eps Tests for a future article. 2 x AMD EPYC 9684X 96-Core testing with a AMD Titanite_4G (RTI1007B BIOS) and ASPEED on Ubuntu 23.10 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2312240-NE-EPS17737430&sro&grw .
eps Processor Motherboard Chipset Memory Disk Graphics Network OS Kernel Compiler File-System Screen Resolution a b 2 x AMD EPYC 9684X 96-Core @ 2.55GHz (192 Cores / 384 Threads) AMD Titanite_4G (RTI1007B BIOS) AMD Device 14a4 1520GB 3201GB Micron_7450_MTFDKCB3T2TFS ASPEED Broadcom NetXtreme BCM5720 PCIe Ubuntu 23.10 6.5.0-13-generic (x86_64) GCC 13.2.0 ext4 800x600 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,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 Processor Details - Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0xa10113e Java Details - OpenJDK Runtime Environment (build 11.0.21+9-post-Ubuntu-0ubuntu123.10) 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: Mitigation of safe RET + 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 STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected
eps java-scimark2: Composite java-scimark2: Monte Carlo java-scimark2: Fast Fourier Transform java-scimark2: Sparse Matrix Multiply java-scimark2: Dense LU Matrix Factorization java-scimark2: Jacobi Successive Over-Relaxation webp2: Default webp2: Quality 75, Compression Effort 7 webp2: Quality 95, Compression Effort 7 webp2: Quality 100, Compression Effort 5 webp2: Quality 100, Lossless Compression xmrig: KawPow - 1M xmrig: Monero - 1M xmrig: Wownero - 1M xmrig: GhostRider - 1M xmrig: CryptoNight-Heavy - 1M xmrig: CryptoNight-Femto UPX2 - 1M lczero: BLAS lczero: Eigen deepsparse: NLP Document Classification, oBERT base uncased on IMDB - Asynchronous Multi-Stream openssl: SHA256 openssl: RSA4096 openssl: SHA512 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 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 - Asynchronous Multi-Stream deepsparse: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Synchronous Single-Stream openssl: RSA4096 deepsparse: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Synchronous Single-Stream deepsparse: ResNet-50, Baseline - Asynchronous Multi-Stream deepsparse: ResNet-50, Baseline - Asynchronous Multi-Stream deepsparse: ResNet-50, Baseline - Synchronous Single-Stream deepsparse: ResNet-50, Baseline - Synchronous Single-Stream deepsparse: ResNet-50, Sparse INT8 - Asynchronous Multi-Stream deepsparse: ResNet-50, Sparse INT8 - Asynchronous Multi-Stream deepsparse: ResNet-50, Sparse INT8 - Synchronous Single-Stream deepsparse: ResNet-50, Sparse INT8 - Synchronous Single-Stream deepsparse: CV Detection, YOLOv5s COCO - Asynchronous Multi-Stream deepsparse: CV Detection, YOLOv5s COCO - Asynchronous Multi-Stream deepsparse: CV Detection, YOLOv5s COCO - Synchronous Single-Stream deepsparse: CV Detection, YOLOv5s COCO - Synchronous Single-Stream deepsparse: BERT-Large, NLP Question Answering - Asynchronous Multi-Stream deepsparse: BERT-Large, NLP Question Answering - Asynchronous Multi-Stream deepsparse: BERT-Large, NLP Question Answering - Synchronous Single-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 - Asynchronous Multi-Stream deepsparse: CV Classification, ResNet-50 ImageNet - Synchronous Single-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 - Asynchronous Multi-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 - Asynchronous Multi-Stream deepsparse: NLP Text Classification, DistilBERT mnli - Asynchronous Multi-Stream deepsparse: NLP Text Classification, DistilBERT mnli - Synchronous Single-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 - Asynchronous Multi-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, Sparse INT8 - Asynchronous Multi-Stream deepsparse: BERT-Large, NLP Question Answering, Sparse INT8 - 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: NLP Token Classification, BERT base uncased conll2003 - Asynchronous Multi-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 Token Classification, BERT base uncased conll2003 - Synchronous Single-Stream pytorch: CPU - 1 - ResNet-50 pytorch: CPU - 1 - ResNet-152 pytorch: CPU - 16 - ResNet-50 pytorch: CPU - 32 - ResNet-50 pytorch: CPU - 16 - ResNet-152 pytorch: CPU - 256 - ResNet-50 pytorch: CPU - 32 - ResNet-152 pytorch: CPU - 256 - ResNet-152 pytorch: CPU - 1 - Efficientnet_v2_l pytorch: CPU - 16 - Efficientnet_v2_l pytorch: CPU - 32 - Efficientnet_v2_l pytorch: CPU - 256 - Efficientnet_v2_l svt-av1: Preset 4 - Bosphorus 4K svt-av1: Preset 8 - Bosphorus 4K svt-av1: Preset 12 - Bosphorus 4K svt-av1: Preset 13 - Bosphorus 4K svt-av1: Preset 4 - Bosphorus 1080p svt-av1: Preset 8 - Bosphorus 1080p svt-av1: Preset 12 - Bosphorus 1080p svt-av1: Preset 13 - Bosphorus 1080p spark-tpch: 1 - Geometric Mean Of All Queries spark-tpch: 10 - Geometric Mean Of All Queries spark-tpch: 50 - Geometric Mean Of All Queries spark-tpch: 1 - Q01 spark-tpch: 1 - Q02 spark-tpch: 1 - Q03 spark-tpch: 1 - Q04 spark-tpch: 1 - Q05 spark-tpch: 1 - Q06 spark-tpch: 1 - Q07 spark-tpch: 1 - Q08 spark-tpch: 1 - Q09 spark-tpch: 1 - Q10 spark-tpch: 1 - Q11 spark-tpch: 1 - Q12 spark-tpch: 1 - Q13 spark-tpch: 1 - Q14 spark-tpch: 1 - Q15 spark-tpch: 1 - Q16 spark-tpch: 1 - Q17 spark-tpch: 1 - Q18 spark-tpch: 1 - Q19 spark-tpch: 1 - Q20 spark-tpch: 1 - Q21 spark-tpch: 1 - Q22 spark-tpch: 10 - Q01 spark-tpch: 10 - Q02 spark-tpch: 10 - Q03 spark-tpch: 10 - Q04 spark-tpch: 10 - Q05 spark-tpch: 10 - Q06 spark-tpch: 10 - Q07 spark-tpch: 10 - Q08 spark-tpch: 10 - Q09 spark-tpch: 10 - Q10 spark-tpch: 10 - Q11 spark-tpch: 10 - Q12 spark-tpch: 10 - Q13 spark-tpch: 10 - Q14 spark-tpch: 10 - Q15 spark-tpch: 10 - Q16 spark-tpch: 10 - Q17 spark-tpch: 10 - Q18 spark-tpch: 10 - Q19 spark-tpch: 10 - Q20 spark-tpch: 10 - Q21 spark-tpch: 10 - Q22 spark-tpch: 50 - Q01 spark-tpch: 50 - Q02 spark-tpch: 50 - Q03 spark-tpch: 50 - Q04 spark-tpch: 50 - Q05 spark-tpch: 50 - Q06 spark-tpch: 50 - Q07 spark-tpch: 50 - Q08 spark-tpch: 50 - Q09 spark-tpch: 50 - Q10 spark-tpch: 50 - Q11 spark-tpch: 50 - Q12 spark-tpch: 50 - Q13 spark-tpch: 50 - Q14 spark-tpch: 50 - Q15 spark-tpch: 50 - Q16 spark-tpch: 50 - Q17 spark-tpch: 50 - Q18 spark-tpch: 50 - Q19 spark-tpch: 50 - Q20 spark-tpch: 50 - Q21 spark-tpch: 50 - Q22 a b 3984.62 1631.42 420.74 2809.01 13358.53 1703.42 9.48 0.83 0.45 6.51 0.11 123558.6 123352.8 131141.9 31859.7 123041.6 123199.0 853 704 132.6580 281869895760 3244390.3 91630925473 715.0362 48.4476 20.6345 5540.6268 17.3023 190.7999 98622.0 5.2377 1758.5931 54.5064 209.7998 4.7637 17108.4634 5.5955 804.1784 1.2413 784.5178 122.0312 211.7448 4.7188 156.4159 607.5664 32.0229 31.2154 1761.4041 54.4097 208.1200 4.8022 796.0713 120.2065 212.0955 4.7126 1136.7105 84.2519 224.5798 4.4503 248.5770 383.2004 65.2070 15.3183 2608.0090 36.7508 68.2655 14.6422 132.0485 719.2814 48.4917 20.6157 23.57 10.16 21.16 21.00 8.93 21.29 8.90 8.96 6.40 2.32 2.32 2.32 8.248 86.434 178.910 176.670 21.424 165.104 571.875 635.810 2.44964916 10.72150208 19.58745807 4.32006081 2.06179071 3.86442184 3.92525745 4.13122161 0.46822915 4.01044806 2.65584644 5.70969407 3.81359665 1.27338135 2.17542648 1.58815936 2.06485331 2.50185966 1.38147259 2.95993924 5.62853845 0.79092395 3.05739617 9.64531231 1.00769047 7.58889151 7.43104283 13.97308763 12.34571203 16.44365629 2.05104745 14.65200933 15.51824761 21.90670204 15.17488098 8.00292349 9.94400438 7.37728373 7.07622369 5.84138076 6.87131294 12.77044550 18.46971194 6.20677837 11.43560823 32.90715027 6.05411895 12.00795619 14.25487200 26.18788719 20.99598312 29.83627891 5.90309207 24.85711161 26.73535283 36.66458511 24.36003748 13.58028253 19.40537771 12.75901413 12.70455011 9.77733866 14.21570397 24.30927912 34.51305643 10.45287259 20.79876137 87.89528910 10.69325638 3996.76 1632.45 421.91 2792.09 13434.09 1703.25 9.63 0.82 0.45 6.28 0.11 123411.1 122971 131613.6 31728.9 123777.7 122070.3 871 715 132.2719 282211175400 3243345.2 91835961470 717.5936 48.3264 20.686 5540.517 17.3019 191.0971 98528.8 5.2296 1756.5569 54.5546 206.969 4.829 17047.639 5.6159 804.7528 1.2404 786.8905 121.6067 211.7729 4.718 156.4283 607.5735 31.9795 31.2575 1759.0746 54.4859 209.1955 4.7775 797.4124 120.0373 212.1305 4.7117 1136.6439 84.2491 225.4047 4.4341 249.4983 382.5561 65.0079 15.3653 2596.0961 36.9146 68.2636 14.6426 132.4219 717.9791 48.332 20.6837 23.12 10.43 21.57 21.09 8.97 20.60 8.98 9.65 6.74 2.34 2.32 2.28 8.208 86.841 186.609 184.347 21.313 162.561 569.955 639.088 2.49517747 10.65793942 19.56475658 4.44657946 2.08224201 3.86610818 3.75427246 3.69217634 0.35801557 3.87790275 2.60907817 5.89775848 3.81245542 1.13998687 2.26641607 1.74074161 2.21146965 2.58714175 1.51779914 2.88348198 5.13171148 0.85797596 3.05001688 9.55909538 1.06679213 7.28826714 7.39245987 14.28984642 11.26242161 18.86129189 1.8559593 14.89605904 14.55769348 22.52552795 14.77719498 8.27814293 10.03829002 7.94083786 6.90602303 5.43870592 6.95270681 13.01374149 17.31370163 6.0604167 11.53966141 32.70154953 6.04430914 12.86835003 14.53046799 29.68590546 21.8167572 31.20059776 5.88382483 25.86055183 26.62909508 36.66526794 24.68585587 13.31200027 17.70001793 13.04496479 12.56767082 9.48287773 14.97535801 24.55788994 33.74198151 12.08592796 21.05384445 77.70675659 10.87410069 OpenBenchmarking.org
Java SciMark Computational Test: Composite OpenBenchmarking.org Mflops, More Is Better Java SciMark 2.2 Computational Test: Composite a b 900 1800 2700 3600 4500 SE +/- 6.24, N = 3 3984.62 3996.76
Java SciMark Computational Test: Monte Carlo OpenBenchmarking.org Mflops, More Is Better Java SciMark 2.2 Computational Test: Monte Carlo a b 400 800 1200 1600 2000 SE +/- 0.75, N = 3 1631.42 1632.45
Java SciMark Computational Test: Fast Fourier Transform OpenBenchmarking.org Mflops, More Is Better Java SciMark 2.2 Computational Test: Fast Fourier Transform a b 90 180 270 360 450 SE +/- 0.36, N = 3 420.74 421.91
Java SciMark Computational Test: Sparse Matrix Multiply OpenBenchmarking.org Mflops, More Is Better Java SciMark 2.2 Computational Test: Sparse Matrix Multiply a b 600 1200 1800 2400 3000 SE +/- 3.16, N = 3 2809.01 2792.09
Java SciMark Computational Test: Dense LU Matrix Factorization OpenBenchmarking.org Mflops, More Is Better Java SciMark 2.2 Computational Test: Dense LU Matrix Factorization a b 3K 6K 9K 12K 15K SE +/- 31.70, N = 3 13358.53 13434.09
Java SciMark Computational Test: Jacobi Successive Over-Relaxation OpenBenchmarking.org Mflops, More Is Better Java SciMark 2.2 Computational Test: Jacobi Successive Over-Relaxation a b 400 800 1200 1600 2000 SE +/- 0.16, N = 3 1703.42 1703.25
WebP2 Image Encode Encode Settings: Default OpenBenchmarking.org MP/s, More Is Better WebP2 Image Encode 20220823 Encode Settings: Default a b 3 6 9 12 15 SE +/- 0.08, N = 3 9.48 9.63 1. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl
WebP2 Image Encode Encode Settings: Quality 75, Compression Effort 7 OpenBenchmarking.org MP/s, More Is Better WebP2 Image Encode 20220823 Encode Settings: Quality 75, Compression Effort 7 a b 0.1868 0.3736 0.5604 0.7472 0.934 SE +/- 0.00, N = 3 0.83 0.82 1. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl
WebP2 Image Encode Encode Settings: Quality 95, Compression Effort 7 OpenBenchmarking.org MP/s, More Is Better WebP2 Image Encode 20220823 Encode Settings: Quality 95, Compression Effort 7 a b 0.1013 0.2026 0.3039 0.4052 0.5065 SE +/- 0.00, N = 3 0.45 0.45 1. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl
WebP2 Image Encode Encode Settings: Quality 100, Compression Effort 5 OpenBenchmarking.org MP/s, More Is Better WebP2 Image Encode 20220823 Encode Settings: Quality 100, Compression Effort 5 a b 2 4 6 8 10 SE +/- 0.04, N = 3 6.51 6.28 1. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl
WebP2 Image Encode Encode Settings: Quality 100, Lossless Compression OpenBenchmarking.org MP/s, More Is Better WebP2 Image Encode 20220823 Encode Settings: Quality 100, Lossless Compression a b 0.0248 0.0496 0.0744 0.0992 0.124 SE +/- 0.00, N = 3 0.11 0.11 1. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl
Xmrig Variant: KawPow - Hash Count: 1M OpenBenchmarking.org H/s, More Is Better Xmrig 6.21 Variant: KawPow - Hash Count: 1M a b 30K 60K 90K 120K 150K SE +/- 87.00, N = 3 123558.6 123411.1 1. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc
Xmrig Variant: Monero - Hash Count: 1M OpenBenchmarking.org H/s, More Is Better Xmrig 6.21 Variant: Monero - Hash Count: 1M a b 30K 60K 90K 120K 150K SE +/- 404.54, N = 3 123352.8 122971.0 1. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc
Xmrig Variant: Wownero - Hash Count: 1M OpenBenchmarking.org H/s, More Is Better Xmrig 6.21 Variant: Wownero - Hash Count: 1M a b 30K 60K 90K 120K 150K SE +/- 621.69, N = 3 131141.9 131613.6 1. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc
Xmrig Variant: GhostRider - Hash Count: 1M OpenBenchmarking.org H/s, More Is Better Xmrig 6.21 Variant: GhostRider - Hash Count: 1M a b 7K 14K 21K 28K 35K SE +/- 24.02, N = 3 31859.7 31728.9 1. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc
Xmrig Variant: CryptoNight-Heavy - Hash Count: 1M OpenBenchmarking.org H/s, More Is Better Xmrig 6.21 Variant: CryptoNight-Heavy - Hash Count: 1M a b 30K 60K 90K 120K 150K SE +/- 33.09, N = 3 123041.6 123777.7 1. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc
Xmrig Variant: CryptoNight-Femto UPX2 - Hash Count: 1M OpenBenchmarking.org H/s, More Is Better Xmrig 6.21 Variant: CryptoNight-Femto UPX2 - Hash Count: 1M a b 30K 60K 90K 120K 150K SE +/- 220.87, N = 3 123199.0 122070.3 1. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc
LeelaChessZero Backend: BLAS OpenBenchmarking.org Nodes Per Second, More Is Better LeelaChessZero 0.30 Backend: BLAS a b 200 400 600 800 1000 SE +/- 18.54, N = 9 853 871 1. (CXX) g++ options: -flto -pthread
LeelaChessZero Backend: Eigen OpenBenchmarking.org Nodes Per Second, More Is Better LeelaChessZero 0.30 Backend: Eigen a b 150 300 450 600 750 SE +/- 17.59, N = 8 704 715 1. (CXX) g++ options: -flto -pthread
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 30 60 90 120 150 SE +/- 0.66, N = 3 132.66 132.27
OpenSSL Algorithm: SHA256 OpenBenchmarking.org byte/s, More Is Better OpenSSL Algorithm: SHA256 a b 60000M 120000M 180000M 240000M 300000M SE +/- 548972949.20, N = 3 281869895760 282211175400 1. OpenSSL 3.0.10 1 Aug 2023 (Library: OpenSSL 3.0.10 1 Aug 2023)
OpenSSL Algorithm: RSA4096 OpenBenchmarking.org verify/s, More Is Better OpenSSL Algorithm: RSA4096 a b 700K 1400K 2100K 2800K 3500K SE +/- 1292.47, N = 3 3244390.3 3243345.2 1. OpenSSL 3.0.10 1 Aug 2023 (Library: OpenSSL 3.0.10 1 Aug 2023)
OpenSSL Algorithm: SHA512 OpenBenchmarking.org byte/s, More Is Better OpenSSL Algorithm: SHA512 a b 20000M 40000M 60000M 80000M 100000M SE +/- 191332047.54, N = 3 91630925473 91835961470 1. OpenSSL 3.0.10 1 Aug 2023 (Library: OpenSSL 3.0.10 1 Aug 2023)
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 150 300 450 600 750 SE +/- 4.21, N = 3 715.04 717.59
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 11 22 33 44 55 SE +/- 0.02, N = 3 48.45 48.33
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 5 10 15 20 25 SE +/- 0.01, N = 3 20.63 20.69
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 1200 2400 3600 4800 6000 SE +/- 5.02, N = 3 5540.63 5540.52
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 4 8 12 16 20 SE +/- 0.01, N = 3 17.30 17.30
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 40 80 120 160 200 SE +/- 0.06, N = 3 190.80 191.10
OpenSSL Algorithm: RSA4096 OpenBenchmarking.org sign/s, More Is Better OpenSSL Algorithm: RSA4096 a b 20K 40K 60K 80K 100K SE +/- 53.45, N = 3 98622.0 98528.8 1. OpenSSL 3.0.10 1 Aug 2023 (Library: OpenSSL 3.0.10 1 Aug 2023)
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 1.1785 2.357 3.5355 4.714 5.8925 SE +/- 0.0015, N = 3 5.2377 5.2296
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 400 800 1200 1600 2000 SE +/- 1.91, N = 3 1758.59 1756.56
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 12 24 36 48 60 SE +/- 0.06, N = 3 54.51 54.55
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 50 100 150 200 250 SE +/- 0.52, N = 3 209.80 206.97
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 1.0865 2.173 3.2595 4.346 5.4325 SE +/- 0.0118, N = 3 4.7637 4.8290
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 4K 8K 12K 16K 20K SE +/- 16.76, N = 3 17108.46 17047.64
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 1.2636 2.5272 3.7908 5.0544 6.318 SE +/- 0.0055, N = 3 5.5955 5.6159
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 200 400 600 800 1000 SE +/- 3.00, N = 3 804.18 804.75
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 0.2793 0.5586 0.8379 1.1172 1.3965 SE +/- 0.0046, N = 3 1.2413 1.2404
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 200 400 600 800 1000 SE +/- 1.42, N = 3 784.52 786.89
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 30 60 90 120 150 SE +/- 0.25, N = 3 122.03 121.61
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 50 100 150 200 250 SE +/- 0.50, N = 3 211.74 211.77
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 1.0617 2.1234 3.1851 4.2468 5.3085 SE +/- 0.0110, N = 3 4.7188 4.7180
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 30 60 90 120 150 SE +/- 0.02, N = 3 156.42 156.43
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 130 260 390 520 650 SE +/- 0.37, N = 3 607.57 607.57
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 7 14 21 28 35 SE +/- 0.03, N = 3 32.02 31.98
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 7 14 21 28 35 SE +/- 0.03, N = 3 31.22 31.26
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 400 800 1200 1600 2000 SE +/- 2.24, N = 3 1761.40 1759.07
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 12 24 36 48 60 SE +/- 0.07, N = 3 54.41 54.49
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 50 100 150 200 250 SE +/- 0.44, N = 3 208.12 209.20
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 1.0805 2.161 3.2415 4.322 5.4025 SE +/- 0.0103, N = 3 4.8022 4.7775
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 200 400 600 800 1000 SE +/- 1.54, N = 3 796.07 797.41
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 30 60 90 120 150 SE +/- 0.24, N = 3 120.21 120.04
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 50 100 150 200 250 SE +/- 0.35, N = 3 212.10 212.13
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 1.0603 2.1206 3.1809 4.2412 5.3015 SE +/- 0.0079, N = 3 4.7126 4.7117
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 200 400 600 800 1000 SE +/- 2.45, N = 3 1136.71 1136.64
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 20 40 60 80 100 SE +/- 0.19, N = 3 84.25 84.25
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 50 100 150 200 250 SE +/- 0.01, N = 3 224.58 225.40
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 1.0013 2.0026 3.0039 4.0052 5.0065 SE +/- 0.0001, N = 3 4.4503 4.4341
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 50 100 150 200 250 SE +/- 0.41, N = 3 248.58 249.50
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 80 160 240 320 400 SE +/- 0.61, N = 3 383.20 382.56
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 15 30 45 60 75 SE +/- 0.04, N = 3 65.21 65.01
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 4 8 12 16 20 SE +/- 0.01, N = 3 15.32 15.37
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 600 1200 1800 2400 3000 SE +/- 6.37, N = 3 2608.01 2596.10
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 8 16 24 32 40 SE +/- 0.09, N = 3 36.75 36.91
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 15 30 45 60 75 SE +/- 0.11, N = 3 68.27 68.26
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 4 8 12 16 20 SE +/- 0.02, N = 3 14.64 14.64
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 30 60 90 120 150 SE +/- 0.03, N = 3 132.05 132.42
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 160 320 480 640 800 SE +/- 1.53, N = 3 719.28 717.98
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 11 22 33 44 55 SE +/- 0.05, N = 3 48.49 48.33
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 5 10 15 20 25 SE +/- 0.02, N = 3 20.62 20.68
PyTorch Device: CPU - Batch Size: 1 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 1 - Model: ResNet-50 a b 6 12 18 24 30 SE +/- 0.19, N = 15 23.57 23.12 MIN: 11.38 / MAX: 25.62 MIN: 12.17 / MAX: 24.33
PyTorch Device: CPU - Batch Size: 1 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 1 - Model: ResNet-152 a b 3 6 9 12 15 SE +/- 0.08, N = 3 10.16 10.43 MIN: 4.56 / MAX: 10.94 MIN: 4.8 / MAX: 11.36
PyTorch Device: CPU - Batch Size: 16 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 16 - Model: ResNet-50 a b 5 10 15 20 25 SE +/- 0.25, N = 3 21.16 21.57 MIN: 12.26 / MAX: 22.24 MIN: 14.06 / MAX: 22.29
PyTorch Device: CPU - Batch Size: 32 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 32 - Model: ResNet-50 a b 5 10 15 20 25 SE +/- 0.20, N = 3 21.00 21.09 MIN: 11.39 / MAX: 21.87 MIN: 13.93 / MAX: 21.71
PyTorch Device: CPU - Batch Size: 16 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 16 - Model: ResNet-152 a b 3 6 9 12 15 SE +/- 0.10, N = 3 8.93 8.97 MIN: 4.75 / MAX: 9.39 MIN: 4.96 / MAX: 9.11
PyTorch Device: CPU - Batch Size: 256 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 256 - Model: ResNet-50 a b 5 10 15 20 25 SE +/- 0.31, N = 3 21.29 20.60 MIN: 13.22 / MAX: 22.39 MIN: 13.89 / MAX: 21.35
PyTorch Device: CPU - Batch Size: 32 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 32 - Model: ResNet-152 a b 3 6 9 12 15 SE +/- 0.10, N = 3 8.90 8.98 MIN: 4.8 / MAX: 9.23 MIN: 5.1 / MAX: 9.29
PyTorch Device: CPU - Batch Size: 256 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 256 - Model: ResNet-152 a b 3 6 9 12 15 SE +/- 0.05, N = 3 8.96 9.65 MIN: 4.84 / MAX: 9.24 MIN: 4.98 / MAX: 9.85
PyTorch Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l a b 2 4 6 8 10 SE +/- 0.05, N = 3 6.40 6.74 MIN: 2.93 / MAX: 6.73 MIN: 3.48 / MAX: 6.89
PyTorch Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l a b 0.5265 1.053 1.5795 2.106 2.6325 SE +/- 0.01, N = 3 2.32 2.34 MIN: 1.77 / MAX: 2.81 MIN: 1.78 / MAX: 2.78
PyTorch Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l a b 0.522 1.044 1.566 2.088 2.61 SE +/- 0.01, N = 3 2.32 2.32 MIN: 1.86 / MAX: 2.8 MIN: 1.93 / MAX: 2.71
PyTorch Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_l a b 0.522 1.044 1.566 2.088 2.61 SE +/- 0.00, N = 3 2.32 2.28 MIN: 1.83 / MAX: 2.8 MIN: 1.71 / MAX: 2.84
SVT-AV1 Encoder Mode: Preset 4 - Input: Bosphorus 4K OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.8 Encoder Mode: Preset 4 - Input: Bosphorus 4K a b 2 4 6 8 10 SE +/- 0.041, N = 3 8.248 8.208 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
SVT-AV1 Encoder Mode: Preset 8 - Input: Bosphorus 4K OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.8 Encoder Mode: Preset 8 - Input: Bosphorus 4K a b 20 40 60 80 100 SE +/- 0.17, N = 3 86.43 86.84 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
SVT-AV1 Encoder Mode: Preset 12 - Input: Bosphorus 4K OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.8 Encoder Mode: Preset 12 - Input: Bosphorus 4K a b 40 80 120 160 200 SE +/- 1.43, N = 3 178.91 186.61 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
SVT-AV1 Encoder Mode: Preset 13 - Input: Bosphorus 4K OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.8 Encoder Mode: Preset 13 - Input: Bosphorus 4K a b 40 80 120 160 200 SE +/- 1.61, N = 15 176.67 184.35 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
SVT-AV1 Encoder Mode: Preset 4 - Input: Bosphorus 1080p OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.8 Encoder Mode: Preset 4 - Input: Bosphorus 1080p a b 5 10 15 20 25 SE +/- 0.13, N = 3 21.42 21.31 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
SVT-AV1 Encoder Mode: Preset 8 - Input: Bosphorus 1080p OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.8 Encoder Mode: Preset 8 - Input: Bosphorus 1080p a b 40 80 120 160 200 SE +/- 1.87, N = 3 165.10 162.56 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
SVT-AV1 Encoder Mode: Preset 12 - Input: Bosphorus 1080p OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.8 Encoder Mode: Preset 12 - Input: Bosphorus 1080p a b 120 240 360 480 600 SE +/- 1.39, N = 3 571.88 569.96 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
SVT-AV1 Encoder Mode: Preset 13 - Input: Bosphorus 1080p OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.8 Encoder Mode: Preset 13 - Input: Bosphorus 1080p a b 140 280 420 560 700 SE +/- 8.75, N = 3 635.81 639.09 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
Apache Spark TPC-H Scale Factor: 1 - Geometric Mean Of All Queries OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 1 - Geometric Mean Of All Queries a b 0.5614 1.1228 1.6842 2.2456 2.807 SE +/- 0.02040294, N = 3 2.44964916 2.49517747 MIN: 0.73 / MAX: 10.03 MIN: 0.86 / MAX: 9.56
Apache Spark TPC-H Scale Factor: 10 - Geometric Mean Of All Queries OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 10 - Geometric Mean Of All Queries a b 3 6 9 12 15 SE +/- 0.02, N = 3 10.72 10.66 MIN: 5.7 / MAX: 33.03 MIN: 5.44 / MAX: 32.7
Apache Spark TPC-H Scale Factor: 50 - Geometric Mean Of All Queries OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 50 - Geometric Mean Of All Queries a b 5 10 15 20 25 SE +/- 0.05, N = 3 19.59 19.56 MIN: 9.71 / MAX: 103.64 MIN: 9.48 / MAX: 77.71
Apache Spark TPC-H Scale Factor: 1 - Q01 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 1 - Q01 a b 1.0005 2.001 3.0015 4.002 5.0025 SE +/- 0.17358727, N = 3 4.32006081 4.44657946
Apache Spark TPC-H Scale Factor: 1 - Q02 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 1 - Q02 a b 0.4685 0.937 1.4055 1.874 2.3425 SE +/- 0.02016184, N = 3 2.06179071 2.08224201
Apache Spark TPC-H Scale Factor: 1 - Q03 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 1 - Q03 a b 0.8699 1.7398 2.6097 3.4796 4.3495 SE +/- 0.11371323, N = 3 3.86442184 3.86610818
Apache Spark TPC-H Scale Factor: 1 - Q04 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 1 - Q04 a b 0.8832 1.7664 2.6496 3.5328 4.416 SE +/- 0.09899955, N = 3 3.92525745 3.75427246
Apache Spark TPC-H Scale Factor: 1 - Q05 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 1 - Q05 a b 0.9295 1.859 2.7885 3.718 4.6475 SE +/- 0.18898243, N = 3 4.13122161 3.69217634
Apache Spark TPC-H Scale Factor: 1 - Q06 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 1 - Q06 a b 0.1054 0.2108 0.3162 0.4216 0.527 SE +/- 0.03244463, N = 3 0.46822915 0.35801557
Apache Spark TPC-H Scale Factor: 1 - Q07 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 1 - Q07 a b 0.9024 1.8048 2.7072 3.6096 4.512 SE +/- 0.02085439, N = 3 4.01044806 3.87790275
Apache Spark TPC-H Scale Factor: 1 - Q08 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 1 - Q08 a b 0.5976 1.1952 1.7928 2.3904 2.988 SE +/- 0.02941830, N = 3 2.65584644 2.60907817
Apache Spark TPC-H Scale Factor: 1 - Q09 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 1 - Q09 a b 1.327 2.654 3.981 5.308 6.635 SE +/- 0.08828966, N = 3 5.70969407 5.89775848
Apache Spark TPC-H Scale Factor: 1 - Q10 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 1 - Q10 a b 0.8581 1.7162 2.5743 3.4324 4.2905 SE +/- 0.13264795, N = 3 3.81359665 3.81245542
Apache Spark TPC-H Scale Factor: 1 - Q11 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 1 - Q11 a b 0.2865 0.573 0.8595 1.146 1.4325 SE +/- 0.06007206, N = 3 1.27338135 1.13998687
Apache Spark TPC-H Scale Factor: 1 - Q12 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 1 - Q12 a b 0.5099 1.0198 1.5297 2.0396 2.5495 SE +/- 0.15180813, N = 3 2.17542648 2.26641607
Apache Spark TPC-H Scale Factor: 1 - Q13 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 1 - Q13 a b 0.3917 0.7834 1.1751 1.5668 1.9585 SE +/- 0.15789062, N = 3 1.58815936 1.74074161
Apache Spark TPC-H Scale Factor: 1 - Q14 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 1 - Q14 a b 0.4976 0.9952 1.4928 1.9904 2.488 SE +/- 0.16557850, N = 3 2.06485331 2.21146965
Apache Spark TPC-H Scale Factor: 1 - Q15 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 1 - Q15 a b 0.5821 1.1642 1.7463 2.3284 2.9105 SE +/- 0.11136502, N = 3 2.50185966 2.58714175
Apache Spark TPC-H Scale Factor: 1 - Q16 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 1 - Q16 a b 0.3415 0.683 1.0245 1.366 1.7075 SE +/- 0.06760680, N = 3 1.38147259 1.51779914
Apache Spark TPC-H Scale Factor: 1 - Q17 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 1 - Q17 a b 0.666 1.332 1.998 2.664 3.33 SE +/- 0.10612827, N = 3 2.95993924 2.88348198
Apache Spark TPC-H Scale Factor: 1 - Q18 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 1 - Q18 a b 1.2664 2.5328 3.7992 5.0656 6.332 SE +/- 0.11078356, N = 3 5.62853845 5.13171148
Apache Spark TPC-H Scale Factor: 1 - Q19 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 1 - Q19 a b 0.193 0.386 0.579 0.772 0.965 SE +/- 0.03922839, N = 3 0.79092395 0.85797596
Apache Spark TPC-H Scale Factor: 1 - Q20 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 1 - Q20 a b 0.6879 1.3758 2.0637 2.7516 3.4395 SE +/- 0.12035470, N = 3 3.05739617 3.05001688
Apache Spark TPC-H Scale Factor: 1 - Q21 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 1 - Q21 a b 3 6 9 12 15 SE +/- 0.26119238, N = 3 9.64531231 9.55909538
Apache Spark TPC-H Scale Factor: 1 - Q22 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 1 - Q22 a b 0.24 0.48 0.72 0.96 1.2 SE +/- 0.03222070, N = 3 1.00769047 1.06679213
Apache Spark TPC-H Scale Factor: 10 - Q01 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 10 - Q01 a b 2 4 6 8 10 SE +/- 0.23898111, N = 3 7.58889151 7.28826714
Apache Spark TPC-H Scale Factor: 10 - Q02 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 10 - Q02 a b 2 4 6 8 10 SE +/- 0.13824959, N = 3 7.43104283 7.39245987
Apache Spark TPC-H Scale Factor: 10 - Q03 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 10 - Q03 a b 4 8 12 16 20 SE +/- 0.31, N = 3 13.97 14.29
Apache Spark TPC-H Scale Factor: 10 - Q04 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 10 - Q04 a b 3 6 9 12 15 SE +/- 0.21, N = 3 12.35 11.26
Apache Spark TPC-H Scale Factor: 10 - Q05 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 10 - Q05 a b 5 10 15 20 25 SE +/- 0.48, N = 3 16.44 18.86
Apache Spark TPC-H Scale Factor: 10 - Q06 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 10 - Q06 a b 0.4615 0.923 1.3845 1.846 2.3075 SE +/- 0.23574646, N = 3 2.05104745 1.85595930
Apache Spark TPC-H Scale Factor: 10 - Q07 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 10 - Q07 a b 4 8 12 16 20 SE +/- 0.33, N = 3 14.65 14.90
Apache Spark TPC-H Scale Factor: 10 - Q08 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 10 - Q08 a b 4 8 12 16 20 SE +/- 0.41, N = 3 15.52 14.56
Apache Spark TPC-H Scale Factor: 10 - Q09 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 10 - Q09 a b 5 10 15 20 25 SE +/- 0.51, N = 3 21.91 22.53
Apache Spark TPC-H Scale Factor: 10 - Q10 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 10 - Q10 a b 4 8 12 16 20 SE +/- 0.31, N = 3 15.17 14.78
Apache Spark TPC-H Scale Factor: 10 - Q11 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 10 - Q11 a b 2 4 6 8 10 SE +/- 0.04584382, N = 3 8.00292349 8.27814293
Apache Spark TPC-H Scale Factor: 10 - Q12 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 10 - Q12 a b 3 6 9 12 15 SE +/- 0.16460967, N = 3 9.94400438 10.03829002
Apache Spark TPC-H Scale Factor: 10 - Q13 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 10 - Q13 a b 2 4 6 8 10 SE +/- 0.09689769, N = 3 7.37728373 7.94083786
Apache Spark TPC-H Scale Factor: 10 - Q14 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 10 - Q14 a b 2 4 6 8 10 SE +/- 0.33271668, N = 3 7.07622369 6.90602303
Apache Spark TPC-H Scale Factor: 10 - Q15 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 10 - Q15 a b 1.3143 2.6286 3.9429 5.2572 6.5715 SE +/- 0.10221447, N = 3 5.84138076 5.43870592
Apache Spark TPC-H Scale Factor: 10 - Q16 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 10 - Q16 a b 2 4 6 8 10 SE +/- 0.33462632, N = 3 6.87131294 6.95270681
Apache Spark TPC-H Scale Factor: 10 - Q17 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 10 - Q17 a b 3 6 9 12 15 SE +/- 0.07, N = 3 12.77 13.01
Apache Spark TPC-H Scale Factor: 10 - Q18 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 10 - Q18 a b 5 10 15 20 25 SE +/- 0.50, N = 3 18.47 17.31
Apache Spark TPC-H Scale Factor: 10 - Q19 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 10 - Q19 a b 2 4 6 8 10 SE +/- 0.15363169, N = 3 6.20677837 6.06041670
Apache Spark TPC-H Scale Factor: 10 - Q20 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 10 - Q20 a b 3 6 9 12 15 SE +/- 0.14, N = 3 11.44 11.54
Apache Spark TPC-H Scale Factor: 10 - Q21 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 10 - Q21 a b 8 16 24 32 40 SE +/- 0.11, N = 3 32.91 32.70
Apache Spark TPC-H Scale Factor: 10 - Q22 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 10 - Q22 a b 2 4 6 8 10 SE +/- 0.13164085, N = 3 6.05411895 6.04430914
Apache Spark TPC-H Scale Factor: 50 - Q01 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 50 - Q01 a b 3 6 9 12 15 SE +/- 0.21, N = 3 12.01 12.87
Apache Spark TPC-H Scale Factor: 50 - Q02 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 50 - Q02 a b 4 8 12 16 20 SE +/- 0.35, N = 3 14.25 14.53
Apache Spark TPC-H Scale Factor: 50 - Q03 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 50 - Q03 a b 7 14 21 28 35 SE +/- 0.94, N = 3 26.19 29.69
Apache Spark TPC-H Scale Factor: 50 - Q04 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 50 - Q04 a b 5 10 15 20 25 SE +/- 0.46, N = 3 21.00 21.82
Apache Spark TPC-H Scale Factor: 50 - Q05 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 50 - Q05 a b 7 14 21 28 35 SE +/- 0.67, N = 3 29.84 31.20
Apache Spark TPC-H Scale Factor: 50 - Q06 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 50 - Q06 a b 1.3282 2.6564 3.9846 5.3128 6.641 SE +/- 0.04522799, N = 3 5.90309207 5.88382483
Apache Spark TPC-H Scale Factor: 50 - Q07 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 50 - Q07 a b 6 12 18 24 30 SE +/- 0.23, N = 3 24.86 25.86
Apache Spark TPC-H Scale Factor: 50 - Q08 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 50 - Q08 a b 6 12 18 24 30 SE +/- 0.26, N = 3 26.74 26.63
Apache Spark TPC-H Scale Factor: 50 - Q09 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 50 - Q09 a b 8 16 24 32 40 SE +/- 0.34, N = 3 36.66 36.67
Apache Spark TPC-H Scale Factor: 50 - Q10 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 50 - Q10 a b 6 12 18 24 30 SE +/- 0.32, N = 3 24.36 24.69
Apache Spark TPC-H Scale Factor: 50 - Q11 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 50 - Q11 a b 3 6 9 12 15 SE +/- 0.32, N = 3 13.58 13.31
Apache Spark TPC-H Scale Factor: 50 - Q12 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 50 - Q12 a b 5 10 15 20 25 SE +/- 1.19, N = 3 19.41 17.70
Apache Spark TPC-H Scale Factor: 50 - Q13 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 50 - Q13 a b 3 6 9 12 15 SE +/- 0.08, N = 3 12.76 13.04
Apache Spark TPC-H Scale Factor: 50 - Q14 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 50 - Q14 a b 3 6 9 12 15 SE +/- 0.22, N = 3 12.70 12.57
Apache Spark TPC-H Scale Factor: 50 - Q15 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 50 - Q15 a b 3 6 9 12 15 SE +/- 0.05343306, N = 3 9.77733866 9.48287773
Apache Spark TPC-H Scale Factor: 50 - Q16 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 50 - Q16 a b 4 8 12 16 20 SE +/- 0.26, N = 3 14.22 14.98
Apache Spark TPC-H Scale Factor: 50 - Q17 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 50 - Q17 a b 6 12 18 24 30 SE +/- 0.55, N = 3 24.31 24.56
Apache Spark TPC-H Scale Factor: 50 - Q18 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 50 - Q18 a b 8 16 24 32 40 SE +/- 0.33, N = 3 34.51 33.74
Apache Spark TPC-H Scale Factor: 50 - Q19 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 50 - Q19 a b 3 6 9 12 15 SE +/- 0.12, N = 3 10.45 12.09
Apache Spark TPC-H Scale Factor: 50 - Q20 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 50 - Q20 a b 5 10 15 20 25 SE +/- 0.10, N = 3 20.80 21.05
Apache Spark TPC-H Scale Factor: 50 - Q21 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 50 - Q21 a b 20 40 60 80 100 SE +/- 7.93, N = 3 87.90 77.71
Apache Spark TPC-H Scale Factor: 50 - Q22 OpenBenchmarking.org Seconds, Fewer Is Better Apache Spark TPC-H 3.5 Scale Factor: 50 - Q22 a b 3 6 9 12 15 SE +/- 0.12, N = 3 10.69 10.87
Phoronix Test Suite v10.8.5