onednn NVIDIA GH200

ARMv8 Neoverse-V2 testing with a Quanta Cloud QuantaGrid S74G-2U 1S7GZ9Z0000 S7G MB (CG1) (3A06 BIOS) and NVIDIA GH200 480GB 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 2403018-NE-ONEDNNNVI02
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onednn NVIDIA GH200OpenBenchmarking.orgPhoronix Test SuiteARMv8 Neoverse-V2 @ 3.39GHz (72 Cores)Quanta Cloud QuantaGrid S74G-2U 1S7GZ9Z0000 S7G MB (CG1) (3A06 BIOS)1 x 480GB DRAM-6400MT/s960GB SAMSUNG MZ1L2960HCJR-00A07 + 1920GB SAMSUNG MZTL21T9NVIDIA GH200 480GB2 x Mellanox MT2910 + 2 x QLogic FastLinQ QL41000 10/25/40/50GbEUbuntu 22.046.5.0-1007-NVIDIA-64k (aarch64)NVIDIAOpenCL 3.0 CUDA 12.4.891.3.277GCC 11.4.0 + CUDA 11.5ext41920x1200ProcessorMotherboardMemoryDiskGraphicsNetworkOSKernelDisplay DriverOpenCLVulkanCompilerFile-SystemScreen ResolutionOnednn NVIDIA GH200 BenchmarksSystem Logs- Transparent Huge Pages: madvise- --build=aarch64-linux-gnu --disable-libquadmath --disable-libquadmath-support --disable-werror --enable-bootstrap --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-fix-cortex-a53-843419 --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-nls --enable-objc-gc=auto --enable-plugin --enable-shared --enable-threads=posix --host=aarch64-linux-gnu --program-prefix=aarch64-linux-gnu- --target=aarch64-linux-gnu --with-build-config=bootstrap-lto-lean --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-target-system-zlib=auto -v - Scaling Governor: cppc_cpufreq performance (Boost: Disabled)- 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: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of __user pointer sanitization + spectre_v2: Not affected + srbds: Not affected + tsx_async_abort: Not affected

abcdResult OverviewPhoronix Test Suite100%100%101%101%102%oneDNNoneDNNoneDNNoneDNNoneDNNoneDNNoneDNNIP Shapes 1D - CPUR.N.N.T - CPUIP Shapes 3D - CPUC.B.S.A - CPUR.N.N.I - CPUD.B.s - CPUD.B.s - CPU

onednn NVIDIA GH200onednn: IP Shapes 1D - CPUonednn: IP Shapes 3D - CPUonednn: Convolution Batch Shapes Auto - CPUonednn: Deconvolution Batch shapes_1d - CPUonednn: Deconvolution Batch shapes_3d - CPUonednn: Recurrent Neural Network Training - CPUonednn: Recurrent Neural Network Inference - CPUabcd4.170931.836944.7131124.48116.431063583.012283.744.133261.838674.7217124.53276.438393584.682287.554.114561.829044.7064924.55546.440313574.732286.804.096901.830584.7107024.49256.440543602.942280.18OpenBenchmarking.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 3.4Harness: IP Shapes 1D - Engine: CPUabcd0.93851.8772.81553.7544.6925SE +/- 0.01783, N = 3SE +/- 0.03178, N = 3SE +/- 0.04283, N = 3SE +/- 0.03906, N = 34.170934.133264.114564.09690MIN: 3.77MIN: 3.73MIN: 3.68MIN: 3.71. (CXX) g++ options: -O3 -march=native -fopenmp -mcpu=generic -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.4Harness: IP Shapes 3D - Engine: CPUabcd0.41370.82741.24111.65482.0685SE +/- 0.00416, N = 3SE +/- 0.00422, N = 3SE +/- 0.00414, N = 3SE +/- 0.00258, N = 31.836941.838671.829041.83058MIN: 1.66MIN: 1.64MIN: 1.64MIN: 1.641. (CXX) g++ options: -O3 -march=native -fopenmp -mcpu=generic -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.4Harness: Convolution Batch Shapes Auto - Engine: CPUabcd1.06242.12483.18724.24965.312SE +/- 0.00174, N = 3SE +/- 0.00171, N = 3SE +/- 0.00401, N = 3SE +/- 0.00422, N = 34.713114.721714.706494.71070MIN: 4.62MIN: 4.6MIN: 4.6MIN: 4.591. (CXX) g++ options: -O3 -march=native -fopenmp -mcpu=generic -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.4Harness: Deconvolution Batch shapes_1d - Engine: CPUabcd612182430SE +/- 0.04, N = 3SE +/- 0.10, N = 3SE +/- 0.07, N = 3SE +/- 0.09, N = 324.4824.5324.5624.49MIN: 23.03MIN: 22.96MIN: 23.08MIN: 23.011. (CXX) g++ options: -O3 -march=native -fopenmp -mcpu=generic -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.4Harness: Deconvolution Batch shapes_3d - Engine: CPUabcd246810SE +/- 0.01147, N = 3SE +/- 0.00735, N = 3SE +/- 0.01150, N = 3SE +/- 0.01016, N = 36.431066.438396.440316.44054MIN: 6.14MIN: 6.13MIN: 6.17MIN: 6.151. (CXX) g++ options: -O3 -march=native -fopenmp -mcpu=generic -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.4Harness: Recurrent Neural Network Training - Engine: CPUabcd8001600240032004000SE +/- 8.84, N = 3SE +/- 5.09, N = 3SE +/- 31.12, N = 3SE +/- 12.76, N = 33583.013584.683574.733602.94MIN: 3531.56MIN: 3531.87MIN: 3486.97MIN: 3540.981. (CXX) g++ options: -O3 -march=native -fopenmp -mcpu=generic -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.4Harness: Recurrent Neural Network Inference - Engine: CPUabcd5001000150020002500SE +/- 5.70, N = 3SE +/- 8.97, N = 3SE +/- 4.93, N = 3SE +/- 3.22, N = 32283.742287.552286.802280.18MIN: 2232.84MIN: 2226.72MIN: 2234.59MIN: 2235.11. (CXX) g++ options: -O3 -march=native -fopenmp -mcpu=generic -fPIC -pie -ldl