Benchmarks for a future article.
Compare your own system(s) to this result file with the
Phoronix Test Suite by running the command:
phoronix-test-suite benchmark 2312143-NE-A8154652071 a - Phoronix Test Suite a Benchmarks for a future article.
HTML result view exported from: https://openbenchmarking.org/result/2312143-NE-A8154652071&sro&gru .
a Processor Motherboard Chipset Memory Disk Graphics Network OS Kernel Compiler File-System Screen Resolution a b c d 2 x INTEL XEON PLATINUM 8592+ @ 3.90GHz (128 Cores / 256 Threads) Quanta Cloud S6Q-MB-MPS (3B05.TEL4P1 BIOS) Intel Device 1bce 1008GB 3201GB Micron_7450_MTFDKCB3T2TFS ASPEED 2 x Intel X710 for 10GBASE-T Ubuntu 23.10 6.5.0-13-generic (x86_64) GCC 13.2.0 ext4 1920x1080 OpenBenchmarking.org Kernel Details - Transparent Huge Pages: madvise Processor Details - Scaling Governor: intel_pstate powersave (EPP: balance_performance) - CPU Microcode: 0x21000161 Python Details - Python 3.11.6 Security Details - 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 / Automatic IBRS IBPB: conditional RSB filling PBRSB-eIBRS: SW sequence + srbds: Not affected + tsx_async_abort: Not affected Compiler Details - d: --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,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-defaulted --enable-offload-targets=nvptx-none=/build/gcc-13-XYspKM/gcc-13-13.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-13-XYspKM/gcc-13-13.2.0/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
a deepsparse: NLP Document Classification, oBERT base uncased on IMDB - Asynchronous Multi-Stream deepsparse: NLP Document Classification, oBERT base uncased on IMDB - Synchronous Single-Stream deepsparse: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Asynchronous Multi-Stream deepsparse: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Synchronous Single-Stream deepsparse: ResNet-50, Baseline - Asynchronous Multi-Stream deepsparse: ResNet-50, Baseline - Synchronous Single-Stream deepsparse: ResNet-50, Sparse INT8 - Asynchronous Multi-Stream deepsparse: ResNet-50, Sparse INT8 - Synchronous Single-Stream deepsparse: CV Detection, YOLOv5s COCO - Asynchronous Multi-Stream deepsparse: CV Detection, YOLOv5s COCO - Synchronous Single-Stream deepsparse: BERT-Large, NLP Question Answering - Asynchronous Multi-Stream deepsparse: BERT-Large, NLP Question Answering - Synchronous Single-Stream deepsparse: CV Classification, ResNet-50 ImageNet - Asynchronous Multi-Stream deepsparse: CV Classification, ResNet-50 ImageNet - Synchronous Single-Stream deepsparse: CV Detection, YOLOv5s COCO, Sparse INT8 - Asynchronous Multi-Stream deepsparse: CV Detection, YOLOv5s COCO, Sparse INT8 - Synchronous Single-Stream deepsparse: NLP Text Classification, DistilBERT mnli - Asynchronous Multi-Stream deepsparse: NLP Text Classification, DistilBERT mnli - Synchronous Single-Stream deepsparse: CV Segmentation, 90% Pruned YOLACT Pruned - Asynchronous Multi-Stream deepsparse: CV Segmentation, 90% Pruned YOLACT Pruned - Synchronous Single-Stream deepsparse: BERT-Large, NLP Question Answering, Sparse INT8 - Asynchronous Multi-Stream deepsparse: BERT-Large, NLP Question Answering, Sparse INT8 - Synchronous Single-Stream deepsparse: NLP Token Classification, BERT base uncased conll2003 - Asynchronous Multi-Stream deepsparse: NLP Token Classification, BERT base uncased conll2003 - Synchronous Single-Stream deepsparse: NLP Document Classification, oBERT base uncased on IMDB - Asynchronous Multi-Stream deepsparse: NLP Document Classification, oBERT base uncased on IMDB - Synchronous Single-Stream deepsparse: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Asynchronous Multi-Stream deepsparse: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Synchronous Single-Stream deepsparse: ResNet-50, Baseline - Asynchronous Multi-Stream deepsparse: ResNet-50, Baseline - Synchronous Single-Stream deepsparse: ResNet-50, Sparse INT8 - Asynchronous Multi-Stream deepsparse: ResNet-50, Sparse INT8 - Synchronous Single-Stream deepsparse: CV Detection, YOLOv5s COCO - Asynchronous Multi-Stream deepsparse: CV Detection, YOLOv5s COCO - Synchronous Single-Stream deepsparse: BERT-Large, NLP Question Answering - Asynchronous Multi-Stream deepsparse: BERT-Large, NLP Question Answering - Synchronous Single-Stream deepsparse: CV Classification, ResNet-50 ImageNet - Asynchronous Multi-Stream deepsparse: CV Classification, ResNet-50 ImageNet - Synchronous Single-Stream deepsparse: CV Detection, YOLOv5s COCO, Sparse INT8 - Asynchronous Multi-Stream deepsparse: CV Detection, YOLOv5s COCO, Sparse INT8 - Synchronous Single-Stream deepsparse: NLP Text Classification, DistilBERT mnli - Asynchronous Multi-Stream deepsparse: NLP Text Classification, DistilBERT mnli - Synchronous Single-Stream deepsparse: CV Segmentation, 90% Pruned YOLACT Pruned - Asynchronous Multi-Stream deepsparse: CV Segmentation, 90% Pruned YOLACT Pruned - Synchronous Single-Stream deepsparse: BERT-Large, NLP Question Answering, Sparse INT8 - Asynchronous Multi-Stream deepsparse: BERT-Large, NLP Question Answering, Sparse INT8 - Synchronous Single-Stream deepsparse: NLP Token Classification, BERT base uncased conll2003 - Asynchronous Multi-Stream deepsparse: NLP Token Classification, BERT base uncased conll2003 - Synchronous Single-Stream nwchem: C240 Buckyball wrf: conus 2.5km a b c d 133.5159 31.1945 4554.9796 238.6523 1829.9644 338.9562 11228.6625 1030.3181 828.0384 190.8420 156.0563 29.9421 1832.7927 339.0416 854.0525 194.2476 1231.2049 199.6930 183.4966 34.9620 1880.7688 96.4300 133.6023 31.6954 475.6964 32.0613 14.0362 4.2083 34.9169 2.9492 5.6852 0.9681 77.1758 5.2382 407.2777 33.4022 34.8681 2.9484 74.8177 5.1485 51.9301 5.0073 347.6637 28.5876 33.9808 10.3634 475.1265 31.5821 1744 5566.729 133.7189 31.2336 4563.5097 237.0460 1824.3759 337.6799 11169.8517 1027.5117 828.6532 190.0399 155.7222 30.3891 1817.9939 338.8583 852.9455 193.5972 1231.2939 199.3380 180.3157 35.1065 1875.9035 96.3790 133.8239 31.5332 474.1852 32.0368 14.0081 4.2295 35.0063 2.9602 5.7140 0.9706 77.0924 5.2617 408.6263 32.8989 35.1423 2.9500 74.9435 5.1659 51.9273 5.0196 353.6889 28.4701 34.0815 10.3695 474.3687 31.7303 1730.7 5600.976 133.4843 31.6300 4563.4278 230.7640 1827.9780 338.5536 11163.6593 1043.2804 828.4462 189.8175 155.7677 30.2944 1834.4771 338.2192 854.2521 193.0872 1231.2736 199.3323 177.1512 35.0057 1879.8388 96.5474 133.6004 31.7202 475.6804 31.6501 14.0090 4.3436 34.9683 2.9530 5.7165 0.9556 77.1235 5.2651 408.9699 32.9984 34.8217 2.9555 74.7945 5.1802 51.9192 5.0179 359.8919 28.5521 33.9939 10.3507 475.3497 31.5618 1757.3 5583.112 133.0079 32.8936 4556.0233 240.2336 1837.4977 338.1466 11221.1357 1032.2410 825.0841 190.1376 155.6020 29.5231 1819.6861 339.3671 850.8926 193.8186 1226.7960 196.7874 181.2029 34.9987 1865.0193 95.6981 133.5969 33.0540 477.6108 30.4222 14.0315 4.1604 34.7567 2.9573 5.6908 0.9667 77.4573 5.2589 408.1638 33.8635 35.1013 2.9455 75.0848 5.1614 52.0706 5.0808 352.2235 28.5586 34.2508 10.4501 475.4464 30.2891 1748 5617.197 OpenBenchmarking.org
Neural Magic DeepSparse Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream a b c d 30 60 90 120 150 SE +/- 0.15, N = 3 SE +/- 0.13, N = 3 SE +/- 0.16, N = 3 SE +/- 0.11, N = 3 133.52 133.72 133.48 133.01
Neural Magic DeepSparse Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream a b c d 8 16 24 32 40 SE +/- 0.38, N = 4 SE +/- 0.25, N = 15 SE +/- 0.32, N = 15 SE +/- 0.26, N = 15 31.19 31.23 31.63 32.89
Neural Magic DeepSparse Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream a b c d 1000 2000 3000 4000 5000 SE +/- 49.40, N = 5 SE +/- 40.39, N = 7 SE +/- 43.60, N = 6 SE +/- 42.83, N = 6 4554.98 4563.51 4563.43 4556.02
Neural Magic DeepSparse Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Stream a b c d 50 100 150 200 250 SE +/- 4.61, N = 15 SE +/- 3.82, N = 15 SE +/- 3.66, N = 15 SE +/- 3.16, N = 3 238.65 237.05 230.76 240.23
Neural Magic DeepSparse Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream a b c d 400 800 1200 1600 2000 SE +/- 4.85, N = 3 SE +/- 13.19, N = 3 SE +/- 17.94, N = 3 SE +/- 14.66, N = 3 1829.96 1824.38 1827.98 1837.50
Neural Magic DeepSparse Model: ResNet-50, Baseline - Scenario: Synchronous Single-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: ResNet-50, Baseline - Scenario: Synchronous Single-Stream a b c d 70 140 210 280 350 SE +/- 2.76, N = 9 SE +/- 3.44, N = 6 SE +/- 2.56, N = 12 SE +/- 2.94, N = 12 338.96 337.68 338.55 338.15
Neural Magic DeepSparse Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream a b c d 2K 4K 6K 8K 10K SE +/- 71.77, N = 13 SE +/- 89.80, N = 9 SE +/- 101.43, N = 7 SE +/- 77.36, N = 12 11228.66 11169.85 11163.66 11221.14
Neural Magic DeepSparse Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream a b c d 200 400 600 800 1000 SE +/- 11.12, N = 4 SE +/- 9.47, N = 3 SE +/- 5.37, N = 3 SE +/- 9.64, N = 7 1030.32 1027.51 1043.28 1032.24
Neural Magic DeepSparse Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream a b c d 200 400 600 800 1000 SE +/- 7.51, N = 3 SE +/- 6.37, N = 3 SE +/- 6.81, N = 3 SE +/- 9.22, N = 3 828.04 828.65 828.45 825.08
Neural Magic DeepSparse Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream a b c d 40 80 120 160 200 SE +/- 1.29, N = 12 SE +/- 1.73, N = 12 SE +/- 1.69, N = 7 SE +/- 1.52, N = 12 190.84 190.04 189.82 190.14
Neural Magic DeepSparse Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream a b c d 30 60 90 120 150 SE +/- 0.66, N = 3 SE +/- 0.66, N = 3 SE +/- 1.19, N = 3 SE +/- 1.10, N = 3 156.06 155.72 155.77 155.60
Neural Magic DeepSparse Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Stream a b c d 7 14 21 28 35 SE +/- 0.30, N = 6 SE +/- 0.27, N = 3 SE +/- 0.15, N = 3 SE +/- 0.10, N = 3 29.94 30.39 30.29 29.52
Neural Magic DeepSparse Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream a b c d 400 800 1200 1600 2000 SE +/- 22.80, N = 3 SE +/- 7.71, N = 3 SE +/- 5.61, N = 3 SE +/- 21.20, N = 3 1832.79 1817.99 1834.48 1819.69
Neural Magic DeepSparse Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream a b c d 70 140 210 280 350 SE +/- 2.66, N = 10 SE +/- 2.82, N = 9 SE +/- 3.30, N = 6 SE +/- 2.24, N = 12 339.04 338.86 338.22 339.37
Neural Magic DeepSparse Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream a b c d 200 400 600 800 1000 SE +/- 8.70, N = 3 SE +/- 10.26, N = 3 SE +/- 9.10, N = 3 SE +/- 10.96, N = 3 854.05 852.95 854.25 850.89
Neural Magic DeepSparse Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Stream a b c d 40 80 120 160 200 SE +/- 1.36, N = 12 SE +/- 1.53, N = 13 SE +/- 1.70, N = 12 SE +/- 1.62, N = 12 194.25 193.60 193.09 193.82
Neural Magic DeepSparse Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream a b c d 300 600 900 1200 1500 SE +/- 14.83, N = 3 SE +/- 14.60, N = 4 SE +/- 13.91, N = 3 SE +/- 17.38, N = 3 1231.20 1231.29 1231.27 1226.80
Neural Magic DeepSparse Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream a b c d 40 80 120 160 200 SE +/- 1.45, N = 12 SE +/- 2.05, N = 12 SE +/- 1.76, N = 12 SE +/- 1.69, N = 8 199.69 199.34 199.33 196.79
Neural Magic DeepSparse Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream a b c d 40 80 120 160 200 SE +/- 1.57, N = 8 SE +/- 2.09, N = 3 SE +/- 1.83, N = 3 SE +/- 1.48, N = 9 183.50 180.32 177.15 181.20
Neural Magic DeepSparse Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream a b c d 8 16 24 32 40 SE +/- 0.33, N = 7 SE +/- 0.34, N = 6 SE +/- 0.35, N = 6 SE +/- 0.23, N = 12 34.96 35.11 35.01 35.00
Neural Magic DeepSparse Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream a b c d 400 800 1200 1600 2000 SE +/- 21.42, N = 3 SE +/- 26.46, N = 3 SE +/- 21.19, N = 3 SE +/- 21.54, N = 3 1880.77 1875.90 1879.84 1865.02
Neural Magic DeepSparse Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream a b c d 20 40 60 80 100 SE +/- 0.11, N = 3 SE +/- 0.30, N = 3 SE +/- 0.16, N = 3 SE +/- 0.72, N = 10 96.43 96.38 96.55 95.70
Neural Magic DeepSparse Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream a b c d 30 60 90 120 150 SE +/- 0.13, N = 3 SE +/- 0.14, N = 3 SE +/- 0.19, N = 3 SE +/- 0.26, N = 3 133.60 133.82 133.60 133.60
Neural Magic DeepSparse Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream a b c d 8 16 24 32 40 SE +/- 0.31, N = 15 SE +/- 0.25, N = 15 SE +/- 0.33, N = 15 SE +/- 0.33, N = 15 31.70 31.53 31.72 33.05
Neural Magic DeepSparse Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream a b c d 100 200 300 400 500 SE +/- 0.61, N = 3 SE +/- 0.47, N = 3 SE +/- 0.52, N = 3 SE +/- 0.44, N = 3 475.70 474.19 475.68 477.61
Neural Magic DeepSparse Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream a b c d 7 14 21 28 35 SE +/- 0.40, N = 4 SE +/- 0.27, N = 15 SE +/- 0.32, N = 15 SE +/- 0.25, N = 15 32.06 32.04 31.65 30.42
Neural Magic DeepSparse Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream a b c d 4 8 12 16 20 SE +/- 0.16, N = 5 SE +/- 0.13, N = 7 SE +/- 0.14, N = 6 SE +/- 0.14, N = 6 14.04 14.01 14.01 14.03
Neural Magic DeepSparse Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Stream a b c d 0.9773 1.9546 2.9319 3.9092 4.8865 SE +/- 0.0821, N = 15 SE +/- 0.0666, N = 15 SE +/- 0.0661, N = 15 SE +/- 0.0540, N = 3 4.2083 4.2295 4.3436 4.1604
Neural Magic DeepSparse Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream a b c d 8 16 24 32 40 SE +/- 0.08, N = 3 SE +/- 0.25, N = 3 SE +/- 0.35, N = 3 SE +/- 0.29, N = 3 34.92 35.01 34.97 34.76
Neural Magic DeepSparse Model: ResNet-50, Baseline - Scenario: Synchronous Single-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: ResNet-50, Baseline - Scenario: Synchronous Single-Stream a b c d 0.666 1.332 1.998 2.664 3.33 SE +/- 0.0255, N = 9 SE +/- 0.0315, N = 6 SE +/- 0.0242, N = 12 SE +/- 0.0282, N = 12 2.9492 2.9602 2.9530 2.9573
Neural Magic DeepSparse Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream a b c d 1.2862 2.5724 3.8586 5.1448 6.431 SE +/- 0.0393, N = 13 SE +/- 0.0484, N = 9 SE +/- 0.0544, N = 7 SE +/- 0.0425, N = 12 5.6852 5.7140 5.7165 5.6908
Neural Magic DeepSparse Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream a b c d 0.2184 0.4368 0.6552 0.8736 1.092 SE +/- 0.0105, N = 4 SE +/- 0.0090, N = 3 SE +/- 0.0048, N = 3 SE +/- 0.0094, N = 7 0.9681 0.9706 0.9556 0.9667
Neural Magic DeepSparse Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream a b c d 20 40 60 80 100 SE +/- 0.70, N = 3 SE +/- 0.63, N = 3 SE +/- 0.64, N = 3 SE +/- 0.87, N = 3 77.18 77.09 77.12 77.46
Neural Magic DeepSparse Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream a b c d 1.1846 2.3692 3.5538 4.7384 5.923 SE +/- 0.0382, N = 12 SE +/- 0.0526, N = 12 SE +/- 0.0492, N = 7 SE +/- 0.0457, N = 12 5.2382 5.2617 5.2651 5.2589
Neural Magic DeepSparse Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream a b c d 90 180 270 360 450 SE +/- 1.62, N = 3 SE +/- 1.91, N = 3 SE +/- 2.55, N = 3 SE +/- 2.06, N = 3 407.28 408.63 408.97 408.16
Neural Magic DeepSparse Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Stream a b c d 8 16 24 32 40 SE +/- 0.34, N = 6 SE +/- 0.30, N = 3 SE +/- 0.16, N = 3 SE +/- 0.12, N = 3 33.40 32.90 33.00 33.86
Neural Magic DeepSparse Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream a b c d 8 16 24 32 40 SE +/- 0.43, N = 3 SE +/- 0.14, N = 3 SE +/- 0.11, N = 3 SE +/- 0.39, N = 3 34.87 35.14 34.82 35.10
Neural Magic DeepSparse Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream a b c d 0.665 1.33 1.995 2.66 3.325 SE +/- 0.0247, N = 10 SE +/- 0.0260, N = 9 SE +/- 0.0300, N = 6 SE +/- 0.0208, N = 12 2.9484 2.9500 2.9555 2.9455
Neural Magic DeepSparse Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream a b c d 20 40 60 80 100 SE +/- 0.77, N = 3 SE +/- 0.92, N = 3 SE +/- 0.80, N = 3 SE +/- 0.97, N = 3 74.82 74.94 74.79 75.08
Neural Magic DeepSparse Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Stream a b c d 1.1655 2.331 3.4965 4.662 5.8275 SE +/- 0.0389, N = 12 SE +/- 0.0445, N = 13 SE +/- 0.0500, N = 12 SE +/- 0.0471, N = 12 5.1485 5.1659 5.1802 5.1614
Neural Magic DeepSparse Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream a b c d 12 24 36 48 60 SE +/- 0.63, N = 3 SE +/- 0.60, N = 4 SE +/- 0.62, N = 3 SE +/- 0.70, N = 3 51.93 51.93 51.92 52.07
Neural Magic DeepSparse Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream a b c d 1.1432 2.2864 3.4296 4.5728 5.716 SE +/- 0.0391, N = 12 SE +/- 0.0573, N = 12 SE +/- 0.0484, N = 12 SE +/- 0.0457, N = 8 5.0073 5.0196 5.0179 5.0808
Neural Magic DeepSparse Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream a b c d 80 160 240 320 400 SE +/- 3.00, N = 8 SE +/- 4.19, N = 3 SE +/- 3.47, N = 3 SE +/- 2.84, N = 9 347.66 353.69 359.89 352.22
Neural Magic DeepSparse Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream a b c d 7 14 21 28 35 SE +/- 0.28, N = 7 SE +/- 0.29, N = 6 SE +/- 0.29, N = 6 SE +/- 0.20, N = 12 28.59 28.47 28.55 28.56
Neural Magic DeepSparse Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream a b c d 8 16 24 32 40 SE +/- 0.38, N = 3 SE +/- 0.48, N = 3 SE +/- 0.38, N = 3 SE +/- 0.40, N = 3 33.98 34.08 33.99 34.25
Neural Magic DeepSparse Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream a b c d 3 6 9 12 15 SE +/- 0.01, N = 3 SE +/- 0.03, N = 3 SE +/- 0.02, N = 3 SE +/- 0.08, N = 10 10.36 10.37 10.35 10.45
Neural Magic DeepSparse Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream a b c d 100 200 300 400 500 SE +/- 0.32, N = 3 SE +/- 0.39, N = 3 SE +/- 0.55, N = 3 SE +/- 0.75, N = 3 475.13 474.37 475.35 475.45
Neural Magic DeepSparse Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream a b c d 7 14 21 28 35 SE +/- 0.31, N = 15 SE +/- 0.25, N = 15 SE +/- 0.32, N = 15 SE +/- 0.31, N = 15 31.58 31.73 31.56 30.29
NWChem Input: C240 Buckyball OpenBenchmarking.org Seconds, Fewer Is Better NWChem 7.0.2 Input: C240 Buckyball a b c d 400 800 1200 1600 2000 1744.0 1730.7 1757.3 1748.0 1. (F9X) gfortran options: -lnwctask -lccsd -lmcscf -lselci -lmp2 -lmoints -lstepper -ldriver -loptim -lnwdft -lgradients -lcphf -lesp -lddscf -ldangchang -lguess -lhessian -lvib -lnwcutil -lrimp2 -lproperty -lsolvation -lnwints -lprepar -lnwmd -lnwpw -lofpw -lpaw -lpspw -lband -lnwpwlib -lcafe -lspace -lanalyze -lqhop -lpfft -ldplot -ldrdy -lvscf -lqmmm -lqmd -letrans -ltce -lbq -lmm -lcons -lperfm -ldntmc -lccca -ldimqm -lga -larmci -lpeigs -l64to32 -lopenblas -lpthread -lrt -llapack -lnwcblas -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -levent_core -levent_pthreads -lm -lz -lcomex -m64 -ffast-math -std=legacy -fdefault-integer-8 -finline-functions -O2
WRF Input: conus 2.5km OpenBenchmarking.org Seconds, Fewer Is Better WRF 4.2.2 Input: conus 2.5km a b c d 1200 2400 3600 4800 6000 5566.73 5600.98 5583.11 5617.20 1. (F9X) gfortran options: -O2 -ftree-vectorize -funroll-loops -ffree-form -fconvert=big-endian -frecord-marker=4 -fallow-invalid-boz -lesmf_time -lwrfio_nf -lnetcdff -lnetcdf -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -levent_core -levent_pthreads -lm -lz
Phoronix Test Suite v10.8.4