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AMD Ryzen 5 5500U testing with a NB01 NL5xNU (1.07.11RTR1 BIOS) and AMD Lucienne 512MB on Tuxedo 22.04 via the Phoronix Test Suite.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2304095-NE-EAST8665701
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April 09 2023
  37 Minutes
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April 09 2023
  1 Hour, 46 Minutes
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April 09 2023
  2 Hours, 3 Minutes
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eastOpenBenchmarking.orgPhoronix Test SuiteAMD Ryzen 5 5500U @ 4.06GHz (6 Cores / 12 Threads)NB01 NL5xNU (1.07.11RTR1 BIOS)AMD Renoir/Cezanne16GBSamsung SSD 970 EVO Plus 500GBAMD Lucienne 512MB (1800/400MHz)AMD Renoir Radeon HD AudioRealtek RTL8111/8168/8411 + Intel Wi-Fi 6 AX200Tuxedo 22.046.0.0-1010-oem (x86_64)KDE Plasma 5.26.5X Server 1.21.1.34.6 Mesa 22.3.7 (LLVM 14.0.0 DRM 3.48)1.3.230GCC 11.3.0ext41920x1080ProcessorMotherboardChipsetMemoryDiskGraphicsAudioNetworkOSKernelDesktopDisplay ServerOpenGLVulkanCompilerFile-SystemScreen ResolutionEast 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,brig,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-targets=nvptx-none=/build/gcc-11-xKiWfi/gcc-11-11.3.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-11-xKiWfi/gcc-11-11.3.0/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 ondemand (Boost: Enabled) - CPU Microcode: 0x8608103 - itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Mitigation of untrained return thunk; SMT enabled with STIBP protection + 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 STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected

abcResult OverviewPhoronix Test Suite100%104%108%112%srsRAN ProjectoneDNNVVenCGeekbench

eastonednn: IP Shapes 3D - f32 - CPUsrsran: PUSCH Processor Benchmark, Throughput Totalsrsran: PUSCH Processor Benchmark, Throughput Threadonednn: IP Shapes 1D - f32 - CPUsrsran: Downlink Processor Benchmarkonednn: Deconvolution Batch shapes_1d - f32 - CPUvvenc: Bosphorus 4K - Fasteronednn: Convolution Batch Shapes Auto - f32 - CPUonednn: Recurrent Neural Network Inference - f32 - CPUgeekbench: GPU Vulkanonednn: Recurrent Neural Network Training - f32 - CPUgeekbench: CPU Multi Corevvenc: Bosphorus 4K - Fastvvenc: Bosphorus 1080p - Fastergeekbench: CPU Single Coreonednn: Deconvolution Batch shapes_3d - f32 - CPUvvenc: Bosphorus 1080p - Fastgeekbench: CPU Single Coregeekbench: CPU Single Coregeekbench: CPU Multi Coregeekbench: CPU Multi Coreabc9.5521844937.88.64121288.712.15324.91322.11953743.02151236217.6959602.29116.879148611.48587.768158014386956548412.4925554.646.09.31729304.712.28245.01622.46283790.98152766277.7359182.30716.811148911.52957.780158514396957542412.6810555.246.39.37628299.911.96035.00922.47233761.80152506218.4759452.30116.803149211.49567.7811576144969625461OpenBenchmarking.org

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 3.1Harness: IP Shapes 3D - Data Type: f32 - Engine: CPUcba3691215SE +/- 0.03982, N = 3SE +/- 0.02342, N = 312.6810012.492509.55218MIN: 12.07MIN: 11.73MIN: 91. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

srsRAN Project

OpenBenchmarking.orgMbps, More Is BettersrsRAN Project 23.3Test: PUSCH Processor Benchmark, Throughput Totalcba120240360480600SE +/- 0.65, N = 3SE +/- 2.61, N = 3555.2554.6449.0MIN: 402.1 / MAX: 1011.1MIN: 394.8 / MAX: 989.8MIN: 276.2 / MAX: 869.31. (CXX) g++ options: -O3 -fno-trapping-math -fno-math-errno -march=native -mfma -lgtest

OpenBenchmarking.orgMbps, More Is BettersrsRAN Project 23.3Test: PUSCH Processor Benchmark, Throughput Threadcba1020304050SE +/- 0.03, N = 3SE +/- 0.40, N = 346.346.037.8MIN: 33.5 / MAX: 83.7MIN: 33.5 / MAX: 82.9MIN: 23.7 / MAX: 74.11. (CXX) g++ options: -O3 -fno-trapping-math -fno-math-errno -march=native -mfma -lgtest

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 3.1Harness: IP Shapes 1D - Data Type: f32 - Engine: CPUcba3691215SE +/- 0.01855, N = 3SE +/- 0.02426, N = 39.376289.317298.64121MIN: 8.79MIN: 8.76MIN: 8.151. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

srsRAN Project

OpenBenchmarking.orgMbps, More Is BettersrsRAN Project 23.3Test: Downlink Processor Benchmarkcba70140210280350SE +/- 2.14, N = 15SE +/- 3.67, N = 4299.9304.7288.7MIN: 57.2 / MAX: 771.3MIN: 57.5 / MAX: 772.6MIN: 57.3 / MAX: 718.91. (CXX) g++ options: -O3 -fno-trapping-math -fno-math-errno -march=native -mfma -lgtest

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 3.1Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPUcba3691215SE +/- 0.03, N = 3SE +/- 0.01, N = 311.9612.2812.15MIN: 8.8MIN: 8.78MIN: 8.661. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

VVenC

VVenC is the Fraunhofer Versatile Video Encoder as a fast/efficient H.266/VVC encoder. The vvenc encoder makes use of SIMD Everywhere (SIMDe). The vvenc software is published under the Clear BSD License. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFrames Per Second, More Is BetterVVenC 1.8Video Input: Bosphorus 4K - Video Preset: Fastercba1.12862.25723.38584.51445.643SE +/- 0.004, N = 3SE +/- 0.004, N = 35.0095.0164.9131. (CXX) g++ options: -O3 -flto -fno-fat-lto-objects -flto=auto

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 3.1Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPUcba510152025SE +/- 0.01, N = 3SE +/- 0.02, N = 322.4722.4622.12MIN: 21.71MIN: 21.71MIN: 21.441. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.1Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPUcba8001600240032004000SE +/- 5.47, N = 3SE +/- 16.74, N = 33761.803790.983743.02MIN: 3666.82MIN: 3672.57MIN: 3650.521. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

Geekbench

OpenBenchmarking.orgScore, More Is BetterGeekbench 6Test: GPU Vulkancba3K6K9K12K15KSE +/- 31.48, N = 3SE +/- 54.34, N = 3152501527615123

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 3.1Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPUcba13002600390052006500SE +/- 20.47, N = 3SE +/- 42.29, N = 36218.476277.736217.69MIN: 6073.14MIN: 6091.01MIN: 6111.851. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

Geekbench

OpenBenchmarking.orgScore, More Is BetterGeekbench 6Test: CPU Multi Corecba13002600390052006500SE +/- 5.51, N = 3SE +/- 1.86, N = 3594559185960

VVenC

VVenC is the Fraunhofer Versatile Video Encoder as a fast/efficient H.266/VVC encoder. The vvenc encoder makes use of SIMD Everywhere (SIMDe). The vvenc software is published under the Clear BSD License. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFrames Per Second, More Is BetterVVenC 1.8Video Input: Bosphorus 4K - Video Preset: Fastcba0.51911.03821.55732.07642.5955SE +/- 0.006, N = 3SE +/- 0.006, N = 32.3012.3072.2911. (CXX) g++ options: -O3 -flto -fno-fat-lto-objects -flto=auto

OpenBenchmarking.orgFrames Per Second, More Is BetterVVenC 1.8Video Input: Bosphorus 1080p - Video Preset: Fastercba48121620SE +/- 0.01, N = 3SE +/- 0.05, N = 316.8016.8116.881. (CXX) g++ options: -O3 -flto -fno-fat-lto-objects -flto=auto

Geekbench

OpenBenchmarking.orgScore, More Is BetterGeekbench 6Test: CPU Single Corecba30060090012001500SE +/- 0.33, N = 3SE +/- 0.88, N = 3149214891486

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 3.1Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPUcba3691215SE +/- 0.02, N = 3SE +/- 0.02, N = 311.5011.5311.49MIN: 10.94MIN: 10.98MIN: 111. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

VVenC

VVenC is the Fraunhofer Versatile Video Encoder as a fast/efficient H.266/VVC encoder. The vvenc encoder makes use of SIMD Everywhere (SIMDe). The vvenc software is published under the Clear BSD License. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFrames Per Second, More Is BetterVVenC 1.8Video Input: Bosphorus 1080p - Video Preset: Fastcba246810SE +/- 0.008, N = 3SE +/- 0.003, N = 37.7817.7807.7681. (CXX) g++ options: -O3 -flto -fno-fat-lto-objects -flto=auto