Xeon Max AMX HBM2e

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EPYC 9654 2P
June 28 2023
  6 Hours, 59 Minutes
EPYC 9554 2P
June 28 2023
  5 Hours, 42 Minutes
Xeon Max 9480 2P, HBM Caching
June 29 2023
  13 Hours, 47 Minutes
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  8 Hours, 49 Minutes

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Xeon Max AMX HBM2eProcessorMotherboardChipsetMemoryDiskGraphicsMonitorNetworkOSKernelDesktopDisplay ServerCompilerFile-SystemScreen ResolutionEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching2 x AMD EPYC 9654 96-Core @ 2.40GHz (192 Cores / 384 Threads)AMD Titanite_4G (RTI1007B BIOS)AMD Device 14a41520GB7682GB INTEL SSDPF2KX076TZASPEEDVGA HDMIBroadcom NetXtreme BCM5720 PCIeUbuntu 23.046.2.0-20-generic (x86_64)GNOME Shell 44.0X Server 1.21.1.7GCC 12.2.0ext41920x10802 x AMD EPYC 9554 64-Core @ 3.10GHz (128 Cores / 256 Threads)2 x Intel Xeon Max 9480 @ 3.50GHz (112 Cores / 224 Threads)Supermicro X13DEM v1.10 (1.3 BIOS)Intel Device 1bce512GBVE2282 x Broadcom BCM57508 NetXtreme-E 10Gb/25Gb/40Gb/50Gb/100Gb/200GbOpenBenchmarking.orgKernel Details- Transparent Huge Pages: madviseCompiler Details- --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-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-12-Pa930Z/gcc-12-12.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-12-Pa930Z/gcc-12-12.2.0/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 Processor Details- EPYC 9654 2P: Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0xa101121- EPYC 9554 2P: Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0xa101121- Xeon Max 9480 2P, HBM Caching: Scaling Governor: intel_cpufreq performance - CPU Microcode: 0x2c0001d1Python Details- Python 3.11.2Security Details- EPYC 9654 2P: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: 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 Retpolines IBPB: conditional IBRS_FW STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected - EPYC 9554 2P: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: 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 Retpolines IBPB: conditional IBRS_FW STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected - Xeon Max 9480 2P, HBM Caching: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: 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 IBPB: conditional RSB filling PBRSB-eIBRS: SW sequence + srbds: Not affected + tsx_async_abort: Not affected

EPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM CachingResult OverviewPhoronix Test Suite100%171%242%313%384%oneDNNlibxsmmTensorFlowONNX RuntimeOpenVINO

EPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM CachingPer Watt Result OverviewPhoronix Test Suite100%168%236%303%libxsmmTensorFlowTensorFlowTensorFlowTensorFlowTensorFlowTensorFlowTensorFlowTensorFlow128CPU - 16 - VGG-16CPU - 16 - AlexNetCPU - 512 - VGG-16CPU - 512 - AlexNetCPU - 16 - GoogLeNetCPU - 16 - ResNet-50CPU - 512 - GoogLeNetCPU - 512 - ResNet-50

Xeon Max AMX HBM2elibxsmm: 128libxsmm: 256libxsmm: 32libxsmm: 64onednn: IP Shapes 1D - bf16bf16bf16 - CPUonednn: IP Shapes 3D - bf16bf16bf16 - CPUonednn: Convolution Batch Shapes Auto - bf16bf16bf16 - CPUonednn: Deconvolution Batch shapes_1d - bf16bf16bf16 - CPUonednn: Deconvolution Batch shapes_3d - bf16bf16bf16 - CPUonednn: Recurrent Neural Network Training - bf16bf16bf16 - CPUonednn: Recurrent Neural Network Inference - bf16bf16bf16 - CPUtensorflow: CPU - 16 - VGG-16tensorflow: CPU - 16 - AlexNettensorflow: CPU - 512 - VGG-16tensorflow: CPU - 512 - AlexNettensorflow: CPU - 16 - GoogLeNettensorflow: CPU - 16 - ResNet-50tensorflow: CPU - 512 - GoogLeNettensorflow: CPU - 512 - ResNet-50openvino: Face Detection FP16 - CPUopenvino: Face Detection FP16 - CPUopenvino: Person Detection FP16 - CPUopenvino: Person Detection FP16 - CPUopenvino: Person Detection FP32 - CPUopenvino: Person Detection FP32 - CPUopenvino: Vehicle Detection FP16 - CPUopenvino: Vehicle Detection FP16 - CPUopenvino: Face Detection FP16-INT8 - CPUopenvino: Face Detection FP16-INT8 - CPUopenvino: Vehicle Detection FP16-INT8 - CPUopenvino: Vehicle Detection FP16-INT8 - CPUopenvino: Weld Porosity Detection FP16 - CPUopenvino: Weld Porosity Detection FP16 - CPUopenvino: Machine Translation EN To DE FP16 - CPUopenvino: Machine Translation EN To DE FP16 - CPUopenvino: Weld Porosity Detection FP16-INT8 - CPUopenvino: Weld Porosity Detection FP16-INT8 - CPUopenvino: Person Vehicle Bike Detection FP16 - CPUopenvino: Person Vehicle Bike Detection FP16 - CPUopenvino: Age Gender Recognition Retail 0013 FP16 - CPUopenvino: Age Gender Recognition Retail 0013 FP16 - CPUopenvino: Age Gender Recognition Retail 0013 FP16-INT8 - CPUopenvino: Age Gender Recognition Retail 0013 FP16-INT8 - CPUonnx: GPT-2 - CPU - Standardonnx: GPT-2 - CPU - Standardonnx: yolov4 - CPU - Standardonnx: yolov4 - CPU - Standardonnx: bertsquad-12 - CPU - Standardonnx: bertsquad-12 - CPU - Standardonnx: CaffeNet 12-int8 - CPU - Standardonnx: CaffeNet 12-int8 - CPU - Standardonnx: fcn-resnet101-11 - CPU - Standardonnx: fcn-resnet101-11 - CPU - Standardonnx: ArcFace ResNet-100 - CPU - Standardonnx: ArcFace ResNet-100 - CPU - Standardonnx: ResNet50 v1-12-int8 - CPU - Standardonnx: ResNet50 v1-12-int8 - CPU - StandardEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching3426.14379.61298.02270.216.98233.802090.4610532.533260.7321002492.692790.9047.27166.20120.621757.1664.4925.25535.52171.56101.56471.8243.641092.9743.401098.967390.976.49191.41250.3910985.174.369843.034.86950.9450.4219170.619.959133.225.25146867.480.55124618.320.99103.1849.689044.90033204.09110.1794498.9957435.1942.306114.69797212.86319.308451.7898146.5556.870534112.94603.31402.22692.711.196692.205960.3113781.761620.4572721305.66925.76760.31257.94109.891813.6894.4133.40593.20188.1782.04389.5338.24832.0238.53825.525981.575.34155.28205.719010.453.548039.573.97786.0140.6715659.328.097447.604.29162207.970.52128593.240.88132.7217.647355.10505195.89911.687185.9009495.2402.019494.65982214.60624.012241.6445152.4396.559891814.37.8801691.98143.673560.4830753.5352515294.61325.4521.09230.1130.19718.5498.4340.15236.4476.93120.40232.0133.40834.9733.97819.762315.1212.07334.89333.515528.0320.2316941.996.44590.9247.2930938.503.476265.7717.83108515.120.4459457.141.40218.6924.708497.70046130.37011.457687.7638562.2181.782965.33514191.62323.772942.1801125.2848.02166OpenBenchmarking.org

libxsmm

Libxsmm is an open-source library for specialized dense and sparse matrix operations and deep learning primitives. Libxsmm supports making use of Intel AMX, AVX-512, and other modern CPU instruction set capabilities. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGFLOPS/s, More Is Betterlibxsmm 2-1.17-3645M N K: 128EPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching9001800270036004500SE +/- 29.11, N = 3SE +/- 21.03, N = 3SE +/- 22.78, N = 93426.14112.91814.31. (CXX) g++ options: -dynamic -Bstatic -static-libgcc -lgomp -lm -lrt -ldl -lquadmath -lstdc++ -pthread -fPIC -std=c++14 -O2 -fopenmp-simd -funroll-loops -ftree-vectorize -fdata-sections -ffunction-sections -fvisibility=hidden -msse4.2

OpenBenchmarking.orgGFLOPS/s, More Is Betterlibxsmm 2-1.17-3645M N K: 256EPYC 9654 2PEPYC 9554 2P10002000300040005000SE +/- 47.44, N = 5SE +/- 34.70, N = 34379.64603.31. (CXX) g++ options: -dynamic -Bstatic -static-libgcc -lgomp -lm -lrt -ldl -lquadmath -lstdc++ -pthread -fPIC -std=c++14 -O2 -fopenmp-simd -funroll-loops -ftree-vectorize -fdata-sections -ffunction-sections -fvisibility=hidden -msse4.2

OpenBenchmarking.orgGFLOPS/s, More Is Betterlibxsmm 2-1.17-3645M N K: 32EPYC 9654 2PEPYC 9554 2P30060090012001500SE +/- 9.98, N = 15SE +/- 4.06, N = 81298.01402.21. (CXX) g++ options: -dynamic -Bstatic -static-libgcc -lgomp -lm -lrt -ldl -lquadmath -lstdc++ -pthread -fPIC -std=c++14 -O2 -fopenmp-simd -funroll-loops -ftree-vectorize -fdata-sections -ffunction-sections -fvisibility=hidden -msse4.2

OpenBenchmarking.orgGFLOPS/s, More Is Betterlibxsmm 2-1.17-3645M N K: 64EPYC 9654 2PEPYC 9554 2P6001200180024003000SE +/- 33.30, N = 15SE +/- 5.63, N = 72270.22692.71. (CXX) g++ options: -dynamic -Bstatic -static-libgcc -lgomp -lm -lrt -ldl -lquadmath -lstdc++ -pthread -fPIC -std=c++14 -O2 -fopenmp-simd -funroll-loops -ftree-vectorize -fdata-sections -ffunction-sections -fvisibility=hidden -msse4.2

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: bf16bf16bf16 - Engine: CPUEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching48121620SE +/- 0.81790, N = 15SE +/- 0.95058, N = 12SE +/- 0.22497, N = 1516.9823011.196697.88016MIN: 8.09MIN: 5.64MIN: 4.451. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.1Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPUEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching20406080100SE +/- 0.03459, N = 15SE +/- 0.02374, N = 15SE +/- 0.61972, N = 53.802092.2059691.98140MIN: 79.161. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.1Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPUEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching0.82661.65322.47983.30644.133SE +/- 0.003345, N = 15SE +/- 0.002531, N = 7SE +/- 0.025287, N = 70.4610530.3113783.673560MIN: 3.031. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.1Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPUEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching0.571.141.712.282.85SE +/- 0.004515, N = 3SE +/- 0.003878, N = 3SE +/- 0.009112, N = 152.5332601.7616200.483075MIN: 1.7MIN: 1.591. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.1Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPUEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching0.79541.59082.38623.18163.977SE +/- 0.004782, N = 9SE +/- 0.002054, N = 9SE +/- 0.029518, N = 150.7321000.4572723.535250MIN: 2.461. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.1Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPUEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching3K6K9K12K15KSE +/- 18.00, N = 3SE +/- 13.50, N = 5SE +/- 507.18, N = 102492.691305.6615294.60MIN: 7750.751. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.1Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPUEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching6001200180024003000SE +/- 29.80, N = 15SE +/- 2.71, N = 3SE +/- 20.64, N = 122790.90925.771325.45MIN: 2391.98MIN: 909.67MIN: 1025.181. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread

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.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: VGG-16EPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching1326395265SE +/- 0.39, N = 3SE +/- 0.59, N = 3SE +/- 0.61, N = 1547.2760.3121.09

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: AlexNetEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching60120180240300SE +/- 2.70, N = 15SE +/- 3.19, N = 15SE +/- 1.10, N = 5166.20257.94230.11

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 512 - Model: VGG-16EPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching306090120150SE +/- 0.08, N = 3SE +/- 1.46, N = 3SE +/- 0.33, N = 5120.62109.8930.19

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 512 - Model: AlexNetEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching400800120016002000SE +/- 16.13, N = 7SE +/- 12.94, N = 3SE +/- 9.04, N = 31757.161813.68718.54

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: GoogLeNetEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching20406080100SE +/- 1.21, N = 15SE +/- 0.91, N = 15SE +/- 0.98, N = 364.4994.4198.43

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: ResNet-50EPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching918273645SE +/- 0.31, N = 3SE +/- 0.23, N = 3SE +/- 0.32, N = 325.2533.4040.15

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 512 - Model: GoogLeNetEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching130260390520650SE +/- 0.69, N = 3SE +/- 0.96, N = 3SE +/- 1.79, N = 3535.52593.20236.44

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 512 - Model: ResNet-50EPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching4080120160200SE +/- 0.26, N = 3SE +/- 0.70, N = 3SE +/- 0.66, N = 3171.56188.1776.93

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 2022.3Model: Face Detection FP16 - Device: CPUEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching306090120150SE +/- 0.25, N = 3SE +/- 0.04, N = 3SE +/- 0.41, N = 3101.5682.04120.401. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Face Detection FP16 - Device: CPUEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching100200300400500SE +/- 0.93, N = 3SE +/- 0.19, N = 3SE +/- 0.80, N = 3471.82389.53232.01MIN: 431.51 / MAX: 569.3MIN: 380.82 / MAX: 432.57MIN: 138.61 / MAX: 770.451. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Person Detection FP16 - Device: CPUEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching1020304050SE +/- 0.21, N = 3SE +/- 0.23, N = 3SE +/- 0.24, N = 343.6438.2433.401. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Person Detection FP16 - Device: CPUEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching2004006008001000SE +/- 5.11, N = 3SE +/- 5.30, N = 3SE +/- 6.17, N = 31092.97832.02834.97MIN: 825.28 / MAX: 1814.82MIN: 743.95 / MAX: 1258.17MIN: 558.93 / MAX: 2258.391. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Person Detection FP32 - Device: CPUEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching1020304050SE +/- 0.20, N = 3SE +/- 0.04, N = 3SE +/- 0.31, N = 343.4038.5333.971. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Person Detection FP32 - Device: CPUEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching2004006008001000SE +/- 5.33, N = 3SE +/- 1.07, N = 3SE +/- 7.20, N = 31098.96825.52819.76MIN: 825.62 / MAX: 1835.76MIN: 747.05 / MAX: 1238.39MIN: 516.88 / MAX: 2598.391. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Vehicle Detection FP16 - Device: CPUEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching16003200480064008000SE +/- 2.12, N = 3SE +/- 3.49, N = 3SE +/- 17.29, N = 137390.975981.572315.121. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Vehicle Detection FP16 - Device: CPUEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching3691215SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.08, N = 136.495.3412.07MIN: 5.03 / MAX: 55.65MIN: 4.89 / MAX: 34.7MIN: 7.38 / MAX: 250.921. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Face Detection FP16-INT8 - Device: CPUEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching70140210280350SE +/- 0.06, N = 3SE +/- 0.14, N = 3SE +/- 0.45, N = 3191.41155.28334.891. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Face Detection FP16-INT8 - Device: CPUEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching70140210280350SE +/- 0.04, N = 3SE +/- 0.22, N = 3SE +/- 0.44, N = 3250.39205.71333.51MIN: 222.36 / MAX: 303.72MIN: 202.38 / MAX: 252.14MIN: 285.32 / MAX: 516.281. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Vehicle Detection FP16-INT8 - Device: CPUEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching2K4K6K8K10KSE +/- 0.53, N = 3SE +/- 2.20, N = 3SE +/- 25.18, N = 310985.179010.455528.031. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Vehicle Detection FP16-INT8 - Device: CPUEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching510152025SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.09, N = 34.363.5420.23MIN: 3.52 / MAX: 38.49MIN: 3.45 / MAX: 21.7MIN: 12.69 / MAX: 166.761. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Weld Porosity Detection FP16 - Device: CPUEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching4K8K12K16K20KSE +/- 2.32, N = 3SE +/- 1.22, N = 3SE +/- 13.63, N = 39843.038039.5716941.991. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Weld Porosity Detection FP16 - Device: CPUEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching246810SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 34.863.976.44MIN: 4.02 / MAX: 36.01MIN: 3.87 / MAX: 17.35MIN: 4.24 / MAX: 49.431. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Machine Translation EN To DE FP16 - Device: CPUEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching2004006008001000SE +/- 0.77, N = 3SE +/- 1.56, N = 3SE +/- 0.19, N = 3950.94786.01590.921. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Machine Translation EN To DE FP16 - Device: CPUEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching1122334455SE +/- 0.04, N = 3SE +/- 0.08, N = 3SE +/- 0.01, N = 350.4240.6747.29MIN: 39.07 / MAX: 280.94MIN: 34.96 / MAX: 124.31MIN: 32.14 / MAX: 577.781. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Weld Porosity Detection FP16-INT8 - Device: CPUEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching7K14K21K28K35KSE +/- 4.81, N = 3SE +/- 3.60, N = 3SE +/- 38.32, N = 319170.6115659.3230938.501. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Weld Porosity Detection FP16-INT8 - Device: CPUEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching3691215SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 39.958.093.47MIN: 8.36 / MAX: 40.39MIN: 7.89 / MAX: 45.39MIN: 2.48 / MAX: 56.571. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Person Vehicle Bike Detection FP16 - Device: CPUEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching2K4K6K8K10KSE +/- 3.38, N = 3SE +/- 8.54, N = 3SE +/- 8.17, N = 39133.227447.606265.771. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Person Vehicle Bike Detection FP16 - Device: CPUEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching48121620SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.02, N = 35.254.2917.83MIN: 4.36 / MAX: 23.21MIN: 4.11 / MAX: 21.83MIN: 13.06 / MAX: 147.361. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Age Gender Recognition Retail 0013 FP16 - Device: CPUEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching30K60K90K120K150KSE +/- 1825.86, N = 3SE +/- 685.52, N = 3SE +/- 967.90, N = 3146867.48162207.97108515.121. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Age Gender Recognition Retail 0013 FP16 - Device: CPUEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching0.12380.24760.37140.49520.619SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 30.550.520.44MIN: 0.5 / MAX: 45.73MIN: 0.49 / MAX: 50.12MIN: 0.33 / MAX: 42.851. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.3Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPUEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching30K60K90K120K150KSE +/- 611.95, N = 3SE +/- 574.97, N = 3SE +/- 1694.26, N = 12124618.32128593.2459457.141. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.3Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPUEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching0.3150.630.9451.261.575SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.04, N = 120.990.881.40MIN: 0.85 / MAX: 37.79MIN: 0.83 / MAX: 24.85MIN: 0.7 / MAX: 123.261. (CXX) g++ options: -isystem -fsigned-char -ffunction-sections -fdata-sections -msse4.1 -msse4.2 -O3 -fno-strict-overflow -fwrapv -fPIC -fvisibility=hidden -Os -std=c++11 -MD -MT -MF

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.

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: GPT-2 - Device: CPU - Executor: StandardEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching50100150200250SE +/- 0.03, N = 3SE +/- 4.25, N = 15SE +/- 9.23, N = 15103.18132.72218.691. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: yolov4 - Device: CPU - Executor: StandardEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching246810SE +/- 0.04001, N = 3SE +/- 0.03523, N = 3SE +/- 0.13594, N = 124.900335.105057.700461. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: bertsquad-12 - Device: CPU - Executor: StandardEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching3691215SE +/- 0.24, N = 15SE +/- 0.19, N = 15SE +/- 0.23, N = 1510.1811.6911.461. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: CaffeNet 12-int8 - Device: CPU - Executor: StandardEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching120240360480600SE +/- 7.41, N = 15SE +/- 5.94, N = 4SE +/- 8.12, N = 15435.19495.24562.221. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: fcn-resnet101-11 - Device: CPU - Executor: StandardEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching1.20042.40083.60124.80166.002SE +/- 0.02211, N = 3SE +/- 0.02211, N = 3SE +/- 0.18914, N = 154.697974.659825.335141. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: ArcFace ResNet-100 - Device: CPU - Executor: StandardEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching612182430SE +/- 0.09, N = 3SE +/- 0.09, N = 3SE +/- 0.34, N = 1519.3124.0123.771. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.14Model: ResNet50 v1-12-int8 - Device: CPU - Executor: StandardEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching306090120150SE +/- 3.31, N = 15SE +/- 1.11, N = 3SE +/- 2.29, N = 15146.56152.44125.281. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt

CPU Power Consumption Monitor

OpenBenchmarking.orgWattsCPU Power Consumption MonitorPhoronix Test Suite System MonitoringEPYC 9654 2PEPYC 9554 2PXeon Max 9480 2P, HBM Caching160320480640800Min: 31.88 / Avg: 448.81 / Max: 725.51Min: 34.39 / Avg: 413.82 / Max: 710.63Min: 87.33 / Avg: 548.37 / Max: 899.87

CPU Peak Freq (Highest CPU Core Frequency) Monitor

OpenBenchmarking.orgMegahertzCPU Peak Freq (Highest CPU Core Frequency) MonitorPhoronix Test Suite System MonitoringXeon Max 9480 2P, HBM Caching6001200180024003000Min: 1100 / Avg: 3207.85 / Max: 3577

System Power Consumption Monitor

OpenBenchmarking.orgWattsSystem Power Consumption MonitorPhoronix Test Suite System MonitoringXeon Max 9480 2P, HBM Caching160320480640800Min: 260 / Avg: 751.74 / Max: 907

53 Results Shown

libxsmm:
  128
  256
  32
  64
oneDNN:
  IP Shapes 1D - bf16bf16bf16 - CPU
  IP Shapes 3D - bf16bf16bf16 - CPU
  Convolution Batch Shapes Auto - bf16bf16bf16 - CPU
  Deconvolution Batch shapes_1d - bf16bf16bf16 - CPU
  Deconvolution Batch shapes_3d - bf16bf16bf16 - CPU
  Recurrent Neural Network Training - bf16bf16bf16 - CPU
  Recurrent Neural Network Inference - bf16bf16bf16 - CPU
TensorFlow:
  CPU - 16 - VGG-16
  CPU - 16 - AlexNet
  CPU - 512 - VGG-16
  CPU - 512 - AlexNet
  CPU - 16 - GoogLeNet
  CPU - 16 - ResNet-50
  CPU - 512 - GoogLeNet
  CPU - 512 - ResNet-50
OpenVINO:
  Face Detection FP16 - CPU:
    FPS
    ms
  Person Detection FP16 - CPU:
    FPS
    ms
  Person Detection FP32 - CPU:
    FPS
    ms
  Vehicle Detection FP16 - CPU:
    FPS
    ms
  Face Detection FP16-INT8 - CPU:
    FPS
    ms
  Vehicle Detection FP16-INT8 - CPU:
    FPS
    ms
  Weld Porosity Detection FP16 - CPU:
    FPS
    ms
  Machine Translation EN To DE FP16 - CPU:
    FPS
    ms
  Weld Porosity Detection FP16-INT8 - CPU:
    FPS
    ms
  Person Vehicle Bike Detection FP16 - CPU:
    FPS
    ms
  Age Gender Recognition Retail 0013 FP16 - CPU:
    FPS
    ms
  Age Gender Recognition Retail 0013 FP16-INT8 - CPU:
    FPS
    ms
ONNX Runtime:
  GPT-2 - CPU - Standard
  yolov4 - CPU - Standard
  bertsquad-12 - CPU - Standard
  CaffeNet 12-int8 - CPU - Standard
  fcn-resnet101-11 - CPU - Standard
  ArcFace ResNet-100 - CPU - Standard
  ResNet50 v1-12-int8 - CPU - Standard
CPU Power Consumption Monitor:
  Phoronix Test Suite System Monitoring:
    Watts
    Megahertz
    Watts