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&export=pdf&grr&sro&rro .
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 wrf: conus 2.5km nwchem: C240 Buckyball deepsparse: NLP Token Classification, BERT base uncased conll2003 - Synchronous Single-Stream deepsparse: NLP Token Classification, BERT base uncased conll2003 - Synchronous Single-Stream deepsparse: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Synchronous Single-Stream deepsparse: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Synchronous Single-Stream deepsparse: NLP Document Classification, oBERT base uncased on IMDB - Synchronous Single-Stream deepsparse: NLP Document Classification, oBERT base uncased on IMDB - Synchronous Single-Stream deepsparse: CV Detection, YOLOv5s COCO, Sparse INT8 - Synchronous Single-Stream deepsparse: CV Detection, YOLOv5s COCO, Sparse INT8 - Synchronous Single-Stream deepsparse: NLP Text Classification, DistilBERT mnli - Synchronous Single-Stream deepsparse: NLP Text Classification, DistilBERT mnli - Synchronous Single-Stream deepsparse: CV Detection, YOLOv5s COCO - Synchronous Single-Stream deepsparse: CV Detection, YOLOv5s COCO - Synchronous Single-Stream deepsparse: ResNet-50, Sparse INT8 - Asynchronous Multi-Stream deepsparse: ResNet-50, Sparse INT8 - Asynchronous Multi-Stream deepsparse: ResNet-50, Baseline - Synchronous Single-Stream deepsparse: ResNet-50, Baseline - Synchronous Single-Stream deepsparse: CV Classification, ResNet-50 ImageNet - Synchronous Single-Stream deepsparse: CV Classification, ResNet-50 ImageNet - Synchronous Single-Stream deepsparse: CV Segmentation, 90% Pruned YOLACT Pruned - Synchronous Single-Stream deepsparse: CV Segmentation, 90% Pruned YOLACT Pruned - Synchronous Single-Stream deepsparse: BERT-Large, NLP Question Answering - Synchronous Single-Stream deepsparse: BERT-Large, NLP Question Answering - 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 - Asynchronous Multi-Stream deepsparse: BERT-Large, NLP Question Answering - Asynchronous Multi-Stream deepsparse: BERT-Large, NLP Question Answering - Asynchronous Multi-Stream deepsparse: CV Segmentation, 90% Pruned YOLACT Pruned - Asynchronous Multi-Stream deepsparse: CV Segmentation, 90% Pruned YOLACT Pruned - Asynchronous Multi-Stream deepsparse: BERT-Large, NLP Question Answering, Sparse INT8 - Synchronous Single-Stream deepsparse: BERT-Large, NLP Question Answering, Sparse INT8 - Synchronous Single-Stream deepsparse: ResNet-50, Sparse INT8 - Synchronous Single-Stream deepsparse: ResNet-50, Sparse INT8 - Synchronous Single-Stream deepsparse: NLP Document Classification, oBERT base uncased on IMDB - Asynchronous Multi-Stream deepsparse: NLP Document Classification, oBERT base uncased on IMDB - Asynchronous Multi-Stream deepsparse: NLP Token Classification, BERT base uncased conll2003 - Asynchronous Multi-Stream deepsparse: NLP Token Classification, BERT base uncased conll2003 - Asynchronous Multi-Stream deepsparse: BERT-Large, NLP Question Answering, Sparse INT8 - Asynchronous Multi-Stream deepsparse: BERT-Large, NLP Question Answering, Sparse INT8 - Asynchronous Multi-Stream deepsparse: NLP Text Classification, DistilBERT mnli - Asynchronous Multi-Stream deepsparse: NLP Text Classification, DistilBERT mnli - Asynchronous Multi-Stream deepsparse: ResNet-50, Baseline - Asynchronous Multi-Stream deepsparse: ResNet-50, Baseline - Asynchronous Multi-Stream deepsparse: CV Detection, YOLOv5s COCO - Asynchronous Multi-Stream deepsparse: CV Detection, YOLOv5s COCO - Asynchronous Multi-Stream deepsparse: CV Classification, ResNet-50 ImageNet - Asynchronous Multi-Stream deepsparse: CV Classification, ResNet-50 ImageNet - Asynchronous Multi-Stream deepsparse: CV Detection, YOLOv5s COCO, Sparse INT8 - Asynchronous Multi-Stream deepsparse: CV Detection, YOLOv5s COCO, Sparse INT8 - Asynchronous Multi-Stream a b c d 5566.729 1744 31.5821 31.6954 4.2083 238.6523 32.0613 31.1945 5.1485 194.2476 5.0073 199.6930 5.2382 190.8420 5.6852 11228.6625 2.9492 338.9562 2.9484 339.0416 28.5876 34.9620 33.4022 29.9421 14.0362 4554.9796 407.2777 156.0563 347.6637 183.4966 10.3634 96.4300 0.9681 1030.3181 475.6964 133.5159 475.1265 133.6023 33.9808 1880.7688 51.9301 1231.2049 34.9169 1829.9644 77.1758 828.0384 34.8681 1832.7927 74.8177 854.0525 5600.976 1730.7 31.7303 31.5332 4.2295 237.0460 32.0368 31.2336 5.1659 193.5972 5.0196 199.3380 5.2617 190.0399 5.7140 11169.8517 2.9602 337.6799 2.9500 338.8583 28.4701 35.1065 32.8989 30.3891 14.0081 4563.5097 408.6263 155.7222 353.6889 180.3157 10.3695 96.3790 0.9706 1027.5117 474.1852 133.7189 474.3687 133.8239 34.0815 1875.9035 51.9273 1231.2939 35.0063 1824.3759 77.0924 828.6532 35.1423 1817.9939 74.9435 852.9455 5583.112 1757.3 31.5618 31.7202 4.3436 230.7640 31.6501 31.6300 5.1802 193.0872 5.0179 199.3323 5.2651 189.8175 5.7165 11163.6593 2.9530 338.5536 2.9555 338.2192 28.5521 35.0057 32.9984 30.2944 14.0090 4563.4278 408.9699 155.7677 359.8919 177.1512 10.3507 96.5474 0.9556 1043.2804 475.6804 133.4843 475.3497 133.6004 33.9939 1879.8388 51.9192 1231.2736 34.9683 1827.9780 77.1235 828.4462 34.8217 1834.4771 74.7945 854.2521 5617.197 1748 30.2891 33.0540 4.1604 240.2336 30.4222 32.8936 5.1614 193.8186 5.0808 196.7874 5.2589 190.1376 5.6908 11221.1357 2.9573 338.1466 2.9455 339.3671 28.5586 34.9987 33.8635 29.5231 14.0315 4556.0233 408.1638 155.6020 352.2235 181.2029 10.4501 95.6981 0.9667 1032.2410 477.6108 133.0079 475.4464 133.5969 34.2508 1865.0193 52.0706 1226.7960 34.7567 1837.4977 77.4573 825.0841 35.1013 1819.6861 75.0848 850.8926 OpenBenchmarking.org
WRF Input: conus 2.5km OpenBenchmarking.org Seconds, Fewer Is Better WRF 4.2.2 Input: conus 2.5km d c b a 1200 2400 3600 4800 6000 5617.20 5583.11 5600.98 5566.73 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
NWChem Input: C240 Buckyball OpenBenchmarking.org Seconds, Fewer Is Better NWChem 7.0.2 Input: C240 Buckyball d c b a 400 800 1200 1600 2000 1748.0 1757.3 1730.7 1744.0 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
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 d c b a 7 14 21 28 35 SE +/- 0.31, N = 15 SE +/- 0.32, N = 15 SE +/- 0.25, N = 15 SE +/- 0.31, N = 15 30.29 31.56 31.73 31.58
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 d c b a 8 16 24 32 40 SE +/- 0.33, N = 15 SE +/- 0.33, N = 15 SE +/- 0.25, N = 15 SE +/- 0.31, N = 15 33.05 31.72 31.53 31.70
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 d c b a 0.9773 1.9546 2.9319 3.9092 4.8865 SE +/- 0.0540, N = 3 SE +/- 0.0661, N = 15 SE +/- 0.0666, N = 15 SE +/- 0.0821, N = 15 4.1604 4.3436 4.2295 4.2083
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 d c b a 50 100 150 200 250 SE +/- 3.16, N = 3 SE +/- 3.66, N = 15 SE +/- 3.82, N = 15 SE +/- 4.61, N = 15 240.23 230.76 237.05 238.65
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 d c b a 7 14 21 28 35 SE +/- 0.25, N = 15 SE +/- 0.32, N = 15 SE +/- 0.27, N = 15 SE +/- 0.40, N = 4 30.42 31.65 32.04 32.06
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 d c b a 8 16 24 32 40 SE +/- 0.26, N = 15 SE +/- 0.32, N = 15 SE +/- 0.25, N = 15 SE +/- 0.38, N = 4 32.89 31.63 31.23 31.19
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 d c b a 1.1655 2.331 3.4965 4.662 5.8275 SE +/- 0.0471, N = 12 SE +/- 0.0500, N = 12 SE +/- 0.0445, N = 13 SE +/- 0.0389, N = 12 5.1614 5.1802 5.1659 5.1485
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 d c b a 40 80 120 160 200 SE +/- 1.62, N = 12 SE +/- 1.70, N = 12 SE +/- 1.53, N = 13 SE +/- 1.36, N = 12 193.82 193.09 193.60 194.25
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 d c b a 1.1432 2.2864 3.4296 4.5728 5.716 SE +/- 0.0457, N = 8 SE +/- 0.0484, N = 12 SE +/- 0.0573, N = 12 SE +/- 0.0391, N = 12 5.0808 5.0179 5.0196 5.0073
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 d c b a 40 80 120 160 200 SE +/- 1.69, N = 8 SE +/- 1.76, N = 12 SE +/- 2.05, N = 12 SE +/- 1.45, N = 12 196.79 199.33 199.34 199.69
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 d c b a 1.1846 2.3692 3.5538 4.7384 5.923 SE +/- 0.0457, N = 12 SE +/- 0.0492, N = 7 SE +/- 0.0526, N = 12 SE +/- 0.0382, N = 12 5.2589 5.2651 5.2617 5.2382
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 d c b a 40 80 120 160 200 SE +/- 1.52, N = 12 SE +/- 1.69, N = 7 SE +/- 1.73, N = 12 SE +/- 1.29, N = 12 190.14 189.82 190.04 190.84
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 d c b a 1.2862 2.5724 3.8586 5.1448 6.431 SE +/- 0.0425, N = 12 SE +/- 0.0544, N = 7 SE +/- 0.0484, N = 9 SE +/- 0.0393, N = 13 5.6908 5.7165 5.7140 5.6852
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 d c b a 2K 4K 6K 8K 10K SE +/- 77.36, N = 12 SE +/- 101.43, N = 7 SE +/- 89.80, N = 9 SE +/- 71.77, N = 13 11221.14 11163.66 11169.85 11228.66
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 d c b a 0.666 1.332 1.998 2.664 3.33 SE +/- 0.0282, N = 12 SE +/- 0.0242, N = 12 SE +/- 0.0315, N = 6 SE +/- 0.0255, N = 9 2.9573 2.9530 2.9602 2.9492
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 d c b a 70 140 210 280 350 SE +/- 2.94, N = 12 SE +/- 2.56, N = 12 SE +/- 3.44, N = 6 SE +/- 2.76, N = 9 338.15 338.55 337.68 338.96
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 d c b a 0.665 1.33 1.995 2.66 3.325 SE +/- 0.0208, N = 12 SE +/- 0.0300, N = 6 SE +/- 0.0260, N = 9 SE +/- 0.0247, N = 10 2.9455 2.9555 2.9500 2.9484
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 d c b a 70 140 210 280 350 SE +/- 2.24, N = 12 SE +/- 3.30, N = 6 SE +/- 2.82, N = 9 SE +/- 2.66, N = 10 339.37 338.22 338.86 339.04
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 d c b a 7 14 21 28 35 SE +/- 0.20, N = 12 SE +/- 0.29, N = 6 SE +/- 0.29, N = 6 SE +/- 0.28, N = 7 28.56 28.55 28.47 28.59
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 d c b a 8 16 24 32 40 SE +/- 0.23, N = 12 SE +/- 0.35, N = 6 SE +/- 0.34, N = 6 SE +/- 0.33, N = 7 35.00 35.01 35.11 34.96
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 d c b a 8 16 24 32 40 SE +/- 0.12, N = 3 SE +/- 0.16, N = 3 SE +/- 0.30, N = 3 SE +/- 0.34, N = 6 33.86 33.00 32.90 33.40
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 d c b a 7 14 21 28 35 SE +/- 0.10, N = 3 SE +/- 0.15, N = 3 SE +/- 0.27, N = 3 SE +/- 0.30, N = 6 29.52 30.29 30.39 29.94
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 d c b a 4 8 12 16 20 SE +/- 0.14, N = 6 SE +/- 0.14, N = 6 SE +/- 0.13, N = 7 SE +/- 0.16, N = 5 14.03 14.01 14.01 14.04
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 d c b a 1000 2000 3000 4000 5000 SE +/- 42.83, N = 6 SE +/- 43.60, N = 6 SE +/- 40.39, N = 7 SE +/- 49.40, N = 5 4556.02 4563.43 4563.51 4554.98
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 d c b a 90 180 270 360 450 SE +/- 2.06, N = 3 SE +/- 2.55, N = 3 SE +/- 1.91, N = 3 SE +/- 1.62, N = 3 408.16 408.97 408.63 407.28
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 d c b a 30 60 90 120 150 SE +/- 1.10, N = 3 SE +/- 1.19, N = 3 SE +/- 0.66, N = 3 SE +/- 0.66, N = 3 155.60 155.77 155.72 156.06
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 d c b a 80 160 240 320 400 SE +/- 2.84, N = 9 SE +/- 3.47, N = 3 SE +/- 4.19, N = 3 SE +/- 3.00, N = 8 352.22 359.89 353.69 347.66
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 d c b a 40 80 120 160 200 SE +/- 1.48, N = 9 SE +/- 1.83, N = 3 SE +/- 2.09, N = 3 SE +/- 1.57, N = 8 181.20 177.15 180.32 183.50
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 d c b a 3 6 9 12 15 SE +/- 0.08, N = 10 SE +/- 0.02, N = 3 SE +/- 0.03, N = 3 SE +/- 0.01, N = 3 10.45 10.35 10.37 10.36
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 d c b a 20 40 60 80 100 SE +/- 0.72, N = 10 SE +/- 0.16, N = 3 SE +/- 0.30, N = 3 SE +/- 0.11, N = 3 95.70 96.55 96.38 96.43
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 d c b a 0.2184 0.4368 0.6552 0.8736 1.092 SE +/- 0.0094, N = 7 SE +/- 0.0048, N = 3 SE +/- 0.0090, N = 3 SE +/- 0.0105, N = 4 0.9667 0.9556 0.9706 0.9681
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 d c b a 200 400 600 800 1000 SE +/- 9.64, N = 7 SE +/- 5.37, N = 3 SE +/- 9.47, N = 3 SE +/- 11.12, N = 4 1032.24 1043.28 1027.51 1030.32
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 d c b a 100 200 300 400 500 SE +/- 0.44, N = 3 SE +/- 0.52, N = 3 SE +/- 0.47, N = 3 SE +/- 0.61, N = 3 477.61 475.68 474.19 475.70
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 d c b a 30 60 90 120 150 SE +/- 0.11, N = 3 SE +/- 0.16, N = 3 SE +/- 0.13, N = 3 SE +/- 0.15, N = 3 133.01 133.48 133.72 133.52
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 d c b a 100 200 300 400 500 SE +/- 0.75, N = 3 SE +/- 0.55, N = 3 SE +/- 0.39, N = 3 SE +/- 0.32, N = 3 475.45 475.35 474.37 475.13
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 d c b a 30 60 90 120 150 SE +/- 0.26, N = 3 SE +/- 0.19, N = 3 SE +/- 0.14, N = 3 SE +/- 0.13, N = 3 133.60 133.60 133.82 133.60
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 d c b a 8 16 24 32 40 SE +/- 0.40, N = 3 SE +/- 0.38, N = 3 SE +/- 0.48, N = 3 SE +/- 0.38, N = 3 34.25 33.99 34.08 33.98
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 d c b a 400 800 1200 1600 2000 SE +/- 21.54, N = 3 SE +/- 21.19, N = 3 SE +/- 26.46, N = 3 SE +/- 21.42, N = 3 1865.02 1879.84 1875.90 1880.77
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 d c b a 12 24 36 48 60 SE +/- 0.70, N = 3 SE +/- 0.62, N = 3 SE +/- 0.60, N = 4 SE +/- 0.63, N = 3 52.07 51.92 51.93 51.93
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 d c b a 300 600 900 1200 1500 SE +/- 17.38, N = 3 SE +/- 13.91, N = 3 SE +/- 14.60, N = 4 SE +/- 14.83, N = 3 1226.80 1231.27 1231.29 1231.20
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 d c b a 8 16 24 32 40 SE +/- 0.29, N = 3 SE +/- 0.35, N = 3 SE +/- 0.25, N = 3 SE +/- 0.08, N = 3 34.76 34.97 35.01 34.92
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 d c b a 400 800 1200 1600 2000 SE +/- 14.66, N = 3 SE +/- 17.94, N = 3 SE +/- 13.19, N = 3 SE +/- 4.85, N = 3 1837.50 1827.98 1824.38 1829.96
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 d c b a 20 40 60 80 100 SE +/- 0.87, N = 3 SE +/- 0.64, N = 3 SE +/- 0.63, N = 3 SE +/- 0.70, N = 3 77.46 77.12 77.09 77.18
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 d c b a 200 400 600 800 1000 SE +/- 9.22, N = 3 SE +/- 6.81, N = 3 SE +/- 6.37, N = 3 SE +/- 7.51, N = 3 825.08 828.45 828.65 828.04
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 d c b a 8 16 24 32 40 SE +/- 0.39, N = 3 SE +/- 0.11, N = 3 SE +/- 0.14, N = 3 SE +/- 0.43, N = 3 35.10 34.82 35.14 34.87
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 d c b a 400 800 1200 1600 2000 SE +/- 21.20, N = 3 SE +/- 5.61, N = 3 SE +/- 7.71, N = 3 SE +/- 22.80, N = 3 1819.69 1834.48 1817.99 1832.79
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 d c b a 20 40 60 80 100 SE +/- 0.97, N = 3 SE +/- 0.80, N = 3 SE +/- 0.92, N = 3 SE +/- 0.77, N = 3 75.08 74.79 74.94 74.82
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 d c b a 200 400 600 800 1000 SE +/- 10.96, N = 3 SE +/- 9.10, N = 3 SE +/- 10.26, N = 3 SE +/- 8.70, N = 3 850.89 854.25 852.95 854.05
Phoronix Test Suite v10.8.4