tgl onnx onednn

Intel Core i7-1185G7 testing with a Dell 0DXP1F (3.4.0 BIOS) and Intel Xe TGL GT2 3GB on Ubuntu 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 2203319-PTS-TGLONNXO37
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March 30 2022
  37 Minutes
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March 30 2022
  3 Hours, 42 Minutes
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  3 Hours, 47 Minutes
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tgl onnx onednnOpenBenchmarking.orgPhoronix Test SuiteIntel Core i7-1185G7 @ 4.80GHz (4 Cores / 8 Threads)Dell 0DXP1F (3.4.0 BIOS)Intel Tiger Lake-LP16GBMicron 2300 NVMe 512GBIntel Xe TGL GT2 3GB (1350MHz)Realtek ALC289Intel Wi-Fi 6 AX201Ubuntu 22.045.17.0-051700rc7daily20220309-generic (x86_64)GNOME Shell 41.3X Server + Wayland4.6 Mesa 21.3.51.2.195GCC 11.2.0ext41920x1200ProcessorMotherboardChipsetMemoryDiskGraphicsAudioNetworkOSKernelDesktopDisplay ServerOpenGLVulkanCompilerFile-SystemScreen ResolutionTgl Onnx Onednn 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-XWYfV6/gcc-11-11.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-11-XWYfV6/gcc-11-11.2.0/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: intel_pstate powersave (EPP: balance_performance) - CPU Microcode: 0x9a - Thermald 2.4.7 - Python 3.10.2- itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: 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 IBRS plus Retpolines IBPB: conditional RSB filling + srbds: Not affected + tsx_async_abort: Not affected

ABCResult OverviewPhoronix Test Suite100%110%121%131%142%ONNX RuntimeONNX RuntimeONNX RuntimeONNX RuntimeoneDNNoneDNNoneDNNONNX RuntimeoneDNNoneDNNONNX RuntimeoneDNNoneDNNoneDNNoneDNNONNX RuntimeoneDNNoneDNNoneDNNoneDNNoneDNNONNX RuntimeoneDNNoneDNNONNX RuntimeoneDNNONNX RuntimeONNX RuntimeoneDNNONNX RuntimeoneDNNoneDNNoneDNNoneDNNoneDNNoneDNNsuper-resolution-10 - CPU - Standardbertsquad-12 - CPU - Standardfcn-resnet101-11 - CPU - Standardfcn-resnet101-11 - CPU - ParallelIP Shapes 1D - f32 - CPUD.B.s - u8s8f32 - CPUIP Shapes 1D - u8s8f32 - CPUArcFace ResNet-100 - CPU - ParallelC.B.S.A - f32 - CPUIP Shapes 1D - bf16bf16bf16 - CPUsuper-resolution-10 - CPU - ParallelIP Shapes 3D - bf16bf16bf16 - CPUC.B.S.A - u8s8f32 - CPUR.N.N.T - f32 - CPUD.B.s - f32 - CPUArcFace ResNet-100 - CPU - StandardD.B.s - f32 - CPUD.B.s - bf16bf16bf16 - CPUM.M.B.S.T - bf16bf16bf16 - CPUD.B.s - u8s8f32 - CPUIP Shapes 3D - f32 - CPUbertsquad-12 - CPU - ParallelIP Shapes 3D - u8s8f32 - CPUD.B.s - bf16bf16bf16 - CPUGPT-2 - CPU - ParallelM.M.B.S.T - u8s8f32 - CPUyolov4 - CPU - Parallelyolov4 - CPU - StandardR.N.N.I - bf16bf16bf16 - CPUGPT-2 - CPU - StandardR.N.N.T - u8s8f32 - CPUC.B.S.A - bf16bf16bf16 - CPUR.N.N.T - bf16bf16bf16 - CPUR.N.N.I - u8s8f32 - CPUM.M.B.S.T - f32 - CPUR.N.N.I - f32 - CPU

tgl onnx onednnonnx: fcn-resnet101-11 - CPU - Parallelonednn: IP Shapes 1D - u8s8f32 - CPUonnx: ArcFace ResNet-100 - CPU - Parallelonednn: Convolution Batch Shapes Auto - f32 - CPUonnx: super-resolution-10 - CPU - Parallelonednn: IP Shapes 3D - bf16bf16bf16 - CPUonednn: Convolution Batch Shapes Auto - u8s8f32 - CPUonnx: ArcFace ResNet-100 - CPU - Standardonednn: Deconvolution Batch shapes_3d - u8s8f32 - CPUonednn: IP Shapes 3D - f32 - CPUonednn: IP Shapes 3D - u8s8f32 - CPUonnx: GPT-2 - CPU - Parallelonednn: Matrix Multiply Batch Shapes Transformer - u8s8f32 - CPUonnx: yolov4 - CPU - Parallelonnx: yolov4 - CPU - Standardonednn: Recurrent Neural Network Inference - bf16bf16bf16 - CPUonnx: GPT-2 - CPU - Standardonednn: Recurrent Neural Network Training - u8s8f32 - CPUonednn: Convolution Batch Shapes Auto - bf16bf16bf16 - CPUonednn: Recurrent Neural Network Training - bf16bf16bf16 - CPUonednn: Recurrent Neural Network Inference - u8s8f32 - CPUonednn: Matrix Multiply Batch Shapes Transformer - f32 - CPUonednn: Recurrent Neural Network Inference - f32 - CPUonnx: super-resolution-10 - CPU - Standardonnx: fcn-resnet101-11 - CPU - Standardonnx: bertsquad-12 - CPU - Standardonnx: bertsquad-12 - CPU - Parallelonednn: Matrix Multiply Batch Shapes Transformer - bf16bf16bf16 - CPUonednn: Deconvolution Batch shapes_3d - bf16bf16bf16 - CPUonednn: Deconvolution Batch shapes_1d - bf16bf16bf16 - CPUonednn: Recurrent Neural Network Training - f32 - CPUonednn: Deconvolution Batch shapes_1d - u8s8f32 - CPUonednn: Deconvolution Batch shapes_3d - f32 - CPUonednn: Deconvolution Batch shapes_1d - f32 - CPUonednn: IP Shapes 1D - bf16bf16bf16 - CPUonednn: IP Shapes 1D - f32 - CPUABC331.608335508.759918796.319547.853657612.426555.926862.457644661.43081812623702.763887183.1650.92737180.813703.273.201343708.3124884036922210.805241.625858.20557179.622.066179.9956416.252524.3486.73638321.9170655410.1732118886.487288.682957782.467365.983012.4432345131.433711822613708.5263767189.3350.94997188.553706.433.202913706.0122083737222710.792638.946758.44897833.652.4672010.8197716.147722.59228.20647251.6143746510.2447816467.074778.722727212.520916.120002.4980944701.425321822613711.7863737195.1050.89097189.063702.643.204183708.6217563027822110.2889739.252257.26397177.772.4123510.585015.062020.84917.33232OpenBenchmarking.org

ONNX Runtime

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

OpenBenchmarking.orgInferences Per Minute, More Is BetterONNX Runtime 1.11Model: fcn-resnet101-11 - Device: CPU - Executor: ParallelABC816243240SE +/- 0.17, N = 3SE +/- 0.29, N = 123332251. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto -fno-fat-lto-objects -ldl -lrt

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 Intel oneAPI. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.6Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPUACB0.43130.86261.29391.72522.1565SE +/- 0.02179, N = 3SE +/- 0.02467, N = 151.608331.614371.91706MIN: 1.43MIN: 1.36MIN: 1.391. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -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 Zoo. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgInferences Per Minute, More Is BetterONNX Runtime 1.11Model: ArcFace ResNet-100 - Device: CPU - Executor: ParallelBAC120240360480600SE +/- 1.86, N = 3SE +/- 3.82, N = 35545504651. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto -fno-fat-lto-objects -ldl -lrt

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 Intel oneAPI. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.6Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPUABC3691215SE +/- 0.14982, N = 13SE +/- 0.08939, N = 148.7599010.1732110.24478MIN: 8.17MIN: 8.18MIN: 8.191. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -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 Zoo. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgInferences Per Minute, More Is BetterONNX Runtime 1.11Model: super-resolution-10 - Device: CPU - Executor: ParallelBAC400800120016002000SE +/- 8.61, N = 3SE +/- 3.28, N = 31888187916461. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto -fno-fat-lto-objects -ldl -lrt

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 Intel oneAPI. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.6Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPUABC246810SE +/- 0.06647, N = 5SE +/- 0.05421, N = 36.319546.487287.07477MIN: 5.74MIN: 5.73MIN: 5.921. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.6Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPUABC246810SE +/- 0.08839, N = 15SE +/- 0.08702, N = 157.853658.682958.72272MIN: 7.67MIN: 7.61MIN: 7.71. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -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 Zoo. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgInferences Per Minute, More Is BetterONNX Runtime 1.11Model: ArcFace ResNet-100 - Device: CPU - Executor: StandardBAC2004006008001000SE +/- 0.17, N = 3SE +/- 5.85, N = 37787617211. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto -fno-fat-lto-objects -ldl -lrt

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 Intel oneAPI. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.6Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPUABC0.56721.13441.70162.26882.836SE +/- 0.02316, N = 15SE +/- 0.03720, N = 152.426552.467362.52091MIN: 2.2MIN: 2.2MIN: 2.21. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.6Harness: IP Shapes 3D - Data Type: f32 - Engine: CPUABC246810SE +/- 0.00832, N = 3SE +/- 0.02249, N = 35.926865.983016.12000MIN: 5.65MIN: 5.68MIN: 5.861. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.6Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPUBAC0.56211.12421.68632.24842.8105SE +/- 0.00609, N = 3SE +/- 0.01292, N = 32.443232.457602.49809MIN: 2.34MIN: 2.34MIN: 2.311. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -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 Zoo. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgInferences Per Minute, More Is BetterONNX Runtime 1.11Model: GPT-2 - Device: CPU - Executor: ParallelBCA10002000300040005000SE +/- 37.78, N = 12SE +/- 27.09, N = 34513447044661. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto -fno-fat-lto-objects -ldl -lrt

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 Intel oneAPI. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.6Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPUCAB0.32260.64520.96781.29041.613SE +/- 0.00427, N = 3SE +/- 0.00013, N = 31.425321.430801.43371MIN: 1.37MIN: 1.38MIN: 1.381. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -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 Zoo. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgInferences Per Minute, More Is BetterONNX Runtime 1.11Model: yolov4 - Device: CPU - Executor: ParallelCBA4080120160200SE +/- 1.32, N = 3SE +/- 1.64, N = 31821821811. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Minute, More Is BetterONNX Runtime 1.11Model: yolov4 - Device: CPU - Executor: StandardACB60120180240300SE +/- 0.17, N = 3SE +/- 0.17, N = 32622612611. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto -fno-fat-lto-objects -ldl -lrt

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 Intel oneAPI. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.6Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPUABC8001600240032004000SE +/- 1.76, N = 3SE +/- 1.69, N = 33702.703708.523711.78MIN: 3669.11MIN: 3671.55MIN: 3673.421. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -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 Zoo. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgInferences Per Minute, More Is BetterONNX Runtime 1.11Model: GPT-2 - Device: CPU - Executor: StandardABC14002800420056007000SE +/- 1.36, N = 3SE +/- 4.16, N = 36388637663731. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto -fno-fat-lto-objects -ldl -lrt

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 Intel oneAPI. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.6Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPUABC15003000450060007500SE +/- 1.53, N = 3SE +/- 5.73, N = 37183.167189.337195.10MIN: 7143.58MIN: 7134.86MIN: 7136.261. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.6Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPUCAB1122334455SE +/- 0.08, N = 3SE +/- 0.02, N = 350.8950.9350.95MIN: 47.81MIN: 50.57MIN: 50.571. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.6Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPUABC15003000450060007500SE +/- 2.56, N = 3SE +/- 7.40, N = 37180.817188.557189.06MIN: 7130.5MIN: 7142.75MIN: 7132.271. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.6Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPUCAB8001600240032004000SE +/- 8.92, N = 3SE +/- 1.82, N = 33702.643703.273706.43MIN: 3646.09MIN: 3664.66MIN: 3672.11. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.6Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPUABC0.72091.44182.16272.88363.6045SE +/- 0.00447, N = 3SE +/- 0.00537, N = 33.201343.202913.20418MIN: 3.11MIN: 3.11MIN: 3.11. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.6Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPUBAC8001600240032004000SE +/- 0.73, N = 3SE +/- 0.71, N = 33706.013708.313708.62MIN: 3668.11MIN: 3667.77MIN: 3673.451. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -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 Zoo. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgInferences Per Minute, More Is BetterONNX Runtime 1.11Model: super-resolution-10 - Device: CPU - Executor: StandardABC5001000150020002500SE +/- 121.56, N = 12SE +/- 78.17, N = 122488220817561. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Minute, More Is BetterONNX Runtime 1.11Model: fcn-resnet101-11 - Device: CPU - Executor: StandardABC918273645SE +/- 1.89, N = 10SE +/- 2.14, N = 124037301. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Minute, More Is BetterONNX Runtime 1.11Model: bertsquad-12 - Device: CPU - Executor: StandardBAC80160240320400SE +/- 0.17, N = 3SE +/- 19.85, N = 123723692781. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Minute, More Is BetterONNX Runtime 1.11Model: bertsquad-12 - Device: CPU - Executor: ParallelBAC50100150200250SE +/- 5.99, N = 12SE +/- 4.21, N = 122272222211. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto -fno-fat-lto-objects -ldl -lrt

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 Intel oneAPI. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.6Harness: Matrix Multiply Batch Shapes Transformer - Data Type: bf16bf16bf16 - Engine: CPUCBA3691215SE +/- 0.23, N = 15SE +/- 0.03, N = 310.2910.7910.81MIN: 7.37MIN: 10.35MIN: 10.41. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.6Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPUBCA918273645SE +/- 1.01, N = 12SE +/- 0.94, N = 1538.9539.2541.63MIN: 35.45MIN: 35.42MIN: 35.451. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.6Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPUCAB1326395265SE +/- 0.89, N = 15SE +/- 0.71, N = 357.2658.2158.45MIN: 46.22MIN: 55.58MIN: 55.571. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.6Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPUCAB2K4K6K8K10KSE +/- 12.61, N = 3SE +/- 462.12, N = 157177.777179.627833.65MIN: 7109.7MIN: 7126.95MIN: 7123.391. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.6Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPUACB0.55511.11021.66532.22042.7755SE +/- 0.05576, N = 15SE +/- 0.04201, N = 152.066172.412352.46720MIN: 1.84MIN: 1.84MIN: 1.921. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.6Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPUACB3691215SE +/- 0.19882, N = 15SE +/- 0.21609, N = 159.9956410.5850010.81977MIN: 9.67MIN: 9.56MIN: 9.581. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.6Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPUCBA48121620SE +/- 0.35, N = 15SE +/- 0.38, N = 1515.0616.1516.25MIN: 11.2MIN: 11.65MIN: 13.21. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.6Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPUCBA612182430SE +/- 0.79, N = 15SE +/- 0.77, N = 1520.8522.5924.35MIN: 17.06MIN: 17.03MIN: 23.811. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 2.6Harness: IP Shapes 1D - Data Type: f32 - Engine: CPUACB246810SE +/- 0.18274, N = 12SE +/- 0.29521, N = 126.736387.332328.20647MIN: 6.11MIN: 5.99MIN: 5.821. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -std=c++11 -pie -ldl