Intel Xeon Platinum 8490H testing with a Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS) and ASPEED on Ubuntu 22.04 via the Phoronix Test Suite.
Compare your own system(s) to this result file with the
Phoronix Test Suite by running the command:
phoronix-test-suite benchmark 2307296-NE-8490H1S1663 8490h 1s - Phoronix Test Suite 8490h 1s Intel Xeon Platinum 8490H testing with a Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS) and ASPEED on Ubuntu 22.04 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2307296-NE-8490H1S1663&grs&rdt .
8490h 1s Processor Motherboard Chipset Memory Disk Graphics Network OS Kernel Desktop Display Server Vulkan Compiler File-System Screen Resolution a b c d e Intel Xeon Platinum 8490H @ 3.50GHz (60 Cores / 120 Threads) Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS) Intel Device 1bce 512GB 3 x 3841GB Micron_9300_MTFDHAL3T8TDP ASPEED 4 x Intel E810-C for QSFP Ubuntu 22.04 5.15.0-47-generic (x86_64) GNOME Shell 42.4 X Server 1.21.1.3 1.2.204 GCC 11.2.0 ext4 1024x768 OpenBenchmarking.org Kernel Details - Transparent Huge Pages: madvise Compiler Details - --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,brig,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-targets=nvptx-none=/build/gcc-11-gBFGDP/gcc-11-11.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-11-gBFGDP/gcc-11-11.2.0/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 Processor Details - Scaling Governor: intel_pstate performance (EPP: performance) - CPU Microcode: 0x2b0000c0 Java Details - OpenJDK Runtime Environment (build 11.0.16+8-post-Ubuntu-0ubuntu122.04) Python Details - Python 3.10.6 Security Details - itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Enhanced IBRS IBPB: conditional RSB filling + srbds: Not affected + tsx_async_abort: Not affected
8490h 1s cassandra: Writes memtier-benchmark: Redis - 100 - 1:10 deepsparse: ResNet-50, Sparse INT8 - Synchronous Single-Stream deepsparse: ResNet-50, Sparse INT8 - Synchronous Single-Stream memtier-benchmark: Redis - 100 - 1:1 memtier-benchmark: Redis - 50 - 1:5 memtier-benchmark: Redis - 100 - 1:5 memtier-benchmark: Redis - 50 - 1:10 deepsparse: NLP Text Classification, BERT base uncased SST2 - Asynchronous Multi-Stream deepsparse: NLP Text Classification, BERT base uncased SST2 - Asynchronous Multi-Stream deepsparse: NLP Document Classification, oBERT base uncased on IMDB - Asynchronous Multi-Stream memtier-benchmark: Redis - 50 - 1:1 deepsparse: NLP Document Classification, oBERT base uncased on IMDB - Asynchronous Multi-Stream dragonflydb: 10 - 1:5 deepsparse: BERT-Large, NLP Question Answering, Sparse INT8 - Synchronous Single-Stream deepsparse: BERT-Large, NLP Question Answering, Sparse INT8 - Synchronous Single-Stream deepsparse: NLP Text Classification, DistilBERT mnli - Synchronous Single-Stream deepsparse: NLP Text Classification, DistilBERT mnli - Synchronous Single-Stream dragonflydb: 10 - 1:10 deepsparse: CV Classification, ResNet-50 ImageNet - Synchronous Single-Stream deepsparse: CV Classification, ResNet-50 ImageNet - Synchronous Single-Stream deepsparse: NLP Text Classification, DistilBERT mnli - Asynchronous Multi-Stream deepsparse: NLP Text Classification, DistilBERT mnli - Asynchronous Multi-Stream deepsparse: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Synchronous Single-Stream deepsparse: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Synchronous Single-Stream deepsparse: CV Detection, YOLOv5s COCO - Synchronous Single-Stream deepsparse: CV Detection, YOLOv5s COCO - Synchronous Single-Stream deepsparse: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Asynchronous Multi-Stream deepsparse: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Asynchronous Multi-Stream deepsparse: BERT-Large, NLP Question Answering - Asynchronous Multi-Stream deepsparse: ResNet-50, Baseline - Synchronous Single-Stream deepsparse: ResNet-50, Baseline - 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: BERT-Large, NLP Question Answering - Synchronous Single-Stream deepsparse: BERT-Large, NLP Question Answering - Synchronous Single-Stream blender: Fishy Cat - CPU-Only deepsparse: NLP Token Classification, BERT base uncased conll2003 - Asynchronous Multi-Stream deepsparse: NLP Token Classification, BERT base uncased conll2003 - Asynchronous Multi-Stream deepsparse: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Synchronous Single-Stream deepsparse: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Synchronous Single-Stream deepsparse: BERT-Large, NLP Question Answering - Asynchronous Multi-Stream dragonflydb: 10 - 1:100 brl-cad: VGR Performance Metric deepsparse: CV Detection, YOLOv5s COCO, Sparse INT8 - Synchronous Single-Stream deepsparse: CV Detection, YOLOv5s COCO, Sparse INT8 - Synchronous Single-Stream blender: Classroom - CPU-Only 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: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Asynchronous Multi-Stream deepsparse: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Asynchronous Multi-Stream deepsparse: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Asynchronous Multi-Stream blender: Pabellon Barcelona - CPU-Only deepsparse: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Asynchronous Multi-Stream deepsparse: CV Segmentation, 90% Pruned YOLACT Pruned - Synchronous Single-Stream deepsparse: CV Segmentation, 90% Pruned YOLACT Pruned - Synchronous Single-Stream deepsparse: CV Classification, ResNet-50 ImageNet - Asynchronous Multi-Stream blender: BMW27 - CPU-Only deepsparse: CV Classification, ResNet-50 ImageNet - Asynchronous Multi-Stream deepsparse: NLP Text Classification, BERT base uncased SST2 - Synchronous Single-Stream deepsparse: NLP Text Classification, BERT base uncased SST2 - Synchronous Single-Stream deepsparse: NLP Token Classification, BERT base uncased conll2003 - Synchronous Single-Stream deepsparse: NLP Token Classification, BERT base uncased conll2003 - Synchronous Single-Stream deepsparse: CV Segmentation, 90% Pruned YOLACT Pruned - Asynchronous Multi-Stream deepsparse: CV Segmentation, 90% Pruned YOLACT Pruned - Asynchronous Multi-Stream deepsparse: CV Detection, YOLOv5s COCO, Sparse INT8 - Asynchronous Multi-Stream deepsparse: CV Detection, YOLOv5s COCO - Asynchronous Multi-Stream deepsparse: CV Detection, YOLOv5s COCO - Asynchronous Multi-Stream deepsparse: ResNet-50, Baseline - Asynchronous Multi-Stream deepsparse: ResNet-50, Baseline - Asynchronous Multi-Stream deepsparse: CV Detection, YOLOv5s COCO, Sparse INT8 - Asynchronous Multi-Stream deepsparse: BERT-Large, NLP Question Answering, Sparse INT8 - Asynchronous Multi-Stream blender: Barbershop - CPU-Only deepsparse: BERT-Large, NLP Question Answering, Sparse INT8 - Asynchronous Multi-Stream deepsparse: ResNet-50, Sparse INT8 - Asynchronous Multi-Stream deepsparse: ResNet-50, Sparse INT8 - Asynchronous Multi-Stream cryptopp: Unkeyed Algorithms cryptopp: Keyed Algorithms cryptopp: All Algorithms dragonflydb: 20 - 1:5 a b c d e 134694 2929613.17 759.4847 1.3144 2503378.33 2613416.65 2627400.98 2646929.55 137.5084 218.1115 534.5014 2462536.66 56.1193 14247982.45 117.2266 8.5248 121.8864 8.1989 14662941.42 3.7271 267.9943 475.7181 63.0065 86.93 11.4928 184.3867 5.4182 648.3175 46.2475 62.575 3.6608 272.7991 208.9561 4.7834 47.2403 21.1647 35.75 57.076 525.1385 180.141 5.5454 479.125 14338166.15 825917 5.4431 183.6332 68.93 35.4911 28.1702 192.5033 155.8013 15.703 88.73 1905.9808 25.0015 39.9427 780.3982 25.74 38.3944 61.6472 16.2145 35.764 27.9552 396.734 75.6034 86.0393 86.4291 346.9388 38.4127 780.4996 348.5304 868.4975 272.91 34.4904 5672.7993 5.268 452.343734 595.365201 1663.920955 134932 2583878.29 746.7073 1.3371 2630752.03 2546591.86 2710324.97 2544897.58 133.779 224.1648 517.1634 2470315.91 57.7892 14476834.10 114.6147 8.7193 123.6781 8.0804 14292262.52 3.6871 270.8536 487.4646 61.5102 87.1582 11.4653 185.7453 5.3786 644.0495 46.5440 61.5956 3.6961 270.2295 209.1021 4.7802 47.2504 21.1611 35.26 57.5702 520.8695 179.6816 5.5592 486.1851 14432034.21 823602 5.4340 183.9268 69.16 35.3613 28.2735 191.9935 156.2109 15.8316 88.5 1891.0565 24.9917 39.9583 781.3024 25.63 38.3727 61.8913 16.1504 35.7199 27.9897 395.2099 75.8818 85.9332 86.2508 347.6552 38.3371 782.0400 348.7206 869.4702 273.14 34.4634 5678.5152 5.2627 121708 2611551.59 758.3359 1.3167 2460387.75 2516320.69 2554516.65 2508415.59 135.9984 220.4888 517.8375 2377430.14 57.9253 14235868.61 116.3483 8.5903 124.6224 8.019 14204640.25 3.677 271.6229 487.1764 61.546 86.786 11.5118 184.1966 5.4239 649.2977 46.1781 61.4143 3.7248 268.146 208.4283 4.7956 47.4151 21.0871 35.03 57.9918 516.0418 178.7189 5.5886 488.2455 14307949.03 820410 5.4372 183.819 70.03 35.6223 28.0659 191.6104 156.4615 15.8257 88.83 1891.327 25.0071 39.9318 780.3312 25.69 38.4054 61.6088 16.2241 35.8555 27.884 396.6828 75.613 86.2759 86.1641 348.0117 38.4104 780.5294 347.5917 870.7567 272.64 34.4193 5677.035 5.2632 140934 2593991.1 759.4253 1.3146 2493158.97 2452685.99 2549066.22 2487096.51 130.5153 229.4472 511.4186 2383147.07 58.2508 14750102.52 117.2235 8.5255 123.4543 8.0945 14205235.71 3.6743 271.7797 485.7154 61.6935 87.3401 11.4418 184.9319 5.402 648.3864 46.2436 62.1748 3.6938 270.3481 209.6555 4.7675 47.4732 21.0613 35.16 58.2129 514.8982 180.4386 5.5358 482.4354 14571297.77 812806 5.4307 184.047 69.16 35.5925 28.0901 190.8181 157.1756 15.838 88.18 1890.5705 25.0454 39.8698 778.7629 25.75 38.4911 61.8283 16.1666 35.7569 27.9607 396.9936 75.5523 86.2939 86.5253 346.5606 38.422 780.3141 347.5128 871.2052 272.41 34.4017 5665.4699 5.2743 137849 2755166.14 709.1549 1.4076 2474272.95 2444450.11 2541163.68 2540848.35 137.7614 217.7184 520.2239 2414601.07 57.2121 14392511.79 113.2419 8.8247 120.4409 8.2973 14390358.99 3.7788 264.3062 488.2494 61.4194 85.159 11.7345 181.1993 5.5134 633.4455 47.3169 61.0696 3.7499 266.3444 205.2428 4.8699 48.2186 20.736 35.5 57.5236 519.2686 177.0105 5.642 488.2347 14492478.36 822977 5.5183 181.1289 69.25 35.0944 28.488 191.4971 156.5562 15.7168 88.09 1905.1491 25.132 39.7368 782.5439 25.71 38.312 61.8458 16.1614 35.8816 27.8637 396.1651 75.7124 86.1261 86.1663 347.7604 38.2796 783.198 348.1392 870.6664 272.44 34.4226 5679.7805 5.2615 OpenBenchmarking.org
Apache Cassandra Test: Writes OpenBenchmarking.org Op/s, More Is Better Apache Cassandra 4.1.3 Test: Writes a b c d e 30K 60K 90K 120K 150K 134694 134932 121708 140934 137849
Redis 7.0.12 + memtier_benchmark Protocol: Redis - Clients: 100 - Set To Get Ratio: 1:10 OpenBenchmarking.org Ops/sec, More Is Better Redis 7.0.12 + memtier_benchmark 2.0 Protocol: Redis - Clients: 100 - Set To Get Ratio: 1:10 a b c d e 600K 1200K 1800K 2400K 3000K 2929613.17 2583878.29 2611551.59 2593991.10 2755166.14 1. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre
Neural Magic DeepSparse Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.5 Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream a b c d e 160 320 480 640 800 SE +/- 0.65, N = 3 759.48 746.71 758.34 759.43 709.15
Neural Magic DeepSparse Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.5 Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream a b c d e 0.3167 0.6334 0.9501 1.2668 1.5835 SE +/- 0.0011, N = 3 1.3144 1.3371 1.3167 1.3146 1.4076
Redis 7.0.12 + memtier_benchmark Protocol: Redis - Clients: 100 - Set To Get Ratio: 1:1 OpenBenchmarking.org Ops/sec, More Is Better Redis 7.0.12 + memtier_benchmark 2.0 Protocol: Redis - Clients: 100 - Set To Get Ratio: 1:1 a b c d e 600K 1200K 1800K 2400K 3000K 2503378.33 2630752.03 2460387.75 2493158.97 2474272.95 1. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre
Redis 7.0.12 + memtier_benchmark Protocol: Redis - Clients: 50 - Set To Get Ratio: 1:5 OpenBenchmarking.org Ops/sec, More Is Better Redis 7.0.12 + memtier_benchmark 2.0 Protocol: Redis - Clients: 50 - Set To Get Ratio: 1:5 a b c d e 600K 1200K 1800K 2400K 3000K 2613416.65 2546591.86 2516320.69 2452685.99 2444450.11 1. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre
Redis 7.0.12 + memtier_benchmark Protocol: Redis - Clients: 100 - Set To Get Ratio: 1:5 OpenBenchmarking.org Ops/sec, More Is Better Redis 7.0.12 + memtier_benchmark 2.0 Protocol: Redis - Clients: 100 - Set To Get Ratio: 1:5 a b c d e 600K 1200K 1800K 2400K 3000K 2627400.98 2710324.97 2554516.65 2549066.22 2541163.68 1. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre
Redis 7.0.12 + memtier_benchmark Protocol: Redis - Clients: 50 - Set To Get Ratio: 1:10 OpenBenchmarking.org Ops/sec, More Is Better Redis 7.0.12 + memtier_benchmark 2.0 Protocol: Redis - Clients: 50 - Set To Get Ratio: 1:10 a b c d e 600K 1200K 1800K 2400K 3000K 2646929.55 2544897.58 2508415.59 2487096.51 2540848.35 1. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre
Neural Magic DeepSparse Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.5 Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream a b c d e 30 60 90 120 150 137.51 133.78 136.00 130.52 137.76
Neural Magic DeepSparse Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.5 Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream a b c d e 50 100 150 200 250 218.11 224.16 220.49 229.45 217.72
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 1.5 Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream a b c d e 120 240 360 480 600 SE +/- 1.23, N = 3 534.50 517.16 517.84 511.42 520.22
Redis 7.0.12 + memtier_benchmark Protocol: Redis - Clients: 50 - Set To Get Ratio: 1:1 OpenBenchmarking.org Ops/sec, More Is Better Redis 7.0.12 + memtier_benchmark 2.0 Protocol: Redis - Clients: 50 - Set To Get Ratio: 1:1 a b c d e 500K 1000K 1500K 2000K 2500K 2462536.66 2470315.91 2377430.14 2383147.07 2414601.07 1. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre
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 1.5 Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream a b c d e 13 26 39 52 65 SE +/- 0.18, N = 3 56.12 57.79 57.93 58.25 57.21
Dragonflydb Clients Per Thread: 10 - Set To Get Ratio: 1:5 OpenBenchmarking.org Ops/sec, More Is Better Dragonflydb 1.6.2 Clients Per Thread: 10 - Set To Get Ratio: 1:5 a b c d e 3M 6M 9M 12M 15M SE +/- 71046.49, N = 3 14247982.45 14476834.10 14235868.61 14750102.52 14392511.79 1. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre
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 1.5 Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream a b c d e 30 60 90 120 150 117.23 114.61 116.35 117.22 113.24
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 1.5 Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream a b c d e 2 4 6 8 10 8.5248 8.7193 8.5903 8.5255 8.8247
Neural Magic DeepSparse Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.5 Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream a b c d e 30 60 90 120 150 SE +/- 0.43, N = 3 121.89 123.68 124.62 123.45 120.44
Neural Magic DeepSparse Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.5 Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream a b c d e 2 4 6 8 10 SE +/- 0.0280, N = 3 8.1989 8.0804 8.0190 8.0945 8.2973
Dragonflydb Clients Per Thread: 10 - Set To Get Ratio: 1:10 OpenBenchmarking.org Ops/sec, More Is Better Dragonflydb 1.6.2 Clients Per Thread: 10 - Set To Get Ratio: 1:10 a b c d e 3M 6M 9M 12M 15M SE +/- 31999.75, N = 3 14662941.42 14292262.52 14204640.25 14205235.71 14390358.99 1. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre
Neural Magic DeepSparse Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.5 Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream a b c d e 0.8502 1.7004 2.5506 3.4008 4.251 SE +/- 0.0060, N = 3 3.7271 3.6871 3.6770 3.6743 3.7788
Neural Magic DeepSparse Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.5 Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream a b c d e 60 120 180 240 300 SE +/- 0.45, N = 3 267.99 270.85 271.62 271.78 264.31
Neural Magic DeepSparse Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.5 Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream a b c d e 110 220 330 440 550 SE +/- 0.85, N = 3 475.72 487.46 487.18 485.72 488.25
Neural Magic DeepSparse Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.5 Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream a b c d e 14 28 42 56 70 SE +/- 0.11, N = 3 63.01 61.51 61.55 61.69 61.42
Neural Magic DeepSparse Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.5 Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream a b c d e 20 40 60 80 100 SE +/- 0.09, N = 3 86.93 87.16 86.79 87.34 85.16
Neural Magic DeepSparse Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.5 Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream a b c d e 3 6 9 12 15 SE +/- 0.01, N = 3 11.49 11.47 11.51 11.44 11.73
Neural Magic DeepSparse Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.5 Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream a b c d e 40 80 120 160 200 SE +/- 0.69, N = 3 184.39 185.75 184.20 184.93 181.20
Neural Magic DeepSparse Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.5 Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream a b c d e 1.2405 2.481 3.7215 4.962 6.2025 SE +/- 0.0199, N = 3 5.4182 5.3786 5.4239 5.4020 5.5134
Neural Magic DeepSparse Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.5 Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream a b c d e 140 280 420 560 700 SE +/- 5.86, N = 3 648.32 644.05 649.30 648.39 633.45
Neural Magic DeepSparse Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.5 Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream a b c d e 11 22 33 44 55 SE +/- 0.41, N = 3 46.25 46.54 46.18 46.24 47.32
Neural Magic DeepSparse Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.5 Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream a b c d e 14 28 42 56 70 SE +/- 0.44, N = 3 62.58 61.60 61.41 62.17 61.07
Neural Magic DeepSparse Model: ResNet-50, Baseline - Scenario: Synchronous Single-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.5 Model: ResNet-50, Baseline - Scenario: Synchronous Single-Stream a b c d e 0.8437 1.6874 2.5311 3.3748 4.2185 SE +/- 0.0089, N = 3 3.6608 3.6961 3.7248 3.6938 3.7499
Neural Magic DeepSparse Model: ResNet-50, Baseline - Scenario: Synchronous Single-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.5 Model: ResNet-50, Baseline - Scenario: Synchronous Single-Stream a b c d e 60 120 180 240 300 SE +/- 0.64, N = 3 272.80 270.23 268.15 270.35 266.34
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 1.5 Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Stream a b c d e 50 100 150 200 250 SE +/- 0.71, N = 3 208.96 209.10 208.43 209.66 205.24
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 1.5 Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Stream a b c d e 1.0957 2.1914 3.2871 4.3828 5.4785 SE +/- 0.0162, N = 3 4.7834 4.7802 4.7956 4.7675 4.8699
Neural Magic DeepSparse Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.5 Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Stream a b c d e 11 22 33 44 55 SE +/- 0.16, N = 3 47.24 47.25 47.42 47.47 48.22
Neural Magic DeepSparse Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.5 Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Stream a b c d e 5 10 15 20 25 SE +/- 0.07, N = 3 21.16 21.16 21.09 21.06 20.74
Blender Blend File: Fishy Cat - Compute: CPU-Only OpenBenchmarking.org Seconds, Fewer Is Better Blender 3.6 Blend File: Fishy Cat - Compute: CPU-Only a b c d e 8 16 24 32 40 35.75 35.26 35.03 35.16 35.50
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 1.5 Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream a b c d e 13 26 39 52 65 57.08 57.57 57.99 58.21 57.52
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 1.5 Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream a b c d e 110 220 330 440 550 525.14 520.87 516.04 514.90 519.27
Neural Magic DeepSparse Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Synchronous Single-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.5 Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Synchronous Single-Stream a b c d e 40 80 120 160 200 SE +/- 0.21, N = 3 180.14 179.68 178.72 180.44 177.01
Neural Magic DeepSparse Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Synchronous Single-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.5 Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Synchronous Single-Stream a b c d e 1.2695 2.539 3.8085 5.078 6.3475 SE +/- 0.0064, N = 3 5.5454 5.5592 5.5886 5.5358 5.6420
Neural Magic DeepSparse Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.5 Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream a b c d e 110 220 330 440 550 SE +/- 2.68, N = 3 479.13 486.19 488.25 482.44 488.23
Dragonflydb Clients Per Thread: 10 - Set To Get Ratio: 1:100 OpenBenchmarking.org Ops/sec, More Is Better Dragonflydb 1.6.2 Clients Per Thread: 10 - Set To Get Ratio: 1:100 a b c d e 3M 6M 9M 12M 15M SE +/- 145332.09, N = 3 14338166.15 14432034.21 14307949.03 14571297.77 14492478.36 1. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre
BRL-CAD VGR Performance Metric OpenBenchmarking.org VGR Performance Metric, More Is Better BRL-CAD 7.36 VGR Performance Metric a b c d e 200K 400K 600K 800K 1000K 825917 823602 820410 812806 822977 1. (CXX) g++ options: -std=c++14 -pipe -fvisibility=hidden -fno-strict-aliasing -fno-common -fexceptions -ftemplate-depth-128 -m64 -ggdb3 -O3 -fipa-pta -fstrength-reduce -finline-functions -flto -ltcl8.6 -lregex_brl -lz_brl -lnetpbm -ldl -lm -ltk8.6
Neural Magic DeepSparse Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.5 Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Stream a b c d e 1.2416 2.4832 3.7248 4.9664 6.208 SE +/- 0.0092, N = 3 5.4431 5.4340 5.4372 5.4307 5.5183
Neural Magic DeepSparse Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.5 Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Stream a b c d e 40 80 120 160 200 SE +/- 0.31, N = 3 183.63 183.93 183.82 184.05 181.13
Blender Blend File: Classroom - Compute: CPU-Only OpenBenchmarking.org Seconds, Fewer Is Better Blender 3.6 Blend File: Classroom - Compute: CPU-Only a b c d e 16 32 48 64 80 68.93 69.16 70.03 69.16 69.25
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 1.5 Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream a b c d e 8 16 24 32 40 SE +/- 0.07, N = 3 35.49 35.36 35.62 35.59 35.09
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 1.5 Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream a b c d e 7 14 21 28 35 SE +/- 0.05, N = 3 28.17 28.27 28.07 28.09 28.49
Neural Magic DeepSparse Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.5 Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream a b c d e 40 80 120 160 200 SE +/- 0.10, N = 3 192.50 191.99 191.61 190.82 191.50
Neural Magic DeepSparse Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.5 Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream a b c d e 30 60 90 120 150 SE +/- 0.08, N = 3 155.80 156.21 156.46 157.18 156.56
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 1.5 Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream a b c d e 4 8 12 16 20 SE +/- 0.01, N = 3 15.70 15.83 15.83 15.84 15.72
Blender Blend File: Pabellon Barcelona - Compute: CPU-Only OpenBenchmarking.org Seconds, Fewer Is Better Blender 3.6 Blend File: Pabellon Barcelona - Compute: CPU-Only a b c d e 20 40 60 80 100 88.73 88.50 88.83 88.18 88.09
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 1.5 Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream a b c d e 400 800 1200 1600 2000 SE +/- 1.24, N = 3 1905.98 1891.06 1891.33 1890.57 1905.15
Neural Magic DeepSparse Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.5 Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream a b c d e 6 12 18 24 30 SE +/- 0.00, N = 3 25.00 24.99 25.01 25.05 25.13
Neural Magic DeepSparse Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.5 Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream a b c d e 9 18 27 36 45 SE +/- 0.01, N = 3 39.94 39.96 39.93 39.87 39.74
Neural Magic DeepSparse Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.5 Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream a b c d e 200 400 600 800 1000 SE +/- 0.42, N = 3 780.40 781.30 780.33 778.76 782.54
Blender Blend File: BMW27 - Compute: CPU-Only OpenBenchmarking.org Seconds, Fewer Is Better Blender 3.6 Blend File: BMW27 - Compute: CPU-Only a b c d e 6 12 18 24 30 25.74 25.63 25.69 25.75 25.71
Neural Magic DeepSparse Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.5 Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream a b c d e 9 18 27 36 45 SE +/- 0.02, N = 3 38.39 38.37 38.41 38.49 38.31
Neural Magic DeepSparse Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.5 Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Stream a b c d e 14 28 42 56 70 61.65 61.89 61.61 61.83 61.85
Neural Magic DeepSparse Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.5 Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Stream a b c d e 4 8 12 16 20 16.21 16.15 16.22 16.17 16.16
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 1.5 Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream a b c d e 8 16 24 32 40 35.76 35.72 35.86 35.76 35.88
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 1.5 Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream a b c d e 7 14 21 28 35 27.96 27.99 27.88 27.96 27.86
Neural Magic DeepSparse Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.5 Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream a b c d e 90 180 270 360 450 SE +/- 1.22, N = 3 396.73 395.21 396.68 396.99 396.17
Neural Magic DeepSparse Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.5 Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream a b c d e 20 40 60 80 100 SE +/- 0.23, N = 3 75.60 75.88 75.61 75.55 75.71
Neural Magic DeepSparse Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.5 Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream a b c d e 20 40 60 80 100 SE +/- 0.14, N = 3 86.04 85.93 86.28 86.29 86.13
Neural Magic DeepSparse Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.5 Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream a b c d e 20 40 60 80 100 SE +/- 0.08, N = 3 86.43 86.25 86.16 86.53 86.17
Neural Magic DeepSparse Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.5 Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream a b c d e 80 160 240 320 400 SE +/- 0.33, N = 3 346.94 347.66 348.01 346.56 347.76
Neural Magic DeepSparse Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.5 Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream a b c d e 9 18 27 36 45 SE +/- 0.04, N = 3 38.41 38.34 38.41 38.42 38.28
Neural Magic DeepSparse Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.5 Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream a b c d e 200 400 600 800 1000 SE +/- 0.80, N = 3 780.50 782.04 780.53 780.31 783.20
Neural Magic DeepSparse Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.5 Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream a b c d e 80 160 240 320 400 SE +/- 0.57, N = 3 348.53 348.72 347.59 347.51 348.14
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 1.5 Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream a b c d e 200 400 600 800 1000 SE +/- 0.53, N = 3 868.50 869.47 870.76 871.21 870.67
Blender Blend File: Barbershop - Compute: CPU-Only OpenBenchmarking.org Seconds, Fewer Is Better Blender 3.6 Blend File: Barbershop - Compute: CPU-Only a b c d e 60 120 180 240 300 272.91 273.14 272.64 272.41 272.44
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 1.5 Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream a b c d e 8 16 24 32 40 SE +/- 0.02, N = 3 34.49 34.46 34.42 34.40 34.42
Neural Magic DeepSparse Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.5 Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream a b c d e 1200 2400 3600 4800 6000 SE +/- 3.30, N = 3 5672.80 5678.52 5677.04 5665.47 5679.78
Neural Magic DeepSparse Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.5 Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream a b c d e 1.1867 2.3734 3.5601 4.7468 5.9335 SE +/- 0.0032, N = 3 5.2680 5.2627 5.2632 5.2743 5.2615
Crypto++ Test: Unkeyed Algorithms OpenBenchmarking.org MiB/second, More Is Better Crypto++ 8.8 Test: Unkeyed Algorithms a 100 200 300 400 500 452.34 1. (CXX) g++ options: -g2 -O3 -fPIC -pthread -pipe
Crypto++ Test: Keyed Algorithms OpenBenchmarking.org MiB/second, More Is Better Crypto++ 8.8 Test: Keyed Algorithms a 130 260 390 520 650 595.37 1. (CXX) g++ options: -g2 -O3 -fPIC -pthread -pipe
Crypto++ Test: All Algorithms OpenBenchmarking.org MiB/second, More Is Better Crypto++ 8.8 Test: All Algorithms a 400 800 1200 1600 2000 1663.92 1. (CXX) g++ options: -g2 -O3 -fPIC -pthread -pipe
Phoronix Test Suite v10.8.4