxl

The JPEG XL Image Coding System is designed to provide next-generation JPEG image capabilities with JPEG XL offering better image quality and compression over legacy JPEG. This test profile is suited for JPEG XL decode performance testing to PNG output file, the pts/jpexl test is for encode performance. The JPEG XL encoding/decoding is done using the libjxl codebase. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMP/s, More Is BetterJPEG-XL Decoding libjxl 0.10.1CPU Threads: 1ba163248648072.1260.53

FurMark

FurMark 2 is a cross-platform GPU stress test that can exercise both OpenGL and Vulkan drivers/GPUs. FurMark 2 is the successor to the original FurMark benchmark. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterFurMark 2.1Resolution: 1920 x 1080 - Demo: Furmark Knot Vulkan - MSAA: 2ba1.1542.3083.4624.6165.775.1287644.561718MIN: 5 / MAX: 11MAX: 11

OpenBenchmarking.orgFPS, More Is BetterFurMark 2.1Resolution: 1920 x 1080 - Demo: FurMark OpenGL - MSAA: 2ba4812162017.7816.41MIN: 17 / MAX: 19MIN: 16 / MAX: 18

OpenBenchmarking.orgFPS, More Is BetterFurMark 2.1Resolution: 1920 x 1080 - Demo: FurMark Vulkan - MSAA: 1ab61218243024.7923.03MIN: 24 / MAX: 29MIN: 23 / MAX: 27

OpenBenchmarking.orgFPS, More Is BetterFurMark 2.1Resolution: 1920 x 1080 - Demo: FurMark Vulkan - MSAA: Offba61218243024.9523.42MIN: 24 / MAX: 28MIN: 23 / MAX: 27

OpenBenchmarking.orgFPS, More Is BetterFurMark 2.1Resolution: 1920 x 1080 - Demo: FurMark Knot OpenGL - MSAA: Offab2468107.2253036.792490MAX: 9MAX: 8

OpenBenchmarking.orgFPS, More Is BetterFurMark 2.1Resolution: 1920 x 1080 - Demo: Furmark Knot Vulkan - MSAA: Offba2468107.6382627.237682MAX: 13MIN: 7 / MAX: 13

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 2024.0Model: Machine Translation EN To DE FP16 - Device: CPUab2040608010079.1482.19MIN: 63.93 / MAX: 90.29MIN: 42.67 / MAX: 91.371. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2024.0Model: Machine Translation EN To DE FP16 - Device: CPUab112233445550.5048.631. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

FurMark

FurMark 2 is a cross-platform GPU stress test that can exercise both OpenGL and Vulkan drivers/GPUs. FurMark 2 is the successor to the original FurMark benchmark. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterFurMark 2.1Resolution: 1920 x 1080 - Demo: Furmark Knot Vulkan - MSAA: 1ba2468107.9510507.736106MAX: 14MAX: 14

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 2024.0Model: Handwritten English Recognition FP16-INT8 - Device: CPUab50100150200250243.19237.861. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2024.0Model: Handwritten English Recognition FP16-INT8 - Device: CPUab61218243024.6525.19MIN: 18.37 / MAX: 32.84MIN: 20.95 / MAX: 33.741. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2024.0Model: Person Detection FP32 - Device: CPUba91827364537.436.71. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2024.0Model: Person Detection FP32 - Device: CPUba20406080100106.86108.85MIN: 87.6 / MAX: 115.86MIN: 88.85 / MAX: 116.371. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

JPEG-XL Decoding libjxl

The JPEG XL Image Coding System is designed to provide next-generation JPEG image capabilities with JPEG XL offering better image quality and compression over legacy JPEG. This test profile is suited for JPEG XL decode performance testing to PNG output file, the pts/jpexl test is for encode performance. The JPEG XL encoding/decoding is done using the libjxl codebase. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMP/s, More Is BetterJPEG-XL Decoding libjxl 0.10.1CPU Threads: Allba70140210280350319.94314.28

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 2024.0Model: Person Detection FP16 - Device: CPUba91827364537.1736.591. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2024.0Model: Person Detection FP16 - Device: CPUba20406080100107.47109.17MIN: 90.58 / MAX: 116.74MIN: 87.29 / MAX: 117.091. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2024.0Model: Road Segmentation ADAS FP16 - Device: CPUab306090120150114.76113.421. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2024.0Model: Road Segmentation ADAS FP16 - Device: CPUab81624324034.8035.21MIN: 26.66 / MAX: 46.51MIN: 28.97 / MAX: 41.771. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2024.0Model: Handwritten English Recognition FP16 - Device: CPUba50100150200250237.46234.841. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2024.0Model: Handwritten English Recognition FP16 - Device: CPUba61218243025.2525.53MIN: 19.74 / MAX: 34.59MIN: 19.67 / MAX: 36.371. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2024.0Model: Road Segmentation ADAS FP16-INT8 - Device: CPUab61218243026.3426.60MIN: 21.17 / MAX: 33.58MIN: 21.4 / MAX: 31.331. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2024.0Model: Road Segmentation ADAS FP16-INT8 - Device: CPUab306090120150151.59150.111. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

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 3.4Harness: Convolution Batch Shapes Auto - Engine: CPUba2468108.302108.38357MIN: 8.14MIN: 8.21. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

WavPack Audio Encoding

This test times how long it takes to encode a sample WAV file to WavPack format with very high quality settings. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterWavPack Audio Encoding 5.7WAV To WavPackab2468106.1066.158

JPEG-XL libjxl

The JPEG XL Image Coding System is designed to provide next-generation JPEG image capabilities with JPEG XL offering better image quality and compression over legacy JPEG. This test profile is currently focused on the multi-threaded JPEG XL image encode performance using the reference libjxl library. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMP/s, More Is BetterJPEG-XL libjxl 0.10.1Input: PNG - Quality: 80ba61218243026.3426.131. (CXX) g++ options: -fno-rtti -O3 -fPIE -pie -lm

OpenBenchmarking.orgMP/s, More Is BetterJPEG-XL libjxl 0.10.1Input: JPEG - Quality: 80ba61218243026.1625.961. (CXX) g++ options: -fno-rtti -O3 -fPIE -pie -lm

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 2024.0Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPUab3K6K9K12K15K16040.2915918.961. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

JPEG-XL libjxl

The JPEG XL Image Coding System is designed to provide next-generation JPEG image capabilities with JPEG XL offering better image quality and compression over legacy JPEG. This test profile is currently focused on the multi-threaded JPEG XL image encode performance using the reference libjxl library. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMP/s, More Is BetterJPEG-XL libjxl 0.10.1Input: PNG - Quality: 90ab61218243024.2724.101. (CXX) g++ options: -fno-rtti -O3 -fPIE -pie -lm

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 2024.0Model: Person Re-Identification Retail FP16 - Device: CPUab2468107.257.29MIN: 4.12 / MAX: 11.56MIN: 4.15 / MAX: 11.551. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2024.0Model: Person Re-Identification Retail FP16 - Device: CPUab120240360480600548.71546.101. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2024.0Model: Face Detection FP16-INT8 - Device: CPUba2468107.567.531. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2024.0Model: Noise Suppression Poconet-Like FP16 - Device: CPUba369121510.3910.43MIN: 6.59 / MAX: 17.79MIN: 6.63 / MAX: 16.511. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

JPEG-XL libjxl

The JPEG XL Image Coding System is designed to provide next-generation JPEG image capabilities with JPEG XL offering better image quality and compression over legacy JPEG. This test profile is currently focused on the multi-threaded JPEG XL image encode performance using the reference libjxl library. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMP/s, More Is BetterJPEG-XL libjxl 0.10.1Input: PNG - Quality: 100ba369121510.2710.231. (CXX) g++ options: -fno-rtti -O3 -fPIE -pie -lm

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 3.4Harness: Deconvolution Batch shapes_1d - Engine: CPUba2468106.525966.54831MIN: 6.35MIN: 6.351. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

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 2024.0Model: Noise Suppression Poconet-Like FP16 - Device: CPUba120240360480600571.90570.041. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2024.0Model: Vehicle Detection FP16-INT8 - Device: CPUba100200300400500460.25458.791. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

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 3.4Harness: IP Shapes 3D - Engine: CPUba0.95631.91262.86893.82524.78154.237564.25037MIN: 4.21MIN: 4.231. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

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 2024.0Model: Vehicle Detection FP16 - Device: CPUba4812162014.7014.74MIN: 11.7 / MAX: 22.43MIN: 11.4 / MAX: 19.481. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2024.0Model: Vehicle Detection FP16 - Device: CPUba60120180240300271.63270.921. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2024.0Model: Face Detection FP16 - Device: CPUab0.87081.74162.61243.48324.3543.873.861. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2024.0Model: Face Detection Retail FP16 - Device: CPUba0.9271.8542.7813.7084.6354.114.12MIN: 2.28 / MAX: 10.95MIN: 2.25 / MAX: 7.721. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2024.0Model: Vehicle Detection FP16-INT8 - Device: CPUba2468108.668.68MIN: 5.83 / MAX: 13.59MIN: 4.77 / MAX: 15.311. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2024.0Model: Person Vehicle Bike Detection FP16 - Device: CPUab36912159.089.10MIN: 5.42 / MAX: 12.5MIN: 5.33 / MAX: 15.251. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

JPEG-XL libjxl

The JPEG XL Image Coding System is designed to provide next-generation JPEG image capabilities with JPEG XL offering better image quality and compression over legacy JPEG. This test profile is currently focused on the multi-threaded JPEG XL image encode performance using the reference libjxl library. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMP/s, More Is BetterJPEG-XL libjxl 0.10.1Input: JPEG - Quality: 90ba61218243024.5224.481. (CXX) g++ options: -fno-rtti -O3 -fPIE -pie -lm

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 2024.0Model: Face Detection FP16-INT8 - Device: CPUba110220330440550528.99529.92MIN: 498.49 / MAX: 558.32MIN: 502.72 / MAX: 546.131. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2024.0Model: Weld Porosity Detection FP16 - Device: CPUba90180270360450398.87398.221. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2024.0Model: Face Detection FP16 - Device: CPUab20040060080010001025.071026.63MIN: 991.41 / MAX: 1094.87MIN: 996.76 / MAX: 1100.241. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2024.0Model: Age Gender Recognition Retail 0013 FP16 - Device: CPUba2K4K6K8K10K11229.1511212.901. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2024.0Model: Weld Porosity Detection FP16 - Device: CPUba4812162015.0015.02MIN: 7.99 / MAX: 22.67MIN: 8.04 / MAX: 25.211. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

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 3.4Harness: IP Shapes 1D - Engine: CPUab0.76811.53622.30433.07243.84053.409443.41376MIN: 3.34MIN: 3.341. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

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 2024.0Model: Face Detection Retail FP16 - Device: CPUba2004006008001000966.60965.461. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2024.0Model: Person Vehicle Bike Detection FP16 - Device: CPUab100200300400500439.05438.561. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2024.0Model: Face Detection Retail FP16-INT8 - Device: CPUab300600900120015001399.881398.931. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

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 3.4Harness: Recurrent Neural Network Training - Engine: CPUba90018002700360045004081.184083.29MIN: 4066.64MIN: 4068.071. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.4Harness: Recurrent Neural Network Inference - Engine: CPUba50010001500200025002106.082107.15MIN: 2093.86MIN: 2091.831. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

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 2024.0Model: Weld Porosity Detection FP16-INT8 - Device: CPUba2004006008001000780.63780.321. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

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 3.4Harness: Deconvolution Batch shapes_3d - Engine: CPUba2468107.445227.44675MIN: 7.42MIN: 7.421. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

JPEG-XL libjxl

The JPEG XL Image Coding System is designed to provide next-generation JPEG image capabilities with JPEG XL offering better image quality and compression over legacy JPEG. This test profile is currently focused on the multi-threaded JPEG XL image encode performance using the reference libjxl library. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMP/s, More Is BetterJPEG-XL libjxl 0.10.1Input: JPEG - Quality: 100ab369121510.2110.211. (CXX) g++ options: -fno-rtti -O3 -fPIE -pie -lm

Chaos Group V-RAY

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

OpenBenchmarking.orgvsamples, More Is BetterChaos Group V-RAY 6.0Mode: CPUba3K6K9K12K15K1420614206

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 2024.0Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPUab0.0810.1620.2430.3240.4050.360.36MIN: 0.21 / MAX: 4.41MIN: 0.21 / MAX: 4.351. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2024.0Model: Age Gender Recognition Retail 0013 FP16 - Device: CPUab0.11480.22960.34440.45920.5740.510.51MIN: 0.28 / MAX: 4.37MIN: 0.28 / MAX: 4.491. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2024.0Model: Weld Porosity Detection FP16-INT8 - Device: CPUab2468107.667.66MIN: 4.08 / MAX: 17.01MIN: 4.09 / MAX: 16.041. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2024.0Model: Face Detection Retail FP16-INT8 - Device: CPUab0.95851.9172.87553.8344.79254.264.26MIN: 2.54 / MAX: 8.59MIN: 2.53 / MAX: 13.951. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl

69 Results Shown

FurMark:
  1920 x 1080 - FurMark Vulkan - 2
  1920 x 1080 - FurMark OpenGL - Off
  1920 x 1080 - FurMark Knot OpenGL - 2
  1920 x 1080 - FurMark OpenGL - 1
  1920 x 1080 - FurMark Knot OpenGL - 1
JPEG-XL Decoding libjxl
FurMark:
  1920 x 1080 - Furmark Knot Vulkan - 2
  1920 x 1080 - FurMark OpenGL - 2
  1920 x 1080 - FurMark Vulkan - 1
  1920 x 1080 - FurMark Vulkan - Off
  1920 x 1080 - FurMark Knot OpenGL - Off
  1920 x 1080 - Furmark Knot Vulkan - Off
OpenVINO:
  Machine Translation EN To DE FP16 - CPU:
    ms
    FPS
FurMark
OpenVINO:
  Handwritten English Recognition FP16-INT8 - CPU:
    FPS
    ms
  Person Detection FP32 - CPU:
    FPS
    ms
JPEG-XL Decoding libjxl
OpenVINO:
  Person Detection FP16 - CPU:
    FPS
    ms
  Road Segmentation ADAS FP16 - CPU:
    FPS
    ms
  Handwritten English Recognition FP16 - CPU:
    FPS
    ms
  Road Segmentation ADAS FP16-INT8 - CPU:
    ms
    FPS
oneDNN
WavPack Audio Encoding
JPEG-XL libjxl:
  PNG - 80
  JPEG - 80
OpenVINO
JPEG-XL libjxl
OpenVINO:
  Person Re-Identification Retail FP16 - CPU:
    ms
    FPS
  Face Detection FP16-INT8 - CPU:
    FPS
  Noise Suppression Poconet-Like FP16 - CPU:
    ms
JPEG-XL libjxl
oneDNN
OpenVINO:
  Noise Suppression Poconet-Like FP16 - CPU
  Vehicle Detection FP16-INT8 - CPU
oneDNN
OpenVINO:
  Vehicle Detection FP16 - CPU:
    ms
    FPS
  Face Detection FP16 - CPU:
    FPS
  Face Detection Retail FP16 - CPU:
    ms
  Vehicle Detection FP16-INT8 - CPU:
    ms
  Person Vehicle Bike Detection FP16 - CPU:
    ms
JPEG-XL libjxl
OpenVINO:
  Face Detection FP16-INT8 - CPU
  Weld Porosity Detection FP16 - CPU
  Face Detection FP16 - CPU
  Age Gender Recognition Retail 0013 FP16 - CPU
  Weld Porosity Detection FP16 - CPU
oneDNN
OpenVINO:
  Face Detection Retail FP16 - CPU
  Person Vehicle Bike Detection FP16 - CPU
  Face Detection Retail FP16-INT8 - CPU
oneDNN:
  Recurrent Neural Network Training - CPU
  Recurrent Neural Network Inference - CPU
OpenVINO
oneDNN
JPEG-XL libjxl
Chaos Group V-RAY
OpenVINO:
  Age Gender Recognition Retail 0013 FP16-INT8 - CPU
  Age Gender Recognition Retail 0013 FP16 - CPU
  Weld Porosity Detection FP16-INT8 - CPU
  Face Detection Retail FP16-INT8 - CPU