nlp-benchmarks

AWS EC2 Amazon Linux 2023 Benchmarking

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2402103-NE-2402012NE79
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  Test
  Duration
c6i.2xlarge
February 01
  2 Hours, 25 Minutes
m7i-flex.2xlarge
February 08
  2 Hours, 59 Minutes
c7a.2xlarge
February 09
  1 Hour, 48 Minutes
r7a.xlarge
February 09
  2 Hours, 14 Minutes
m7i.2xlarge
February 09
  2 Hours, 11 Minutes
r7iz.xlarge
February 09
  2 Hours, 37 Minutes
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  2 Hours, 22 Minutes

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nlp-benchmarksProcessorMotherboardChipsetMemoryDiskNetworkOSKernelCompilerFile-SystemSystem Layerc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlargeIntel Xeon Platinum 8375C (4 Cores / 8 Threads)Amazon EC2 c6i.2xlarge (1.0 BIOS)Intel 440FX 82441FX PMC1 x 16GB DDR4-3200MT/s215GB Amazon Elastic Block StoreAmazon ElasticAmazon Linux 20236.1.61-85.141.amzn2023.x86_64 (x86_64)GCC 11.4.1 20230605xfsamazonIntel Xeon Platinum 8488C (4 Cores / 8 Threads)Amazon EC2 m7i-flex.2xlarge (1.0 BIOS)1 x 32GB 4800MT/s6.1.72-96.166.amzn2023.x86_64 (x86_64)AMD EPYC 9R14 (8 Cores)Amazon EC2 c7a.2xlarge (1.0 BIOS)1 x 16GB 4800MT/sAMD EPYC 9R14 (4 Cores)Amazon EC2 r7a.xlarge (1.0 BIOS)1 x 32GB 4800MT/sIntel Xeon Platinum 8488C (4 Cores / 8 Threads)Amazon EC2 m7i.2xlarge (1.0 BIOS)Intel Xeon Gold 6455B (2 Cores / 4 Threads)Amazon EC2 r7iz.xlarge (1.0 BIOS)OpenBenchmarking.orgKernel Details- Transparent Huge Pages: madviseCompiler Details- --build=x86_64-amazon-linux --disable-libunwind-exceptions --enable-__cxa_atexit --enable-bootstrap --enable-cet --enable-checking=release --enable-gnu-indirect-function --enable-gnu-unique-object --enable-initfini-array --enable-languages=c,c++,fortran,lto --enable-multilib --enable-offload-targets=nvptx-none --enable-plugin --enable-shared --enable-threads=posix --mandir=/usr/share/man --with-arch_32=x86-64 --with-arch_64=x86-64-v2 --with-gcc-major-version-only --with-linker-hash-style=gnu --with-tune=generic --without-cuda-driver Processor Details- c6i.2xlarge: CPU Microcode: 0xd0003a5- m7i-flex.2xlarge: CPU Microcode: 0x2b000571- c7a.2xlarge: CPU Microcode: 0xa10113e- r7a.xlarge: CPU Microcode: 0xa10113e- m7i.2xlarge: CPU Microcode: 0x2b000571- r7iz.xlarge: CPU Microcode: 0x2b000571Python Details- Python 3.11.6Security Details- c6i.2xlarge: gather_data_sampling: Unknown: Dependent on hypervisor status + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Mitigation of Clear buffers; SMT Host state unknown + retbleed: Not affected + spec_rstack_overflow: 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 - m7i-flex.2xlarge: 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 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 - c7a.2xlarge: 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 no microcode + 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: disabled RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected - r7a.xlarge: 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 no microcode + 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: disabled RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected - m7i.2xlarge: 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 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 - r7iz.xlarge: 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 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

c6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlargeResult OverviewPhoronix Test Suite100%152%204%256%308%OpenVINOoneDNNPyTorchNumpy BenchmarkPyBench

nlp-benchmarksonednn: Convolution Batch Shapes Auto - f32 - CPUonednn: Deconvolution Batch shapes_1d - f32 - CPUonednn: Deconvolution Batch shapes_3d - f32 - CPUonednn: Convolution Batch Shapes Auto - u8s8f32 - CPUonednn: Deconvolution Batch shapes_1d - u8s8f32 - CPUonednn: Deconvolution Batch shapes_3d - u8s8f32 - CPUonednn: Recurrent Neural Network Inference - f32 - CPUonednn: Convolution Batch Shapes Auto - bf16bf16bf16 - CPUonednn: Deconvolution Batch shapes_1d - bf16bf16bf16 - CPUonednn: Deconvolution Batch shapes_3d - bf16bf16bf16 - CPUonednn: Recurrent Neural Network Inference - u8s8f32 - CPUonednn: Recurrent Neural Network Inference - bf16bf16bf16 - CPUnumpy: pytorch: CPU - 1 - ResNet-50pytorch: CPU - 1 - ResNet-152pytorch: CPU - 16 - ResNet-50pytorch: CPU - 32 - ResNet-50pytorch: CPU - 16 - ResNet-152pytorch: CPU - 32 - ResNet-152pytorch: CPU - 1 - Efficientnet_v2_lpytorch: CPU - 16 - Efficientnet_v2_lpytorch: CPU - 32 - Efficientnet_v2_lopenvino: Face Detection FP16 - CPUopenvino: Face Detection FP16 - CPUopenvino: Face Detection FP16-INT8 - CPUopenvino: Face Detection FP16-INT8 - CPUopenvino: Machine Translation EN To DE FP16 - CPUopenvino: Machine Translation EN To DE FP16 - CPUpybench: Total For Average Test Timesc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge5.9366912.66188.098036.243912.038361.772862496.8433.192046.698634.71662492.292501.50374.9926.7810.5715.9615.816.366.387.994.064.041.772252.046.53610.5922.26179.5310005.842618.100077.948787.194621.0163271.0032692382.463.689931.763503.110752389.642318.31438.2529.8912.1018.8418.347.367.558.995.385.478.43474.4616.57241.2153.8774.207367.351015.014375.103307.746191.094291.264051482.353.282456.902003.123391480.931478.51590.1050.1620.0031.8931.2912.9513.0311.748.758.715.16774.239.76409.7854.5173.348878.226919.8544110.16797.387322.180292.529822856.845.4078413.73186.259072857.772862.86595.0133.3913.1919.3519.327.687.688.445.665.672.62764.304.9408.0230.7764.988875.880198.617188.344626.619741.030111.066022320.943.376101.793603.207922310.902303.44452.5031.3612.4819.6219.437.657.668.845.265.287.80511.5414.51275.6549.3980.948157.6674511.197311.249310.19331.427361.457263062.694.994032.377054.093113064.813062.84554.2827.4311.0715.9215.306.376.398.174.634.635.86341.0810.72186.6434.4558.03691OpenBenchmarking.org

oneDNN

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPUc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge246810SE +/- 0.03862, N = 3SE +/- 0.02435, N = 3SE +/- 0.01338, N = 3SE +/- 0.00015, N = 3SE +/- 0.00970, N = 3SE +/- 0.00852, N = 35.936695.842617.351018.226915.880197.66745MIN: 5.66MIN: 5MIN: 7.22MIN: 8.1MIN: 5.62MIN: 7.481. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPUc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge3691215Min: 5.89 / Avg: 5.94 / Max: 6.01Min: 5.81 / Avg: 5.84 / Max: 5.89Min: 7.34 / Avg: 7.35 / Max: 7.38Min: 8.23 / Avg: 8.23 / Max: 8.23Min: 5.86 / Avg: 5.88 / Max: 5.89Min: 7.66 / Avg: 7.67 / Max: 7.681. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPUc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge3691215SE +/- 0.07954, N = 3SE +/- 0.01302, N = 3SE +/- 0.00229, N = 3SE +/- 0.00467, N = 3SE +/- 0.08548, N = 12SE +/- 0.00848, N = 312.661808.100075.014379.854418.6171811.19730MIN: 10.8MIN: 6.7MIN: 4.93MIN: 9.75MIN: 7.87MIN: 10.841. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPUc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge48121620Min: 12.54 / Avg: 12.66 / Max: 12.81Min: 8.07 / Avg: 8.1 / Max: 8.12Min: 5.01 / Avg: 5.01 / Max: 5.02Min: 9.85 / Avg: 9.85 / Max: 9.86Min: 8.44 / Avg: 8.62 / Max: 9.54Min: 11.19 / Avg: 11.2 / Max: 11.211. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPUc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge3691215SE +/- 0.01712, N = 3SE +/- 0.08711, N = 3SE +/- 0.00261, N = 3SE +/- 0.01406, N = 3SE +/- 0.02786, N = 3SE +/- 0.03556, N = 38.098037.948785.1033010.167908.3446211.24930MIN: 8.02MIN: 6.79MIN: 5.05MIN: 10.11MIN: 8.05MIN: 10.981. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPUc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge3691215Min: 8.07 / Avg: 8.1 / Max: 8.13Min: 7.79 / Avg: 7.95 / Max: 8.09Min: 5.1 / Avg: 5.1 / Max: 5.11Min: 10.15 / Avg: 10.17 / Max: 10.2Min: 8.31 / Avg: 8.34 / Max: 8.4Min: 11.18 / Avg: 11.25 / Max: 11.31. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPUc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge3691215SE +/- 0.08834, N = 3SE +/- 0.03815, N = 3SE +/- 0.01540, N = 3SE +/- 0.01020, N = 3SE +/- 0.02083, N = 3SE +/- 0.00372, N = 36.243917.194627.746197.387326.6197410.19330MIN: 5.78MIN: 6.66MIN: 7.55MIN: 7.27MIN: 6.24MIN: 9.931. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPUc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge3691215Min: 6.15 / Avg: 6.24 / Max: 6.42Min: 7.12 / Avg: 7.19 / Max: 7.25Min: 7.72 / Avg: 7.75 / Max: 7.78Min: 7.37 / Avg: 7.39 / Max: 7.41Min: 6.58 / Avg: 6.62 / Max: 6.65Min: 10.19 / Avg: 10.19 / Max: 10.21. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPUc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge0.49060.98121.47181.96242.453SE +/- 0.002826, N = 3SE +/- 0.013619, N = 15SE +/- 0.002971, N = 3SE +/- 0.000469, N = 3SE +/- 0.000901, N = 3SE +/- 0.003845, N = 32.0383601.0163271.0942902.1802901.0301101.427360MIN: 1.97MIN: 0.79MIN: 1.08MIN: 2.15MIN: 0.94MIN: 1.351. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPUc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge246810Min: 2.04 / Avg: 2.04 / Max: 2.04Min: 0.97 / Avg: 1.02 / Max: 1.16Min: 1.09 / Avg: 1.09 / Max: 1.1Min: 2.18 / Avg: 2.18 / Max: 2.18Min: 1.03 / Avg: 1.03 / Max: 1.03Min: 1.42 / Avg: 1.43 / Max: 1.441. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPUc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge0.56921.13841.70762.27682.846SE +/- 0.013170, N = 3SE +/- 0.011545, N = 4SE +/- 0.004187, N = 3SE +/- 0.006412, N = 3SE +/- 0.003802, N = 3SE +/- 0.001934, N = 31.7728601.0032691.2640502.5298201.0660201.457260MIN: 1.73MIN: 0.84MIN: 1.25MIN: 2.5MIN: 1MIN: 1.411. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPUc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge246810Min: 1.75 / Avg: 1.77 / Max: 1.79Min: 0.98 / Avg: 1 / Max: 1.03Min: 1.26 / Avg: 1.26 / Max: 1.27Min: 2.52 / Avg: 2.53 / Max: 2.54Min: 1.06 / Avg: 1.07 / Max: 1.07Min: 1.45 / Avg: 1.46 / Max: 1.461. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPUc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge7001400210028003500SE +/- 7.01, N = 3SE +/- 26.45, N = 4SE +/- 1.52, N = 3SE +/- 2.56, N = 3SE +/- 7.66, N = 3SE +/- 2.90, N = 32496.842382.461482.352856.842320.943062.69MIN: 2465.66MIN: 2219.69MIN: 1476.16MIN: 2845.85MIN: 2290.27MIN: 3036.531. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPUc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge5001000150020002500Min: 2486.35 / Avg: 2496.84 / Max: 2510.14Min: 2317.56 / Avg: 2382.46 / Max: 2447.12Min: 1480.48 / Avg: 1482.35 / Max: 1485.36Min: 2852.25 / Avg: 2856.84 / Max: 2861.11Min: 2310.19 / Avg: 2320.94 / Max: 2335.77Min: 3057.7 / Avg: 3062.69 / Max: 3067.751. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPUc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge816243240SE +/- 0.00337, N = 3SE +/- 0.03984, N = 3SE +/- 0.00275, N = 3SE +/- 0.02244, N = 3SE +/- 0.00955, N = 3SE +/- 0.00443, N = 333.192003.689933.282455.407843.376104.99403MIN: 33.13MIN: 5.321. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPUc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge714212835Min: 33.19 / Avg: 33.19 / Max: 33.2Min: 3.61 / Avg: 3.69 / Max: 3.75Min: 3.28 / Avg: 3.28 / Max: 3.29Min: 5.38 / Avg: 5.41 / Max: 5.45Min: 3.36 / Avg: 3.38 / Max: 3.39Min: 4.99 / Avg: 4.99 / Max: 51. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPUc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge1122334455SE +/- 0.01032, N = 3SE +/- 0.00827, N = 3SE +/- 0.00810, N = 3SE +/- 0.02961, N = 3SE +/- 0.00405, N = 3SE +/- 0.00607, N = 346.698601.763506.9020013.731801.793602.37705MIN: 46.42MIN: 13.511. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPUc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge1020304050Min: 46.68 / Avg: 46.7 / Max: 46.71Min: 1.75 / Avg: 1.76 / Max: 1.78Min: 6.89 / Avg: 6.9 / Max: 6.92Min: 13.7 / Avg: 13.73 / Max: 13.79Min: 1.79 / Avg: 1.79 / Max: 1.8Min: 2.37 / Avg: 2.38 / Max: 2.391. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPUc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge816243240SE +/- 0.00790, N = 3SE +/- 0.01261, N = 3SE +/- 0.00414, N = 3SE +/- 0.01228, N = 3SE +/- 0.00738, N = 3SE +/- 0.02647, N = 334.716603.110753.123396.259073.207924.09311MIN: 34.6MIN: 6.181. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPUc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge714212835Min: 34.71 / Avg: 34.72 / Max: 34.73Min: 3.09 / Avg: 3.11 / Max: 3.13Min: 3.12 / Avg: 3.12 / Max: 3.13Min: 6.24 / Avg: 6.26 / Max: 6.28Min: 3.19 / Avg: 3.21 / Max: 3.22Min: 4.06 / Avg: 4.09 / Max: 4.141. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPUc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge7001400210028003500SE +/- 2.42, N = 3SE +/- 24.80, N = 3SE +/- 2.09, N = 3SE +/- 1.65, N = 3SE +/- 2.59, N = 3SE +/- 9.60, N = 32492.292389.641480.932857.772310.903064.81MIN: 2460.06MIN: 2260.99MIN: 1474.24MIN: 2848.47MIN: 2291.18MIN: 3031.61. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPUc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge5001000150020002500Min: 2489.1 / Avg: 2492.29 / Max: 2497.05Min: 2353.7 / Avg: 2389.64 / Max: 2437.21Min: 1477.31 / Avg: 1480.93 / Max: 1484.54Min: 2854.58 / Avg: 2857.77 / Max: 2860.06Min: 2307 / Avg: 2310.9 / Max: 2315.81Min: 3047.32 / Avg: 3064.81 / Max: 3080.41. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPUc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge7001400210028003500SE +/- 2.60, N = 3SE +/- 15.72, N = 3SE +/- 1.00, N = 3SE +/- 3.75, N = 3SE +/- 1.63, N = 3SE +/- 2.69, N = 32501.502318.311478.512862.862303.443062.84MIN: 2476.86MIN: 2205.71MIN: 1472.49MIN: 2849.87MIN: 2276.46MIN: 3033.81. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.3Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPUc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge5001000150020002500Min: 2497.61 / Avg: 2501.5 / Max: 2506.43Min: 2287.05 / Avg: 2318.31 / Max: 2336.83Min: 1476.64 / Avg: 1478.51 / Max: 1480.07Min: 2856.66 / Avg: 2862.86 / Max: 2869.62Min: 2301.7 / Avg: 2303.44 / Max: 2306.7Min: 3059.46 / Avg: 3062.84 / Max: 3068.161. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl

Numpy Benchmark

This is a test to obtain the general Numpy performance. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgScore, More Is BetterNumpy Benchmarkc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge130260390520650SE +/- 1.37, N = 3SE +/- 3.53, N = 3SE +/- 1.02, N = 3SE +/- 0.90, N = 3SE +/- 0.98, N = 3SE +/- 0.21, N = 3374.99438.25590.10595.01452.50554.28
OpenBenchmarking.orgScore, More Is BetterNumpy Benchmarkc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge110220330440550Min: 372.52 / Avg: 374.99 / Max: 377.24Min: 432.57 / Avg: 438.25 / Max: 444.72Min: 588.54 / Avg: 590.1 / Max: 592.02Min: 593.67 / Avg: 595.01 / Max: 596.71Min: 450.55 / Avg: 452.5 / Max: 453.7Min: 554 / Avg: 554.28 / Max: 554.69

PyTorch

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-50c6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge1122334455SE +/- 0.13, N = 3SE +/- 0.05, N = 3SE +/- 0.32, N = 3SE +/- 0.04, N = 3SE +/- 0.15, N = 3SE +/- 0.09, N = 326.7829.8950.1633.3931.3627.43MIN: 13.67 / MAX: 27.8MIN: 7.96 / MAX: 34.56MIN: 33.27 / MAX: 51.43MIN: 24.56 / MAX: 33.78MIN: 26.54 / MAX: 32.62MIN: 21.64 / MAX: 28.06
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-50c6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge1020304050Min: 26.52 / Avg: 26.78 / Max: 26.94Min: 29.8 / Avg: 29.89 / Max: 29.97Min: 49.7 / Avg: 50.16 / Max: 50.79Min: 33.31 / Avg: 33.39 / Max: 33.44Min: 31.16 / Avg: 31.36 / Max: 31.66Min: 27.25 / Avg: 27.43 / Max: 27.54

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-152c6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge510152025SE +/- 0.01, N = 3SE +/- 0.10, N = 3SE +/- 0.05, N = 3SE +/- 0.02, N = 3SE +/- 0.09, N = 3SE +/- 0.02, N = 310.5712.1020.0013.1912.4811.07MIN: 9.04 / MAX: 10.77MIN: 2.89 / MAX: 13.92MIN: 15.6 / MAX: 20.36MIN: 10.96 / MAX: 13.33MIN: 8.7 / MAX: 12.92MIN: 9.42 / MAX: 11.22
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-152c6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge510152025Min: 10.56 / Avg: 10.57 / Max: 10.58Min: 11.93 / Avg: 12.1 / Max: 12.28Min: 19.95 / Avg: 20 / Max: 20.09Min: 13.16 / Avg: 13.19 / Max: 13.23Min: 12.3 / Avg: 12.48 / Max: 12.6Min: 11.02 / Avg: 11.07 / Max: 11.11

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-50c6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge714212835SE +/- 0.12, N = 3SE +/- 0.17, N = 3SE +/- 0.24, N = 3SE +/- 0.18, N = 3SE +/- 0.08, N = 3SE +/- 0.04, N = 315.9618.8431.8919.3519.6215.92MIN: 11.65 / MAX: 17.13MIN: 4.37 / MAX: 21.77MIN: 23.54 / MAX: 32.58MIN: 15.18 / MAX: 19.82MIN: 15.92 / MAX: 20.23MIN: 14.8 / MAX: 16.24
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-50c6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge714212835Min: 15.76 / Avg: 15.96 / Max: 16.16Min: 18.51 / Avg: 18.84 / Max: 19.09Min: 31.47 / Avg: 31.89 / Max: 32.31Min: 19 / Avg: 19.35 / Max: 19.63Min: 19.5 / Avg: 19.62 / Max: 19.77Min: 15.87 / Avg: 15.92 / Max: 16.01

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-50c6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge714212835SE +/- 0.17, N = 4SE +/- 0.29, N = 15SE +/- 0.42, N = 15SE +/- 0.15, N = 10SE +/- 0.21, N = 5SE +/- 0.21, N = 1515.8118.3431.2919.3219.4315.30MIN: 9.11 / MAX: 17.08MIN: 4.11 / MAX: 22.15MIN: 20.73 / MAX: 33.27MIN: 13.74 / MAX: 19.98MIN: 13.34 / MAX: 20.17MIN: 10.53 / MAX: 16.18
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-50c6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge714212835Min: 15.33 / Avg: 15.81 / Max: 16.15Min: 15.59 / Avg: 18.34 / Max: 19.52Min: 28.22 / Avg: 31.29 / Max: 32.77Min: 18.18 / Avg: 19.32 / Max: 19.82Min: 18.6 / Avg: 19.43 / Max: 19.73Min: 13.72 / Avg: 15.3 / Max: 15.93

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-152c6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge3691215SE +/- 0.05, N = 3SE +/- 0.08, N = 5SE +/- 0.09, N = 3SE +/- 0.02, N = 3SE +/- 0.02, N = 3SE +/- 0.01, N = 36.367.3612.957.687.656.37MIN: 5.43 / MAX: 6.61MIN: 2.24 / MAX: 8.66MIN: 4.2 / MAX: 13.21MIN: 6.45 / MAX: 7.76MIN: 6.27 / MAX: 7.82MIN: 5.79 / MAX: 6.45
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-152c6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge48121620Min: 6.26 / Avg: 6.36 / Max: 6.43Min: 7.06 / Avg: 7.36 / Max: 7.48Min: 12.81 / Avg: 12.95 / Max: 13.1Min: 7.64 / Avg: 7.68 / Max: 7.7Min: 7.62 / Avg: 7.65 / Max: 7.69Min: 6.36 / Avg: 6.37 / Max: 6.39

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-152c6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge3691215SE +/- 0.01, N = 3SE +/- 0.02, N = 3SE +/- 0.05, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 36.387.5513.037.687.666.39MIN: 3.7 / MAX: 6.57MIN: 2.93 / MAX: 8.62MIN: 10.5 / MAX: 13.2MIN: 6.31 / MAX: 7.76MIN: 4.36 / MAX: 7.82MIN: 5.8 / MAX: 6.46
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-152c6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge48121620Min: 6.37 / Avg: 6.38 / Max: 6.4Min: 7.52 / Avg: 7.55 / Max: 7.59Min: 12.93 / Avg: 13.03 / Max: 13.11Min: 7.66 / Avg: 7.68 / Max: 7.7Min: 7.64 / Avg: 7.66 / Max: 7.68Min: 6.37 / Avg: 6.39 / Max: 6.4

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_lc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge3691215SE +/- 0.02, N = 3SE +/- 0.09, N = 12SE +/- 0.02, N = 3SE +/- 0.01, N = 3SE +/- 0.04, N = 3SE +/- 0.02, N = 37.998.9911.748.448.848.17MIN: 6.59 / MAX: 8.31MIN: 3.08 / MAX: 10.39MIN: 8.95 / MAX: 11.9MIN: 2.94 / MAX: 8.53MIN: 7.72 / MAX: 9.09MIN: 1.5 / MAX: 8.27
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_lc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge3691215Min: 7.95 / Avg: 7.99 / Max: 8.03Min: 8.46 / Avg: 8.99 / Max: 9.37Min: 11.7 / Avg: 11.74 / Max: 11.77Min: 8.42 / Avg: 8.44 / Max: 8.46Min: 8.78 / Avg: 8.84 / Max: 8.93Min: 8.14 / Avg: 8.17 / Max: 8.19

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_lc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge246810SE +/- 0.03, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 34.065.388.755.665.264.63MIN: 3.29 / MAX: 4.32MIN: 2.12 / MAX: 6.08MIN: 5.72 / MAX: 8.84MIN: 4.27 / MAX: 5.72MIN: 3.36 / MAX: 5.38MIN: 3.17 / MAX: 4.69
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_lc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge3691215Min: 4 / Avg: 4.06 / Max: 4.1Min: 5.36 / Avg: 5.38 / Max: 5.39Min: 8.73 / Avg: 8.75 / Max: 8.77Min: 5.64 / Avg: 5.66 / Max: 5.68Min: 5.24 / Avg: 5.26 / Max: 5.28Min: 4.61 / Avg: 4.63 / Max: 4.65

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_lc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge246810SE +/- 0.02, N = 3SE +/- 0.01, N = 3SE +/- 0.02, N = 3SE +/- 0.01, N = 3SE +/- 0.02, N = 3SE +/- 0.01, N = 34.045.478.715.675.284.63MIN: 3.5 / MAX: 4.36MIN: 2.31 / MAX: 6.19MIN: 5.53 / MAX: 8.82MIN: 4.37 / MAX: 5.73MIN: 4.01 / MAX: 5.41MIN: 4.28 / MAX: 4.69
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_lc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge3691215Min: 4.02 / Avg: 4.04 / Max: 4.07Min: 5.45 / Avg: 5.47 / Max: 5.49Min: 8.67 / Avg: 8.71 / Max: 8.74Min: 5.65 / Avg: 5.67 / Max: 5.68Min: 5.24 / Avg: 5.28 / Max: 5.3Min: 4.62 / Avg: 4.63 / Max: 4.65

OpenVINO

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.2.devModel: Face Detection FP16 - Device: CPUc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge246810SE +/- 0.01, N = 3SE +/- 0.10, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.04, N = 3SE +/- 0.02, N = 31.778.435.162.627.805.861. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -pie
OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.2.devModel: Face Detection FP16 - Device: CPUc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge3691215Min: 1.76 / Avg: 1.77 / Max: 1.78Min: 8.23 / Avg: 8.43 / Max: 8.58Min: 5.15 / Avg: 5.16 / Max: 5.16Min: 2.62 / Avg: 2.62 / Max: 2.62Min: 7.75 / Avg: 7.8 / Max: 7.87Min: 5.83 / Avg: 5.86 / Max: 5.881. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -pie

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.2.devModel: Face Detection FP16 - Device: CPUc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge5001000150020002500SE +/- 3.74, N = 3SE +/- 5.97, N = 3SE +/- 0.28, N = 3SE +/- 0.15, N = 3SE +/- 2.36, N = 3SE +/- 0.94, N = 32252.04474.46774.23764.30511.54341.08MIN: 2202.18 / MAX: 2317.24MIN: 427.39 / MAX: 558.54MIN: 767.78 / MAX: 795.49MIN: 761.82 / MAX: 783.23MIN: 337.11 / MAX: 534.54MIN: 269.26 / MAX: 532.111. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -pie
OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.2.devModel: Face Detection FP16 - Device: CPUc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge400800120016002000Min: 2244.57 / Avg: 2252.04 / Max: 2256.2Min: 465.87 / Avg: 474.46 / Max: 485.94Min: 773.88 / Avg: 774.23 / Max: 774.79Min: 764.08 / Avg: 764.3 / Max: 764.59Min: 507.13 / Avg: 511.54 / Max: 515.22Min: 339.95 / Avg: 341.08 / Max: 342.951. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -pie

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.2.devModel: Face Detection FP16-INT8 - Device: CPUc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge48121620SE +/- 0.04, N = 3SE +/- 0.16, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.02, N = 3SE +/- 0.01, N = 36.5316.579.764.9014.5110.721. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -pie
OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.2.devModel: Face Detection FP16-INT8 - Device: CPUc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge48121620Min: 6.47 / Avg: 6.53 / Max: 6.6Min: 16.25 / Avg: 16.57 / Max: 16.78Min: 9.76 / Avg: 9.76 / Max: 9.76Min: 4.9 / Avg: 4.9 / Max: 4.9Min: 14.49 / Avg: 14.51 / Max: 14.54Min: 10.71 / Avg: 10.72 / Max: 10.731. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -pie

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.2.devModel: Face Detection FP16-INT8 - Device: CPUc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge130260390520650SE +/- 3.28, N = 3SE +/- 2.35, N = 3SE +/- 0.07, N = 3SE +/- 0.14, N = 3SE +/- 0.26, N = 3SE +/- 0.12, N = 3610.59241.21409.78408.02275.65186.64MIN: 497.95 / MAX: 643.84MIN: 91.81 / MAX: 374.94MIN: 407.35 / MAX: 424.19MIN: 406.22 / MAX: 426.04MIN: 267.85 / MAX: 299.94MIN: 178.68 / MAX: 210.71. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -pie
OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.2.devModel: Face Detection FP16-INT8 - Device: CPUc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge110220330440550Min: 604.8 / Avg: 610.59 / Max: 616.17Min: 238.26 / Avg: 241.21 / Max: 245.85Min: 409.68 / Avg: 409.78 / Max: 409.91Min: 407.8 / Avg: 408.02 / Max: 408.28Min: 275.15 / Avg: 275.65 / Max: 276.04Min: 186.4 / Avg: 186.64 / Max: 186.781. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -pie

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.2.devModel: Machine Translation EN To DE FP16 - Device: CPUc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge1224364860SE +/- 0.06, N = 3SE +/- 0.19, N = 3SE +/- 0.02, N = 3SE +/- 0.18, N = 3SE +/- 0.02, N = 3SE +/- 0.03, N = 322.2653.8754.5130.7749.3934.451. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -pie
OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.2.devModel: Machine Translation EN To DE FP16 - Device: CPUc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge1122334455Min: 22.16 / Avg: 22.26 / Max: 22.37Min: 53.5 / Avg: 53.87 / Max: 54.11Min: 54.49 / Avg: 54.51 / Max: 54.54Min: 30.4 / Avg: 30.77 / Max: 30.99Min: 49.36 / Avg: 49.39 / Max: 49.43Min: 34.4 / Avg: 34.45 / Max: 34.511. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -pie

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.2.devModel: Machine Translation EN To DE FP16 - Device: CPUc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge4080120160200SE +/- 0.44, N = 3SE +/- 0.25, N = 3SE +/- 0.02, N = 3SE +/- 0.40, N = 3SE +/- 0.04, N = 3SE +/- 0.05, N = 3179.5374.2073.3464.9880.9458.03MIN: 100.26 / MAX: 344MIN: 34.84 / MAX: 96.18MIN: 65.17 / MAX: 80.62MIN: 61.57 / MAX: 90.41MIN: 69.04 / MAX: 153.39MIN: 52.43 / MAX: 74.851. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -pie
OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.2.devModel: Machine Translation EN To DE FP16 - Device: CPUc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge306090120150Min: 178.75 / Avg: 179.53 / Max: 180.27Min: 73.88 / Avg: 74.2 / Max: 74.69Min: 73.29 / Avg: 73.34 / Max: 73.36Min: 64.51 / Avg: 64.98 / Max: 65.77Min: 80.85 / Avg: 80.94 / Max: 81Min: 57.94 / Avg: 58.03 / Max: 58.121. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -pie

PyBench

This test profile reports the total time of the different average timed test results from PyBench. PyBench reports average test times for different functions such as BuiltinFunctionCalls and NestedForLoops, with this total result providing a rough estimate as to Python's average performance on a given system. This test profile runs PyBench each time for 20 rounds. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyBench 2018-02-16Total For Average Test Timesc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge2004006008001000SE +/- 0.33, N = 3SE +/- 3.18, N = 3SE +/- 0.67, N = 3SE +/- 1.33, N = 3SE +/- 2.33, N = 3SE +/- 1.00, N = 31000736887887815691
OpenBenchmarking.orgMilliseconds, Fewer Is BetterPyBench 2018-02-16Total For Average Test Timesc6i.2xlargem7i-flex.2xlargec7a.2xlarger7a.xlargem7i.2xlarger7iz.xlarge2004006008001000Min: 1000 / Avg: 1000.33 / Max: 1001Min: 732 / Avg: 735.67 / Max: 742Min: 886 / Avg: 886.67 / Max: 888Min: 886 / Avg: 887.33 / Max: 890Min: 811 / Avg: 814.67 / Max: 819Min: 690 / Avg: 691 / Max: 693