AMD EPYC Zen 1

AMD EPYC 7601 32-Core testing with a TYAN B8026T70AE24HR (V1.02.B10 BIOS) and llvmpipe on Ubuntu 23.10 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 2401081-NE-AMDEPYCZE16
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Table

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Run Management

Result
Identifier
Performance Per
Dollar
Date
Run
  Test
  Duration
Zen 1 - EPYC 7601
January 06
  1 Day, 1 Hour, 51 Minutes
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AMD EPYC Zen 1OpenBenchmarking.orgPhoronix Test SuiteAMD EPYC 7601 32-Core @ 2.20GHz (32 Cores / 64 Threads)TYAN B8026T70AE24HR (V1.02.B10 BIOS)AMD 17h128GB280GB INTEL SSDPE21D280GA + 1000GB INTEL SSDPE2KX010T8llvmpipeVE2282 x Broadcom NetXtreme BCM5720 PCIeUbuntu 23.106.6.9-060609-generic (x86_64)GNOME Shell 45.0X Server 1.21.1.74.5 Mesa 23.2.1-1ubuntu3.1 (LLVM 15.0.7 256 bits)GCC 13.2.0ext41920x1080ProcessorMotherboardChipsetMemoryDiskGraphicsMonitorNetworkOSKernelDesktopDisplay ServerOpenGLCompilerFile-SystemScreen ResolutionAMD EPYC Zen 1 BenchmarksSystem Logs- Transparent Huge Pages: madvise- --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 - Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0x800126e - OpenJDK Runtime Environment (build 11.0.21+9-post-Ubuntu-0ubuntu123.10)- Python 3.11.6- gather_data_sampling: Not affected + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Mitigation of untrained return thunk; SMT vulnerable + 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 Retpolines IBPB: conditional STIBP: disabled RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected

AMD EPYC Zen 1pytorch: CPU - 1 - ResNet-50pytorch: CPU - 256 - ResNet-50minibude: OpenMP - BM1minibude: OpenMP - BM2openssl: SHA256openssl: AES-128-GCMopenssl: SHA512openssl: AES-256-GCMopenssl: ChaCha20openssl: ChaCha20-Poly1305quicksilver: CORAL2 P1quicksilver: CORAL2 P2quicksilver: CTS2ffmpeg: libx265 - Liveffmpeg: libx265 - Platformffmpeg: libx265 - Uploadffmpeg: libx265 - Video On Demandopenvino: Face Detection FP16-INT8 - CPUopenvino: Age Gender Recognition Retail 0013 FP16-INT8 - CPUopenvino: Person Detection FP16 - CPUopenvino: Weld Porosity Detection FP16-INT8 - CPUopenvino: Vehicle Detection FP16-INT8 - CPUopenvino: Person Vehicle Bike Detection FP16 - CPUopenvino: Machine Translation EN To DE FP16 - CPUopenvino: Face Detection Retail FP16-INT8 - CPUopenvino: Handwritten English Recognition FP16-INT8 - CPUopenvino: Road Segmentation ADAS FP16-INT8 - CPUembree: Pathtracer ISPC - Asian Dragonembree: Pathtracer ISPC - Crownsvt-av1: Preset 13 - Bosphorus 4Ksvt-av1: Preset 12 - Bosphorus 4Ksvt-av1: Preset 8 - Bosphorus 4Ksvt-av1: Preset 4 - Bosphorus 4Kuvg266: Bosphorus 4K - Very Fastuvg266: Bosphorus 4K - Ultra Fastvvenc: Bosphorus 4K - Fasterrav1e: 10rav1e: 6uvg266: Bosphorus 4K - Mediumuvg266: Bosphorus 4K - Super Fastrav1e: 5rav1e: 1x265: Bosphorus 4Kvvenc: Bosphorus 4K - Fastminibude: OpenMP - BM1minibude: OpenMP - BM2mt-dgemm: Sustained Floating-Point Ratexmrig: Wownero - 1Mxmrig: CryptoNight-Femto UPX2 - 1Mxmrig: CryptoNight-Heavy - 1Mxmrig: KawPow - 1Mxmrig: GhostRider - 1Mxmrig: Monero - 1Moidn: RT.ldr_alb_nrm.3840x2160 - CPU-Onlytensorflow: CPU - 16 - ResNet-50ospray: gravity_spheres_volume/dim_512/ao/real_timeospray: gravity_spheres_volume/dim_512/scivis/real_timeospray: gravity_spheres_volume/dim_512/pathtracer/real_timeospray: particle_volume/ao/real_timeospray: particle_volume/scivis/real_timeospray: particle_volume/pathtracer/real_timedeepsparse: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Asynchronous Multi-Streamdeepsparse: NLP Text Classification, DistilBERT mnli - Asynchronous Multi-Streamdeepsparse: CV Classification, ResNet-50 ImageNet - Asynchronous Multi-Streamdeepsparse: NLP Token Classification, BERT base uncased conll2003 - Asynchronous Multi-Streamdeepsparse: CV Detection, YOLOv5s COCO - Asynchronous Multi-Streamdeepsparse: CV Detection, YOLOv5s COCO, Sparse INT8 - Asynchronous Multi-Streamdeepsparse: NLP Document Classification, oBERT base uncased on IMDB - Asynchronous Multi-Streamdeepsparse: CV Segmentation, 90% Pruned YOLACT Pruned - Asynchronous Multi-Streamdeepsparse: ResNet-50, Baseline - Asynchronous Multi-Streamdeepsparse: ResNet-50, Sparse INT8 - Asynchronous Multi-Streamdeepsparse: BERT-Large, NLP Question Answering - Asynchronous Multi-Streamdeepsparse: BERT-Large, NLP Question Answering, Sparse INT8 - Asynchronous Multi-Streamindigobench: CPU - Supercarindigobench: CPU - Bedroomquantlib: Multi-Threadedcompress-7zip: Compression Ratingcompress-7zip: Decompression Ratinggromacs: MPI CPU - water_GMX50_barelammps: 20k Atomscassandra: Writesspeedb: Rand Readspeedb: Read While Writingspeedb: Read Rand Write Randspeedb: Update Randrocksdb: Rand Readrocksdb: Read While Writingrocksdb: Read Rand Write Randrocksdb: Update Randmemtier-benchmark: Redis - 100 - 1:10memtier-benchmark: Redis - 100 - 1:5apache-iotdb: 500 - 100 - 200 - 100apache-iotdb: 500 - 100 - 200 - 400apache-iotdb: 500 - 100 - 500 - 100apache-iotdb: 500 - 100 - 500 - 400apache-iotdb: 500 - 100 - 800 - 100apache-iotdb: 500 - 100 - 800 - 400apache-iotdb: 800 - 100 - 200 - 100apache-iotdb: 800 - 100 - 200 - 400apache-iotdb: 800 - 100 - 500 - 100apache-iotdb: 800 - 100 - 500 - 400apache-iotdb: 800 - 100 - 800 - 100apache-iotdb: 800 - 100 - 800 - 400nginx: 500nginx: 1000apache: 1000openssl: RSA4096kripke: openssl: RSA4096v-ray: CPUapache-iotdb: 500 - 100 - 200 - 100apache-iotdb: 500 - 100 - 200 - 400apache-iotdb: 500 - 100 - 500 - 100apache-iotdb: 500 - 100 - 500 - 400apache-iotdb: 500 - 100 - 800 - 100apache-iotdb: 500 - 100 - 800 - 400apache-iotdb: 800 - 100 - 200 - 100apache-iotdb: 800 - 100 - 200 - 400apache-iotdb: 800 - 100 - 500 - 100apache-iotdb: 800 - 100 - 500 - 400apache-iotdb: 800 - 100 - 800 - 100apache-iotdb: 800 - 100 - 800 - 400namd: ATPase Simulation - 327,506 Atomsospray-studio: 1 - 4K - 1 - Path Tracer - CPUospray-studio: 1 - 4K - 16 - Path Tracer - CPUospray-studio: 1 - 4K - 32 - Path Tracer - CPUospray-studio: 3 - 4K - 1 - Path Tracer - CPUospray-studio: 3 - 4K - 16 - Path Tracer - CPUospray-studio: 3 - 4K - 32 - Path Tracer - CPUopenvino: Face Detection FP16-INT8 - CPUopenvino: Age Gender Recognition Retail 0013 FP16-INT8 - CPUopenvino: Person Detection FP16 - CPUopenvino: Weld Porosity Detection FP16-INT8 - CPUopenvino: Vehicle Detection FP16-INT8 - CPUopenvino: Person Vehicle Bike Detection FP16 - CPUopenvino: Machine Translation EN To DE FP16 - CPUopenvino: Face Detection Retail FP16-INT8 - CPUopenvino: Handwritten English Recognition FP16-INT8 - CPUopenvino: Road Segmentation ADAS FP16-INT8 - CPUdeepsparse: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Asynchronous Multi-Streamdeepsparse: NLP Text Classification, DistilBERT mnli - Asynchronous Multi-Streamdeepsparse: CV Classification, ResNet-50 ImageNet - Asynchronous Multi-Streamdeepsparse: NLP Token Classification, BERT base uncased conll2003 - Asynchronous Multi-Streamdeepsparse: CV Detection, YOLOv5s COCO - Asynchronous Multi-Streamdeepsparse: CV Detection, YOLOv5s COCO, Sparse INT8 - Asynchronous Multi-Streamdeepsparse: NLP Document Classification, oBERT base uncased on IMDB - Asynchronous Multi-Streamdeepsparse: CV Segmentation, 90% Pruned YOLACT Pruned - Asynchronous Multi-Streamdeepsparse: ResNet-50, Baseline - Asynchronous Multi-Streamdeepsparse: ResNet-50, Sparse INT8 - Asynchronous Multi-Streamdeepsparse: BERT-Large, NLP Question Answering - Asynchronous Multi-Streamdeepsparse: BERT-Large, NLP Question Answering, Sparse INT8 - Asynchronous Multi-Streamduckdb: IMDBduckdb: TPC-H Parquetbuild-linux-kernel: defconfigbuild-linux-kernel: allmodconfigbuild-llvm: Ninjabuild-llvm: Unix Makefilesbuild-nodejs: Time To Compilebuild-gem5: Time To Compilebuild-ffmpeg: Time To Compilespecfem3d: Layered Halfspacespecfem3d: Water-layered Halfspacespecfem3d: Homogeneous Halfspacespecfem3d: Mount St. Helensspecfem3d: Tomographic Modelopenfoam: drivaerFastback, Small Mesh Size - Mesh Timeopenfoam: drivaerFastback, Small Mesh Size - Execution Timeopenfoam: drivaerFastback, Medium Mesh Size - Mesh Timeopenfoam: drivaerFastback, Medium Mesh Size - Execution Timeopenradioss: Chrysler Neon 1Measywave: e2Asean Grid + BengkuluSept2007 Source - 1200easywave: e2Asean Grid + BengkuluSept2007 Source - 2400gpaw: Carbon Nanotubecloverleaf: clover_bm64_shortcloverleaf: clover_bm16incompact3d: input.i3d 193 Cells Per Directionincompact3d: X3D-benchmarking input.i3dy-cruncher: 500My-cruncher: 1Bmrbayes: Primate Phylogeny Analysisblender: BMW27 - CPU-Onlyblender: Classroom - CPU-Onlyblender: Fishy Cat - CPU-Onlyblender: Pabellon Barcelona - CPU-Onlyblender: Barbershop - CPU-OnlyZen 1 - EPYC 760126.7221.2114.24514.2202705683040097645009487831618417089948428697479200259673031549069012996667150133331142666758.2321.0310.3921.043.8213011.1043.91377.40295.80471.3841.32877.49189.05149.4921.831518.361367.93470.52526.2523.06022.2727.216.4936.9712.9378.7323.442.2490.56314.523.291356.122355.5013.79079910414.76957.27081.06937.91070.17044.20.489.822.578292.466924.148415.289315.2211698.4413260.249690.6624144.682910.754570.339570.558610.80709.2992142.7964155.701913.2597131.76058.5803.99164481.71239341344171.99213.872152887868670416145679143607420155584798204337187615091842906181183656.971142464.16387122633817645653759940528491255877409059444334460495894592107456993811570374415840375660237625103269.83100664.3588038.284510.7187375933293924.12017546.29166.0085.07294.75127.26421.3039.40147.8982.07318.24129.77488.640.979598478145528280606100501711883316432094.212.43181.9284.6827.0116.95193.339.1169.0453.4761.3934176.4317110.44841457.9155226.9518226.37441460.70411701.3747111.8988102.65821200.1003121.2093199.014245.74276.300755.017435.054529.717387.652388.02339.78978.67990438474.95062589638.06317925029.95188620330.28359304044.44531126.1908231.744461179.2541499.30148.077352.687142.165108.60971.5037.4064191818.05411815.69333.923201.18273.00192.80101.20247.24767.15OpenBenchmarking.org

CPU Power Consumption Monitor

OpenBenchmarking.orgWattsCPU Power Consumption MonitorPhoronix Test Suite System MonitoringZen 1 - EPYC 7601140280420560700Min: 134.19 / Avg: 579.81 / Max: 789.58

PyTorch

OpenBenchmarking.orgbatches/sec Per Watt, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-50Zen 1 - EPYC 76010.00970.01940.02910.03880.04850.043

OpenBenchmarking.orgbatches/sec Per Watt, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-50Zen 1 - EPYC 76010.00720.01440.02160.02880.0360.032

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-50Zen 1 - EPYC 7601612182430SE +/- 0.12, N = 326.72MIN: 15.15 / MAX: 28.15

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-50Zen 1 - EPYC 7601510152025SE +/- 0.22, N = 321.21MIN: 13.9 / MAX: 22.04

miniBUDE

OpenBenchmarking.orgBillion Interactions/s Per Watt, More Is BetterminiBUDE 20210901Implementation: OpenMP - Input Deck: BM1Zen 1 - EPYC 76010.0050.010.0150.020.0250.022

OpenBenchmarking.orgBillion Interactions/s Per Watt, More Is BetterminiBUDE 20210901Implementation: OpenMP - Input Deck: BM2Zen 1 - EPYC 76010.00470.00940.01410.01880.02350.021

OpenBenchmarking.orgBillion Interactions/s, More Is BetterminiBUDE 20210901Implementation: OpenMP - Input Deck: BM1Zen 1 - EPYC 760148121620SE +/- 0.04, N = 314.251. (CC) gcc options: -std=c99 -Ofast -ffast-math -fopenmp -march=native -lm

OpenBenchmarking.orgBillion Interactions/s, More Is BetterminiBUDE 20210901Implementation: OpenMP - Input Deck: BM2Zen 1 - EPYC 760148121620SE +/- 0.01, N = 314.221. (CC) gcc options: -std=c99 -Ofast -ffast-math -fopenmp -march=native -lm

OpenSSL

OpenBenchmarking.orgbyte/s Per Watt, More Is BetterOpenSSL 3.1Algorithm: SHA256Zen 1 - EPYC 76018M16M24M32M40M38850033.87

OpenBenchmarking.orgbyte/s Per Watt, More Is BetterOpenSSL 3.1Algorithm: SHA512Zen 1 - EPYC 76013M6M9M12M15M11909195.29

OpenBenchmarking.orgbyte/s, More Is BetterOpenSSL 3.1Algorithm: SHA256Zen 1 - EPYC 76016000M12000M18000M24000M30000MSE +/- 48383276.04, N = 3270568304001. (CC) gcc options: -pthread -m64 -O3 -ldl

OpenBenchmarking.orgbyte/s Per Watt, More Is BetterOpenSSL 3.1Algorithm: AES-128-GCMZen 1 - EPYC 760130M60M90M120M150M139836719.65

OpenBenchmarking.orgbyte/s Per Watt, More Is BetterOpenSSL 3.1Algorithm: AES-256-GCMZen 1 - EPYC 760130M60M90M120M150M128846358.68

OpenBenchmarking.orgbyte/s Per Watt, More Is BetterOpenSSL 3.1Algorithm: ChaCha20Zen 1 - EPYC 760115M30M45M60M75M69962511.27

OpenBenchmarking.orgbyte/s, More Is BetterOpenSSL 3.1Algorithm: AES-128-GCMZen 1 - EPYC 760120000M40000M60000M80000M100000MSE +/- 101833027.65, N = 3976450094871. (CC) gcc options: -pthread -m64 -O3 -ldl

OpenBenchmarking.orgbyte/s Per Watt, More Is BetterOpenSSL 3.1Algorithm: ChaCha20-Poly1305Zen 1 - EPYC 76019M18M27M36M45M44247682.05

OpenBenchmarking.orgbyte/s, More Is BetterOpenSSL 3.1Algorithm: SHA512Zen 1 - EPYC 76012000M4000M6000M8000M10000MSE +/- 6971539.66, N = 383161841701. (CC) gcc options: -pthread -m64 -O3 -ldl

OpenBenchmarking.orgbyte/s, More Is BetterOpenSSL 3.1Algorithm: AES-256-GCMZen 1 - EPYC 760120000M40000M60000M80000M100000MSE +/- 95870018.66, N = 3899484286971. (CC) gcc options: -pthread -m64 -O3 -ldl

OpenBenchmarking.orgbyte/s, More Is BetterOpenSSL 3.1Algorithm: ChaCha20Zen 1 - EPYC 760110000M20000M30000M40000M50000MSE +/- 23640894.78, N = 3479200259671. (CC) gcc options: -pthread -m64 -O3 -ldl

OpenBenchmarking.orgbyte/s, More Is BetterOpenSSL 3.1Algorithm: ChaCha20-Poly1305Zen 1 - EPYC 76016000M12000M18000M24000M30000MSE +/- 12075597.72, N = 3303154906901. (CC) gcc options: -pthread -m64 -O3 -ldl

Quicksilver

Quicksilver is a proxy application that represents some elements of the Mercury workload by solving a simplified dynamic Monte Carlo particle transport problem. Quicksilver is developed by Lawrence Livermore National Laboratory (LLNL) and this test profile currently makes use of the OpenMP CPU threaded code path. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFigure Of Merit, More Is BetterQuicksilver 20230818Input: CORAL2 P1Zen 1 - EPYC 76013M6M9M12M15MSE +/- 66916.20, N = 3129966671. (CXX) g++ options: -fopenmp -O3 -march=native

OpenBenchmarking.orgFigure Of Merit, More Is BetterQuicksilver 20230818Input: CORAL2 P2Zen 1 - EPYC 76013M6M9M12M15MSE +/- 37118.43, N = 3150133331. (CXX) g++ options: -fopenmp -O3 -march=native

OpenBenchmarking.orgFigure Of Merit Per Watt, More Is BetterQuicksilver 20230818Input: CTS2Zen 1 - EPYC 76014K8K12K16K20K18307.66

OpenBenchmarking.orgFigure Of Merit, More Is BetterQuicksilver 20230818Input: CTS2Zen 1 - EPYC 76012M4M6M8M10MSE +/- 16666.67, N = 3114266671. (CXX) g++ options: -fopenmp -O3 -march=native

FFmpeg

OpenBenchmarking.orgFPS Per Watt, More Is BetterFFmpeg 6.1Encoder: libx265 - Scenario: LiveZen 1 - EPYC 76010.03920.07840.11760.15680.1960.174

OpenBenchmarking.orgFPS, More Is BetterFFmpeg 6.1Encoder: libx265 - Scenario: LiveZen 1 - EPYC 76011326395265SE +/- 0.07, N = 358.231. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl -lnuma

OpenBenchmarking.orgFPS, More Is BetterFFmpeg 6.1Encoder: libx265 - Scenario: PlatformZen 1 - EPYC 7601510152025SE +/- 0.02, N = 321.031. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl -lnuma

OpenBenchmarking.orgFPS Per Watt, More Is BetterFFmpeg 6.1Encoder: libx265 - Scenario: UploadZen 1 - EPYC 76010.0070.0140.0210.0280.0350.031

OpenBenchmarking.orgFPS, More Is BetterFFmpeg 6.1Encoder: libx265 - Scenario: UploadZen 1 - EPYC 76013691215SE +/- 0.00, N = 310.391. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl -lnuma

OpenBenchmarking.orgFPS, More Is BetterFFmpeg 6.1Encoder: libx265 - Scenario: Video On DemandZen 1 - EPYC 7601510152025SE +/- 0.00, N = 321.041. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl -lnuma

OpenVINO

This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.2.devModel: Face Detection FP16-INT8 - Device: CPUZen 1 - EPYC 76010.85951.7192.57853.4384.2975SE +/- 0.00, N = 33.821. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -pie

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.2.devModel: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPUZen 1 - EPYC 76013K6K9K12K15KSE +/- 3.60, N = 313011.101. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -pie

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.2.devModel: Person Detection FP16 - Device: CPUZen 1 - EPYC 76011020304050SE +/- 0.09, N = 343.911. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -pie

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.2.devModel: Weld Porosity Detection FP16-INT8 - Device: CPUZen 1 - EPYC 760180160240320400SE +/- 0.02, N = 3377.401. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -pie

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.2.devModel: Vehicle Detection FP16-INT8 - Device: CPUZen 1 - EPYC 760160120180240300SE +/- 0.35, N = 3295.801. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -pie

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.2.devModel: Person Vehicle Bike Detection FP16 - Device: CPUZen 1 - EPYC 7601100200300400500SE +/- 1.63, N = 3471.381. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -pie

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.2.devModel: Machine Translation EN To DE FP16 - Device: CPUZen 1 - EPYC 7601918273645SE +/- 0.10, N = 341.321. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -pie

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.2.devModel: Face Detection Retail FP16-INT8 - Device: CPUZen 1 - EPYC 76012004006008001000SE +/- 0.26, N = 3877.491. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -pie

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.2.devModel: Handwritten English Recognition FP16-INT8 - Device: CPUZen 1 - EPYC 76014080120160200SE +/- 0.70, N = 3189.051. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -pie

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2023.2.devModel: Road Segmentation ADAS FP16-INT8 - Device: CPUZen 1 - EPYC 7601306090120150SE +/- 0.14, N = 3149.491. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -pie

Embree

OpenBenchmarking.orgFrames Per Second Per Watt, More Is BetterEmbree 4.3Binary: Pathtracer ISPC - Model: Asian DragonZen 1 - EPYC 76010.00770.01540.02310.03080.03850.034

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.3Binary: Pathtracer ISPC - Model: Asian DragonZen 1 - EPYC 7601510152025SE +/- 0.05, N = 321.83MIN: 21.6 / MAX: 22.16

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.3Binary: Pathtracer ISPC - Model: CrownZen 1 - EPYC 7601510152025SE +/- 0.09, N = 318.36MIN: 18.01 / MAX: 18.84

SVT-AV1

This is a benchmark of the SVT-AV1 open-source video encoder/decoder. SVT-AV1 was originally developed by Intel as part of their Open Visual Cloud / Scalable Video Technology (SVT). Development of SVT-AV1 has since moved to the Alliance for Open Media as part of upstream AV1 development. SVT-AV1 is a CPU-based multi-threaded video encoder for the AV1 video format with a sample YUV video file. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.8Encoder Mode: Preset 13 - Input: Bosphorus 4KZen 1 - EPYC 76011530456075SE +/- 2.72, N = 1267.931. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.8Encoder Mode: Preset 12 - Input: Bosphorus 4KZen 1 - EPYC 76011632486480SE +/- 0.80, N = 1570.531. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.8Encoder Mode: Preset 8 - Input: Bosphorus 4KZen 1 - EPYC 7601612182430SE +/- 0.17, N = 326.251. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq

OpenBenchmarking.orgFrames Per Second, More Is BetterSVT-AV1 1.8Encoder Mode: Preset 4 - Input: Bosphorus 4KZen 1 - EPYC 76010.68851.3772.06552.7543.4425SE +/- 0.011, N = 33.0601. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq

uvg266

uvg266 is an open-source VVC/H.266 (Versatile Video Coding) encoder based on Kvazaar as part of the Ultra Video Group, Tampere University, Finland. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFrames Per Second, More Is Betteruvg266 0.4.1Video Input: Bosphorus 4K - Video Preset: Very FastZen 1 - EPYC 7601510152025SE +/- 0.08, N = 322.27

OpenBenchmarking.orgFrames Per Second, More Is Betteruvg266 0.4.1Video Input: Bosphorus 4K - Video Preset: Ultra FastZen 1 - EPYC 7601612182430SE +/- 0.04, N = 327.21

VVenC

VVenC is the Fraunhofer Versatile Video Encoder as a fast/efficient H.266/VVC encoder. The vvenc encoder makes use of SIMD Everywhere (SIMDe). The vvenc software is published under the Clear BSD License. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFrames Per Second, More Is BetterVVenC 1.9Video Input: Bosphorus 4K - Video Preset: FasterZen 1 - EPYC 7601246810SE +/- 0.018, N = 36.4931. (CXX) g++ options: -O3 -flto=auto -fno-fat-lto-objects

rav1e

Xiph rav1e is a Rust-written AV1 video encoder that claims to be the fastest and safest AV1 encoder. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFrames Per Second, More Is Betterrav1e 0.7Speed: 10Zen 1 - EPYC 7601246810SE +/- 0.080, N = 36.971

OpenBenchmarking.orgFrames Per Second Per Watt, More Is Betterrav1e 0.7Speed: 6Zen 1 - EPYC 76010.00180.00360.00540.00720.0090.008

OpenBenchmarking.orgFrames Per Second, More Is Betterrav1e 0.7Speed: 6Zen 1 - EPYC 76010.66081.32161.98242.64323.304SE +/- 0.003, N = 32.937

uvg266

uvg266 is an open-source VVC/H.266 (Versatile Video Coding) encoder based on Kvazaar as part of the Ultra Video Group, Tampere University, Finland. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFrames Per Second, More Is Betteruvg266 0.4.1Video Input: Bosphorus 4K - Video Preset: MediumZen 1 - EPYC 7601246810SE +/- 0.04, N = 38.73

OpenBenchmarking.orgFrames Per Second, More Is Betteruvg266 0.4.1Video Input: Bosphorus 4K - Video Preset: Super FastZen 1 - EPYC 7601612182430SE +/- 0.01, N = 323.44

rav1e

OpenBenchmarking.orgFrames Per Second Per Watt, More Is Betterrav1e 0.7Speed: 5Zen 1 - EPYC 76010.00140.00280.00420.00560.0070.006

OpenBenchmarking.orgFrames Per Second Per Watt, More Is Betterrav1e 0.7Speed: 1Zen 1 - EPYC 76010.00020.00040.00060.00080.0010.001

x265

OpenBenchmarking.orgFrames Per Second Per Watt, More Is Betterx265 3.4Video Input: Bosphorus 4KZen 1 - EPYC 76010.00630.01260.01890.02520.03150.028

VVenC

OpenBenchmarking.orgFrames Per Second Per Watt, More Is BetterVVenC 1.9Video Input: Bosphorus 4K - Video Preset: FastZen 1 - EPYC 76010.00140.00280.00420.00560.0070.006

rav1e

Xiph rav1e is a Rust-written AV1 video encoder that claims to be the fastest and safest AV1 encoder. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFrames Per Second, More Is Betterrav1e 0.7Speed: 5Zen 1 - EPYC 76010.5061.0121.5182.0242.53SE +/- 0.014, N = 32.249

OpenBenchmarking.orgFrames Per Second, More Is Betterrav1e 0.7Speed: 1Zen 1 - EPYC 76010.12670.25340.38010.50680.6335SE +/- 0.001, N = 30.563

x265

This is a simple test of the x265 encoder run on the CPU with 1080p and 4K options for H.265 video encode performance with x265. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFrames Per Second, More Is Betterx265 3.4Video Input: Bosphorus 4KZen 1 - EPYC 760148121620SE +/- 0.17, N = 414.521. (CXX) g++ options: -O3 -rdynamic -lpthread -lrt -ldl -lnuma

VVenC

VVenC is the Fraunhofer Versatile Video Encoder as a fast/efficient H.266/VVC encoder. The vvenc encoder makes use of SIMD Everywhere (SIMDe). The vvenc software is published under the Clear BSD License. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFrames Per Second, More Is BetterVVenC 1.9Video Input: Bosphorus 4K - Video Preset: FastZen 1 - EPYC 76010.74051.4812.22152.9623.7025SE +/- 0.034, N = 33.2911. (CXX) g++ options: -O3 -flto=auto -fno-fat-lto-objects

miniBUDE

MiniBUDE is a mini application for the the core computation of the Bristol University Docking Engine (BUDE). This test profile currently makes use of the OpenMP implementation of miniBUDE for CPU benchmarking. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGFInst/s, More Is BetterminiBUDE 20210901Implementation: OpenMP - Input Deck: BM1Zen 1 - EPYC 760180160240320400SE +/- 0.94, N = 3356.121. (CC) gcc options: -std=c99 -Ofast -ffast-math -fopenmp -march=native -lm

OpenBenchmarking.orgGFInst/s, More Is BetterminiBUDE 20210901Implementation: OpenMP - Input Deck: BM2Zen 1 - EPYC 760180160240320400SE +/- 0.27, N = 3355.501. (CC) gcc options: -std=c99 -Ofast -ffast-math -fopenmp -march=native -lm

ACES DGEMM

OpenBenchmarking.orgGFLOP/s Per Watt, More Is BetterACES DGEMM 1.0Sustained Floating-Point RateZen 1 - EPYC 76010.00140.00280.00420.00560.0070.006

OpenBenchmarking.orgGFLOP/s, More Is BetterACES DGEMM 1.0Sustained Floating-Point RateZen 1 - EPYC 76010.85291.70582.55873.41164.2645SE +/- 0.057778, N = 153.7907991. (CC) gcc options: -O3 -march=native -fopenmp

Xmrig

Xmrig is an open-source cross-platform CPU/GPU miner for RandomX, KawPow, CryptoNight and AstroBWT. This test profile is setup to measure the Xmrig CPU mining performance. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgH/s, More Is BetterXmrig 6.21Variant: Wownero - Hash Count: 1MZen 1 - EPYC 76012K4K6K8K10KSE +/- 27.32, N = 310414.71. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc

OpenBenchmarking.orgH/s, More Is BetterXmrig 6.21Variant: CryptoNight-Femto UPX2 - Hash Count: 1MZen 1 - EPYC 760115003000450060007500SE +/- 75.94, N = 126957.21. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc

OpenBenchmarking.orgH/s, More Is BetterXmrig 6.21Variant: CryptoNight-Heavy - Hash Count: 1MZen 1 - EPYC 760115003000450060007500SE +/- 21.41, N = 37081.01. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc

OpenBenchmarking.orgH/s, More Is BetterXmrig 6.21Variant: KawPow - Hash Count: 1MZen 1 - EPYC 760115003000450060007500SE +/- 60.77, N = 126937.91. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc

OpenBenchmarking.orgH/s, More Is BetterXmrig 6.21Variant: GhostRider - Hash Count: 1MZen 1 - EPYC 76012004006008001000SE +/- 6.67, N = 31070.11. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc

OpenBenchmarking.orgH/s Per Watt, More Is BetterXmrig 6.21Variant: Monero - Hash Count: 1MZen 1 - EPYC 7601369121510.86

OpenBenchmarking.orgH/s, More Is BetterXmrig 6.21Variant: Monero - Hash Count: 1MZen 1 - EPYC 760115003000450060007500SE +/- 58.63, N = 37044.21. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc

Intel Open Image Denoise

OpenBenchmarking.orgImages / Sec, More Is BetterIntel Open Image Denoise 2.1Run: RT.ldr_alb_nrm.3840x2160 - Device: CPU-OnlyZen 1 - EPYC 76010.1080.2160.3240.4320.54SE +/- 0.00, N = 30.48

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries if desired for complementary metrics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: ResNet-50Zen 1 - EPYC 76013691215SE +/- 0.04, N = 39.82

OSPRay

OpenBenchmarking.orgItems Per Second Per Watt, More Is BetterOSPRay 2.12Benchmark: particle_volume/ao/real_timeZen 1 - EPYC 76010.00180.00360.00540.00720.0090.008

OpenBenchmarking.orgItems Per Second Per Watt, More Is BetterOSPRay 2.12Benchmark: particle_volume/pathtracer/real_timeZen 1 - EPYC 76010.03650.0730.10950.1460.18250.162

OpenBenchmarking.orgItems Per Second, More Is BetterOSPRay 2.12Benchmark: gravity_spheres_volume/dim_512/ao/real_timeZen 1 - EPYC 76010.58011.16021.74032.32042.9005SE +/- 0.00282, N = 32.57829

OpenBenchmarking.orgItems Per Second, More Is BetterOSPRay 2.12Benchmark: gravity_spheres_volume/dim_512/scivis/real_timeZen 1 - EPYC 76010.55511.11021.66532.22042.7755SE +/- 0.01722, N = 32.46692

OpenBenchmarking.orgItems Per Second, More Is BetterOSPRay 2.12Benchmark: gravity_spheres_volume/dim_512/pathtracer/real_timeZen 1 - EPYC 76010.93341.86682.80023.73364.667SE +/- 0.01550, N = 34.14841

OpenBenchmarking.orgItems Per Second, More Is BetterOSPRay 2.12Benchmark: particle_volume/ao/real_timeZen 1 - EPYC 76011.19012.38023.57034.76045.9505SE +/- 0.01171, N = 35.28931

OpenBenchmarking.orgItems Per Second, More Is BetterOSPRay 2.12Benchmark: particle_volume/scivis/real_timeZen 1 - EPYC 76011.17482.34963.52444.69925.874SE +/- 0.00822, N = 35.22116

OpenBenchmarking.orgItems Per Second, More Is BetterOSPRay 2.12Benchmark: particle_volume/pathtracer/real_timeZen 1 - EPYC 760120406080100SE +/- 0.08, N = 398.44

Neural Magic DeepSparse

This is a benchmark of Neural Magic's DeepSparse using its built-in deepsparse.benchmark utility and various models from their SparseZoo (https://sparsezoo.neuralmagic.com/). Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-StreamZen 1 - EPYC 760160120180240300SE +/- 1.56, N = 3260.25

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-StreamZen 1 - EPYC 760120406080100SE +/- 0.85, N = 690.66

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-StreamZen 1 - EPYC 7601306090120150SE +/- 0.49, N = 3144.68

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-StreamZen 1 - EPYC 76013691215SE +/- 0.04, N = 310.75

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-StreamZen 1 - EPYC 76011632486480SE +/- 0.21, N = 370.34

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-StreamZen 1 - EPYC 76011632486480SE +/- 0.11, N = 370.56

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-StreamZen 1 - EPYC 76013691215SE +/- 0.07, N = 310.81

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-StreamZen 1 - EPYC 76013691215SE +/- 0.0191, N = 39.2992

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-StreamZen 1 - EPYC 7601306090120150SE +/- 1.66, N = 3142.80

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-StreamZen 1 - EPYC 7601306090120150SE +/- 0.49, N = 3155.70

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-StreamZen 1 - EPYC 76013691215SE +/- 0.06, N = 313.26

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.6Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-StreamZen 1 - EPYC 7601306090120150SE +/- 1.27, N = 3131.76

IndigoBench

This is a test of Indigo Renderer's IndigoBench benchmark. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgM samples/s, More Is BetterIndigoBench 4.4Acceleration: CPU - Scene: SupercarZen 1 - EPYC 7601246810SE +/- 0.050, N = 38.580

OpenBenchmarking.orgM samples/s, More Is BetterIndigoBench 4.4Acceleration: CPU - Scene: BedroomZen 1 - EPYC 76010.8981.7962.6943.5924.49SE +/- 0.022, N = 33.991

QuantLib

QuantLib is an open-source library/framework around quantitative finance for modeling, trading and risk management scenarios. QuantLib is written in C++ with Boost and its built-in benchmark used reports the QuantLib Benchmark Index benchmark score. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMFLOPS, More Is BetterQuantLib 1.32Configuration: Multi-ThreadedZen 1 - EPYC 760114K28K42K56K70KSE +/- 8.17, N = 364481.71. (CXX) g++ options: -O3 -march=native -fPIE -pie

7-Zip Compression

OpenBenchmarking.orgMIPS Per Watt, More Is Better7-Zip Compression 22.01Test: Decompression RatingZen 1 - EPYC 760150100150200250214.29

OpenBenchmarking.orgMIPS, More Is Better7-Zip Compression 22.01Test: Compression RatingZen 1 - EPYC 760130K60K90K120K150KSE +/- 1034.27, N = 31239341. (CXX) g++ options: -lpthread -ldl -O2 -fPIC

OpenBenchmarking.orgMIPS, More Is Better7-Zip Compression 22.01Test: Decompression RatingZen 1 - EPYC 760130K60K90K120K150KSE +/- 1450.84, N = 31344171. (CXX) g++ options: -lpthread -ldl -O2 -fPIC

GROMACS

The GROMACS (GROningen MAchine for Chemical Simulations) molecular dynamics package testing with the water_GMX50 data. This test profile allows selecting between CPU and GPU-based GROMACS builds. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgNs Per Day, More Is BetterGROMACS 2023Implementation: MPI CPU - Input: water_GMX50_bareZen 1 - EPYC 76010.44820.89641.34461.79282.241SE +/- 0.017, N = 31.9921. (CXX) g++ options: -O3

LAMMPS Molecular Dynamics Simulator

LAMMPS is a classical molecular dynamics code, and an acronym for Large-scale Atomic/Molecular Massively Parallel Simulator. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgns/day, More Is BetterLAMMPS Molecular Dynamics Simulator 23Jun2022Model: 20k AtomsZen 1 - EPYC 760148121620SE +/- 0.05, N = 313.871. (CXX) g++ options: -O3 -lm -ldl

Apache Cassandra

This is a benchmark of the Apache Cassandra NoSQL database management system making use of cassandra-stress. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgOp/s, More Is BetterApache Cassandra 4.1.3Test: WritesZen 1 - EPYC 760130K60K90K120K150KSE +/- 702.01, N = 3152887

Speedb

Speedb is a next-generation key value storage engine that is RocksDB compatible and aiming for stability, efficiency, and performance. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgOp/s, More Is BetterSpeedb 2.7Test: Random ReadZen 1 - EPYC 760120M40M60M80M100MSE +/- 795244.11, N = 3868670411. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread

OpenBenchmarking.orgOp/s, More Is BetterSpeedb 2.7Test: Read While WritingZen 1 - EPYC 76011.3M2.6M3.9M5.2M6.5MSE +/- 67628.42, N = 361456791. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread

OpenBenchmarking.orgOp/s, More Is BetterSpeedb 2.7Test: Read Random Write RandomZen 1 - EPYC 7601300K600K900K1200K1500KSE +/- 1989.50, N = 314360741. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread

OpenBenchmarking.orgOp/s, More Is BetterSpeedb 2.7Test: Update RandomZen 1 - EPYC 760140K80K120K160K200KSE +/- 239.59, N = 32015551. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread

RocksDB

OpenBenchmarking.orgOp/s Per Watt, More Is BetterRocksDB 8.0Test: Random ReadZen 1 - EPYC 760130K60K90K120K150K125079.64

OpenBenchmarking.orgOp/s Per Watt, More Is BetterRocksDB 8.0Test: Read While WritingZen 1 - EPYC 7601110022003300440055004962.32

OpenBenchmarking.orgOp/s Per Watt, More Is BetterRocksDB 8.0Test: Read Random Write RandomZen 1 - EPYC 760150010001500200025002244.55

OpenBenchmarking.orgOp/s Per Watt, More Is BetterRocksDB 8.0Test: Update RandomZen 1 - EPYC 7601110220330440550502.97

OpenBenchmarking.orgOp/s, More Is BetterRocksDB 8.0Test: Random ReadZen 1 - EPYC 760120M40M60M80M100MSE +/- 416491.60, N = 3847982041. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread

OpenBenchmarking.orgOp/s, More Is BetterRocksDB 8.0Test: Read While WritingZen 1 - EPYC 7601700K1400K2100K2800K3500KSE +/- 34108.45, N = 333718761. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread

OpenBenchmarking.orgOp/s, More Is BetterRocksDB 8.0Test: Read Random Write RandomZen 1 - EPYC 7601300K600K900K1200K1500KSE +/- 4649.81, N = 315091841. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread

OpenBenchmarking.orgOp/s, More Is BetterRocksDB 8.0Test: Update RandomZen 1 - EPYC 760160K120K180K240K300KSE +/- 737.50, N = 32906181. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread

Redis 7.0.12 + memtier_benchmark

OpenBenchmarking.orgOps/sec Per Watt, More Is BetterRedis 7.0.12 + memtier_benchmark 2.0Protocol: Redis - Clients: 100 - Set To Get Ratio: 1:10Zen 1 - EPYC 76014008001200160020001836.86

OpenBenchmarking.orgOps/sec, More Is BetterRedis 7.0.12 + memtier_benchmark 2.0Protocol: Redis - Clients: 100 - Set To Get Ratio: 1:10Zen 1 - EPYC 7601300K600K900K1200K1500KSE +/- 1850.76, N = 31183656.971. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre

OpenBenchmarking.orgOps/sec, More Is BetterRedis 7.0.12 + memtier_benchmark 2.0Protocol: Redis - Clients: 100 - Set To Get Ratio: 1:5Zen 1 - EPYC 7601200K400K600K800K1000KSE +/- 8571.80, N = 111142464.161. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre

Meta Performance Per Watts

OpenBenchmarking.orgPerformance Per Watts, More Is BetterMeta Performance Per WattsPerformance Per WattsZen 1 - EPYC 760150010001500200025002562.10

Apache IoTDB

Apache IotDB is a time series database and this benchmark is facilitated using the IoT Benchmaark [https://github.com/thulab/iot-benchmark/]. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgpoint/sec, More Is BetterApache IoTDB 1.2Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 200 - Client Number: 100Zen 1 - EPYC 76018M16M24M32M40MSE +/- 524500.20, N = 338712263

OpenBenchmarking.orgpoint/sec, More Is BetterApache IoTDB 1.2Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 200 - Client Number: 400Zen 1 - EPYC 76018M16M24M32M40MSE +/- 325879.11, N = 838176456

OpenBenchmarking.orgpoint/sec, More Is BetterApache IoTDB 1.2Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 500 - Client Number: 100Zen 1 - EPYC 760112M24M36M48M60MSE +/- 175336.13, N = 353759940

OpenBenchmarking.orgpoint/sec, More Is BetterApache IoTDB 1.2Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 500 - Client Number: 400Zen 1 - EPYC 760111M22M33M44M55MSE +/- 507374.51, N = 352849125

OpenBenchmarking.orgpoint/sec, More Is BetterApache IoTDB 1.2Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 800 - Client Number: 100Zen 1 - EPYC 760113M26M39M52M65MSE +/- 85534.45, N = 358774090

OpenBenchmarking.orgpoint/sec, More Is BetterApache IoTDB 1.2Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 800 - Client Number: 400Zen 1 - EPYC 760113M26M39M52M65MSE +/- 470631.65, N = 359444334

OpenBenchmarking.orgpoint/sec, More Is BetterApache IoTDB 1.2Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 200 - Client Number: 100Zen 1 - EPYC 760110M20M30M40M50MSE +/- 405601.66, N = 346049589

OpenBenchmarking.orgpoint/sec, More Is BetterApache IoTDB 1.2Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 200 - Client Number: 400Zen 1 - EPYC 760110M20M30M40M50MSE +/- 330018.02, N = 345921074

OpenBenchmarking.orgpoint/sec, More Is BetterApache IoTDB 1.2Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 500 - Client Number: 100Zen 1 - EPYC 760112M24M36M48M60MSE +/- 197187.95, N = 356993811

OpenBenchmarking.orgpoint/sec, More Is BetterApache IoTDB 1.2Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 500 - Client Number: 400Zen 1 - EPYC 760112M24M36M48M60MSE +/- 596691.26, N = 557037441

OpenBenchmarking.orgpoint/sec, More Is BetterApache IoTDB 1.2Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 800 - Client Number: 100Zen 1 - EPYC 760113M26M39M52M65MSE +/- 295389.20, N = 358403756

OpenBenchmarking.orgpoint/sec, More Is BetterApache IoTDB 1.2Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 800 - Client Number: 400Zen 1 - EPYC 760113M26M39M52M65MSE +/- 138623.83, N = 360237625

nginx

OpenBenchmarking.orgRequests Per Second Per Watt, More Is Betternginx 1.23.2Connections: 1000Zen 1 - EPYC 7601306090120150148.96

Apache HTTP Server

OpenBenchmarking.orgRequests Per Second Per Watt, More Is BetterApache HTTP Server 2.4.56Concurrent Requests: 1000Zen 1 - EPYC 7601306090120150132.65

nginx

This is a benchmark of the lightweight Nginx HTTP(S) web-server. This Nginx web server benchmark test profile makes use of the wrk program for facilitating the HTTP requests over a fixed period time with a configurable number of concurrent clients/connections. HTTPS with a self-signed OpenSSL certificate is used by this test for local benchmarking. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgRequests Per Second, More Is Betternginx 1.23.2Connections: 500Zen 1 - EPYC 760120K40K60K80K100KSE +/- 450.48, N = 3103269.831. (CC) gcc options: -lluajit-5.1 -lm -lssl -lcrypto -lpthread -ldl -std=c99 -O2

OpenBenchmarking.orgRequests Per Second, More Is Betternginx 1.23.2Connections: 1000Zen 1 - EPYC 760120K40K60K80K100KSE +/- 212.46, N = 3100664.351. (CC) gcc options: -lluajit-5.1 -lm -lssl -lcrypto -lpthread -ldl -std=c99 -O2

Apache HTTP Server

This is a test of the Apache HTTPD web server. This Apache HTTPD web server benchmark test profile makes use of the wrk program for facilitating the HTTP requests over a fixed period time with a configurable number of concurrent clients. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgRequests Per Second, More Is BetterApache HTTP Server 2.4.56Concurrent Requests: 1000Zen 1 - EPYC 760120K40K60K80K100KSE +/- 319.15, N = 388038.281. (CC) gcc options: -lluajit-5.1 -lm -lssl -lcrypto -lpthread -ldl -std=c99 -O2

OpenSSL

OpenSSL is an open-source toolkit that implements SSL (Secure Sockets Layer) and TLS (Transport Layer Security) protocols. This test profile makes use of the built-in "openssl speed" benchmarking capabilities. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgsign/s, More Is BetterOpenSSL 3.1Algorithm: RSA4096Zen 1 - EPYC 760110002000300040005000SE +/- 8.66, N = 34510.71. (CC) gcc options: -pthread -m64 -O3 -ldl

Kripke

OpenBenchmarking.orgThroughput FoM Per Watt, More Is BetterKripke 1.2.6Zen 1 - EPYC 760160K120K180K240K300K291422.10

OpenBenchmarking.orgThroughput FoM, More Is BetterKripke 1.2.6Zen 1 - EPYC 760140M80M120M160M200MSE +/- 1601742.67, N = 31873759331. (CXX) g++ options: -O3 -fopenmp -ldl

OpenSSL

OpenBenchmarking.orgverify/s Per Watt, More Is BetterOpenSSL 3.1Algorithm: RSA4096Zen 1 - EPYC 760190180270360450432.83

OpenBenchmarking.orgverify/s, More Is BetterOpenSSL 3.1Algorithm: RSA4096Zen 1 - EPYC 760160K120K180K240K300KSE +/- 361.69, N = 3293924.11. (CC) gcc options: -pthread -m64 -O3 -ldl

Chaos Group V-RAY

OpenBenchmarking.orgvsamples Per Watt, More Is BetterChaos Group V-RAY 5.02Mode: CPUZen 1 - EPYC 760181624324034.52

OpenBenchmarking.orgvsamples, More Is BetterChaos Group V-RAY 5.02Mode: CPUZen 1 - EPYC 76014K8K12K16K20KSE +/- 15.72, N = 320175

Apache IoTDB

Apache IotDB is a time series database and this benchmark is facilitated using the IoT Benchmaark [https://github.com/thulab/iot-benchmark/]. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgAverage Latency, Fewer Is BetterApache IoTDB 1.2Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 200 - Client Number: 100Zen 1 - EPYC 76011020304050SE +/- 0.62, N = 346.29MAX: 12751.47

OpenBenchmarking.orgAverage Latency, Fewer Is BetterApache IoTDB 1.2Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 200 - Client Number: 400Zen 1 - EPYC 76014080120160200SE +/- 1.86, N = 8166.00MAX: 27445.2

OpenBenchmarking.orgAverage Latency, Fewer Is BetterApache IoTDB 1.2Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 500 - Client Number: 100Zen 1 - EPYC 760120406080100SE +/- 0.50, N = 385.07MAX: 11426.59

OpenBenchmarking.orgAverage Latency, Fewer Is BetterApache IoTDB 1.2Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 500 - Client Number: 400Zen 1 - EPYC 760160120180240300SE +/- 3.57, N = 3294.75MAX: 29204.63

OpenBenchmarking.orgAverage Latency, Fewer Is BetterApache IoTDB 1.2Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 800 - Client Number: 100Zen 1 - EPYC 7601306090120150SE +/- 0.22, N = 3127.26MAX: 10220.3

OpenBenchmarking.orgAverage Latency, Fewer Is BetterApache IoTDB 1.2Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 800 - Client Number: 400Zen 1 - EPYC 760190180270360450SE +/- 5.76, N = 3421.30MAX: 27834.33

OpenBenchmarking.orgAverage Latency, Fewer Is BetterApache IoTDB 1.2Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 200 - Client Number: 100Zen 1 - EPYC 7601918273645SE +/- 0.33, N = 339.40MAX: 23930.49

OpenBenchmarking.orgAverage Latency, Fewer Is BetterApache IoTDB 1.2Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 200 - Client Number: 400Zen 1 - EPYC 7601306090120150SE +/- 1.86, N = 3147.89MAX: 27830.18

OpenBenchmarking.orgAverage Latency, Fewer Is BetterApache IoTDB 1.2Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 500 - Client Number: 100Zen 1 - EPYC 760120406080100SE +/- 0.21, N = 382.07MAX: 23993.13

OpenBenchmarking.orgAverage Latency, Fewer Is BetterApache IoTDB 1.2Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 500 - Client Number: 400Zen 1 - EPYC 760170140210280350SE +/- 4.76, N = 5318.24MAX: 28518.21

OpenBenchmarking.orgAverage Latency, Fewer Is BetterApache IoTDB 1.2Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 800 - Client Number: 100Zen 1 - EPYC 7601306090120150SE +/- 0.61, N = 3129.77MAX: 23980.17

OpenBenchmarking.orgAverage Latency, Fewer Is BetterApache IoTDB 1.2Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 800 - Client Number: 400Zen 1 - EPYC 7601110220330440550SE +/- 3.72, N = 3488.64MAX: 28615.16

NAMD

NAMD is a parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems. NAMD was developed by the Theoretical and Computational Biophysics Group in the Beckman Institute for Advanced Science and Technology at the University of Illinois at Urbana-Champaign. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgdays/ns, Fewer Is BetterNAMD 2.14ATPase Simulation - 327,506 AtomsZen 1 - EPYC 76010.22040.44080.66120.88161.102SE +/- 0.00385, N = 30.97959

OSPRay Studio

Intel OSPRay Studio is an open-source, interactive visualization and ray-tracing software package. OSPRay Studio makes use of Intel OSPRay, a portable ray-tracing engine for high-performance, high-fidelity visualizations. OSPRay builds off Intel's Embree and Intel SPMD Program Compiler (ISPC) components as part of the oneAPI rendering toolkit. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.13Camera: 1 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPUZen 1 - EPYC 76012K4K6K8K10KSE +/- 16.50, N = 38478

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.13Camera: 1 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPUZen 1 - EPYC 760130K60K90K120K150KSE +/- 81.84, N = 3145528

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.13Camera: 1 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPUZen 1 - EPYC 760160K120K180K240K300KSE +/- 353.76, N = 3280606

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.13Camera: 3 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPUZen 1 - EPYC 76012K4K6K8K10KSE +/- 34.23, N = 310050

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.13Camera: 3 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPUZen 1 - EPYC 760140K80K120K160K200KSE +/- 133.22, N = 3171188

OpenBenchmarking.orgms, Fewer Is BetterOSPRay Studio 0.13Camera: 3 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPUZen 1 - EPYC 760170K140K210K280K350KSE +/- 188.22, N = 3331643

OpenVINO

This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.2.devModel: Face Detection FP16-INT8 - Device: CPUZen 1 - EPYC 7601400800120016002000SE +/- 0.06, N = 32094.21MIN: 2092.79 / MAX: 2112.411. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -pie

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.2.devModel: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPUZen 1 - EPYC 76010.54681.09361.64042.18722.734SE +/- 0.00, N = 32.43MIN: 2.39 / MAX: 10.021. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -pie

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.2.devModel: Person Detection FP16 - Device: CPUZen 1 - EPYC 76014080120160200SE +/- 0.36, N = 3181.92MIN: 171.42 / MAX: 202.331. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -pie

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.2.devModel: Weld Porosity Detection FP16-INT8 - Device: CPUZen 1 - EPYC 760120406080100SE +/- 0.00, N = 384.68MIN: 84.05 / MAX: 93.441. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -pie

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.2.devModel: Vehicle Detection FP16-INT8 - Device: CPUZen 1 - EPYC 7601612182430SE +/- 0.03, N = 327.01MIN: 26.86 / MAX: 38.571. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -pie

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.2.devModel: Person Vehicle Bike Detection FP16 - Device: CPUZen 1 - EPYC 760148121620SE +/- 0.06, N = 316.95MIN: 16.19 / MAX: 27.981. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -pie

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.2.devModel: Machine Translation EN To DE FP16 - Device: CPUZen 1 - EPYC 76014080120160200SE +/- 0.49, N = 3193.33MIN: 178.13 / MAX: 252.211. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -pie

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.2.devModel: Face Detection Retail FP16-INT8 - Device: CPUZen 1 - EPYC 76013691215SE +/- 0.00, N = 39.1MIN: 9.04 / MAX: 17.251. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -pie

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.2.devModel: Handwritten English Recognition FP16-INT8 - Device: CPUZen 1 - EPYC 76014080120160200SE +/- 0.65, N = 3169.04MIN: 141.74 / MAX: 192.161. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -pie

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2023.2.devModel: Road Segmentation ADAS FP16-INT8 - Device: CPUZen 1 - EPYC 76011224364860SE +/- 0.05, N = 353.47MIN: 52.68 / MAX: 66.731. (CXX) g++ options: -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -pie

Neural Magic DeepSparse

This is a benchmark of Neural Magic's DeepSparse using its built-in deepsparse.benchmark utility and various models from their SparseZoo (https://sparsezoo.neuralmagic.com/). Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-StreamZen 1 - EPYC 76011428425670SE +/- 0.36, N = 361.39

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-StreamZen 1 - EPYC 76014080120160200SE +/- 1.64, N = 6176.43

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-StreamZen 1 - EPYC 760120406080100SE +/- 0.40, N = 3110.45

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-StreamZen 1 - EPYC 760130060090012001500SE +/- 5.55, N = 31457.92

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-StreamZen 1 - EPYC 760150100150200250SE +/- 0.66, N = 3226.95

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-StreamZen 1 - EPYC 760150100150200250SE +/- 0.35, N = 3226.37

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-StreamZen 1 - EPYC 760130060090012001500SE +/- 2.60, N = 31460.70

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-StreamZen 1 - EPYC 7601400800120016002000SE +/- 3.29, N = 31701.37

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-StreamZen 1 - EPYC 7601306090120150SE +/- 1.29, N = 3111.90

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-StreamZen 1 - EPYC 760120406080100SE +/- 0.30, N = 3102.66

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-StreamZen 1 - EPYC 760130060090012001500SE +/- 3.61, N = 31200.10

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.6Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-StreamZen 1 - EPYC 7601306090120150SE +/- 1.16, N = 3121.21

DuckDB

DuckDB is an in-progress SQL OLAP database management system optimized for analytics and features a vectorized and parallel engine. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterDuckDB 0.9.1Benchmark: IMDBZen 1 - EPYC 76014080120160200SE +/- 0.56, N = 3199.011. (CXX) g++ options: -O3 -rdynamic -lssl -lcrypto -ldl

OpenBenchmarking.orgSeconds, Fewer Is BetterDuckDB 0.9.1Benchmark: TPC-H ParquetZen 1 - EPYC 760150100150200250SE +/- 0.21, N = 3245.741. (CXX) g++ options: -O3 -rdynamic -lssl -lcrypto -ldl

Timed Linux Kernel Compilation

This test times how long it takes to build the Linux kernel in a default configuration (defconfig) for the architecture being tested or alternatively an allmodconfig for building all possible kernel modules for the build. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed Linux Kernel Compilation 6.1Build: defconfigZen 1 - EPYC 760120406080100SE +/- 0.88, N = 376.30

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed Linux Kernel Compilation 6.1Build: allmodconfigZen 1 - EPYC 7601160320480640800SE +/- 0.57, N = 3755.02

Timed LLVM Compilation

This test times how long it takes to compile/build the LLVM compiler stack. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed LLVM Compilation 16.0Build System: NinjaZen 1 - EPYC 760190180270360450SE +/- 1.49, N = 3435.05

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed LLVM Compilation 16.0Build System: Unix MakefilesZen 1 - EPYC 7601110220330440550SE +/- 1.95, N = 3529.72

Timed Node.js Compilation

This test profile times how long it takes to build/compile Node.js itself from source. Node.js is a JavaScript run-time built from the Chrome V8 JavaScript engine while itself is written in C/C++. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed Node.js Compilation 19.8.1Time To CompileZen 1 - EPYC 760180160240320400SE +/- 0.64, N = 3387.65

Timed Gem5 Compilation

This test times how long it takes to compile Gem5. Gem5 is a simulator for computer system architecture research. Gem5 is widely used for computer architecture research within the industry, academia, and more. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed Gem5 Compilation 23.0.1Time To CompileZen 1 - EPYC 760180160240320400SE +/- 4.50, N = 3388.02

Timed FFmpeg Compilation

This test times how long it takes to build the FFmpeg multimedia library. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed FFmpeg Compilation 6.1Time To CompileZen 1 - EPYC 7601918273645SE +/- 0.10, N = 339.79

SPECFEM3D

simulates acoustic (fluid), elastic (solid), coupled acoustic/elastic, poroelastic or seismic wave propagation in any type of conforming mesh of hexahedra. This test profile currently relies on CPU-based execution for SPECFEM3D and using a variety of their built-in examples/models for benchmarking. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterSPECFEM3D 4.0Model: Layered HalfspaceZen 1 - EPYC 760120406080100SE +/- 0.98, N = 378.681. (F9X) gfortran options: -O2 -fopenmp -std=f2003 -fimplicit-none -fmax-errors=10 -pedantic -pedantic-errors -O3 -finline-functions -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -levent_core -levent_pthreads -lm -lz

OpenBenchmarking.orgSeconds, Fewer Is BetterSPECFEM3D 4.0Model: Water-layered HalfspaceZen 1 - EPYC 760120406080100SE +/- 0.29, N = 374.951. (F9X) gfortran options: -O2 -fopenmp -std=f2003 -fimplicit-none -fmax-errors=10 -pedantic -pedantic-errors -O3 -finline-functions -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -levent_core -levent_pthreads -lm -lz

OpenBenchmarking.orgSeconds, Fewer Is BetterSPECFEM3D 4.0Model: Homogeneous HalfspaceZen 1 - EPYC 7601918273645SE +/- 0.31, N = 338.061. (F9X) gfortran options: -O2 -fopenmp -std=f2003 -fimplicit-none -fmax-errors=10 -pedantic -pedantic-errors -O3 -finline-functions -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -levent_core -levent_pthreads -lm -lz

OpenBenchmarking.orgSeconds, Fewer Is BetterSPECFEM3D 4.0Model: Mount St. HelensZen 1 - EPYC 7601714212835SE +/- 0.41, N = 329.951. (F9X) gfortran options: -O2 -fopenmp -std=f2003 -fimplicit-none -fmax-errors=10 -pedantic -pedantic-errors -O3 -finline-functions -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -levent_core -levent_pthreads -lm -lz

OpenBenchmarking.orgSeconds, Fewer Is BetterSPECFEM3D 4.0Model: Tomographic ModelZen 1 - EPYC 7601714212835SE +/- 0.13, N = 330.281. (F9X) gfortran options: -O2 -fopenmp -std=f2003 -fimplicit-none -fmax-errors=10 -pedantic -pedantic-errors -O3 -finline-functions -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -levent_core -levent_pthreads -lm -lz

OpenFOAM

OpenFOAM is the leading free, open-source software for computational fluid dynamics (CFD). This test profile currently uses the drivaerFastback test case for analyzing automotive aerodynamics or alternatively the older motorBike input. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterOpenFOAM 10Input: drivaerFastback, Small Mesh Size - Mesh TimeZen 1 - EPYC 7601102030405044.451. (CXX) g++ options: -std=c++14 -m64 -O3 -ftemplate-depth-100 -fPIC -fuse-ld=bfd -Xlinker --add-needed --no-as-needed -lfoamToVTK -ldynamicMesh -llagrangian -lgenericPatchFields -lfileFormats -lOpenFOAM -ldl -lm

OpenBenchmarking.orgSeconds, Fewer Is BetterOpenFOAM 10Input: drivaerFastback, Small Mesh Size - Execution TimeZen 1 - EPYC 7601306090120150126.191. (CXX) g++ options: -std=c++14 -m64 -O3 -ftemplate-depth-100 -fPIC -fuse-ld=bfd -Xlinker --add-needed --no-as-needed -lfoamToVTK -ldynamicMesh -llagrangian -lgenericPatchFields -lfileFormats -lOpenFOAM -ldl -lm

OpenBenchmarking.orgSeconds, Fewer Is BetterOpenFOAM 10Input: drivaerFastback, Medium Mesh Size - Mesh TimeZen 1 - EPYC 760150100150200250231.741. (CXX) g++ options: -std=c++14 -m64 -O3 -ftemplate-depth-100 -fPIC -fuse-ld=bfd -Xlinker --add-needed --no-as-needed -lfoamToVTK -ldynamicMesh -llagrangian -lgenericPatchFields -lfileFormats -lOpenFOAM -ldl -lm

OpenBenchmarking.orgSeconds, Fewer Is BetterOpenFOAM 10Input: drivaerFastback, Medium Mesh Size - Execution TimeZen 1 - EPYC 7601300600900120015001179.251. (CXX) g++ options: -std=c++14 -m64 -O3 -ftemplate-depth-100 -fPIC -fuse-ld=bfd -Xlinker --add-needed --no-as-needed -lfoamToVTK -ldynamicMesh -llagrangian -lgenericPatchFields -lfileFormats -lOpenFOAM -ldl -lm

OpenRadioss

OpenRadioss is an open-source AGPL-licensed finite element solver for dynamic event analysis OpenRadioss is based on Altair Radioss and open-sourced in 2022. This open-source finite element solver is benchmarked with various example models available from https://www.openradioss.org/models/ and https://github.com/OpenRadioss/ModelExchange/tree/main/Examples. This test is currently using a reference OpenRadioss binary build offered via GitHub. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterOpenRadioss 2023.09.15Model: Chrysler Neon 1MZen 1 - EPYC 7601110220330440550SE +/- 0.62, N = 3499.30

easyWave

The easyWave software allows simulating tsunami generation and propagation in the context of early warning systems. EasyWave supports making use of OpenMP for CPU multi-threading and there are also GPU ports available but not currently incorporated as part of this test profile. The easyWave tsunami generation software is run with one of the example/reference input files for measuring the CPU execution time. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BettereasyWave r34Input: e2Asean Grid + BengkuluSept2007 Source - Time: 1200Zen 1 - EPYC 7601306090120150SE +/- 1.77, N = 4148.081. (CXX) g++ options: -O3 -fopenmp

OpenBenchmarking.orgSeconds, Fewer Is BettereasyWave r34Input: e2Asean Grid + BengkuluSept2007 Source - Time: 2400Zen 1 - EPYC 760180160240320400SE +/- 6.02, N = 6352.691. (CXX) g++ options: -O3 -fopenmp

GPAW

GPAW is a density-functional theory (DFT) Python code based on the projector-augmented wave (PAW) method and the atomic simulation environment (ASE). Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterGPAW 23.6Input: Carbon NanotubeZen 1 - EPYC 7601306090120150SE +/- 0.91, N = 3142.171. (CC) gcc options: -shared -fwrapv -O2 -lxc -lblas -lmpi

CloverLeaf

CloverLeaf is a Lagrangian-Eulerian hydrodynamics benchmark. This test profile currently makes use of CloverLeaf's OpenMP version. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterCloverLeaf 1.3Input: clover_bm64_shortZen 1 - EPYC 760120406080100SE +/- 1.39, N = 3108.601. (F9X) gfortran options: -O3 -march=native -funroll-loops -fopenmp

OpenBenchmarking.orgSeconds, Fewer Is BetterCloverLeaf 1.3Input: clover_bm16Zen 1 - EPYC 76012004006008001000SE +/- 1.74, N = 3971.501. (F9X) gfortran options: -O3 -march=native -funroll-loops -fopenmp

Xcompact3d Incompact3d

Xcompact3d Incompact3d is a Fortran-MPI based, finite difference high-performance code for solving the incompressible Navier-Stokes equation and as many as you need scalar transport equations. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterXcompact3d Incompact3d 2021-03-11Input: input.i3d 193 Cells Per DirectionZen 1 - EPYC 7601918273645SE +/- 0.22, N = 337.411. (F9X) gfortran options: -cpp -O2 -funroll-loops -floop-optimize -fcray-pointer -fbacktrace -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -levent_core -levent_pthreads -lm -lz

OpenBenchmarking.orgSeconds, Fewer Is BetterXcompact3d Incompact3d 2021-03-11Input: X3D-benchmarking input.i3dZen 1 - EPYC 76012004006008001000SE +/- 0.24, N = 3818.051. (F9X) gfortran options: -cpp -O2 -funroll-loops -floop-optimize -fcray-pointer -fbacktrace -lmpi_usempif08 -lmpi_mpifh -lmpi -lopen-rte -lopen-pal -lhwloc -levent_core -levent_pthreads -lm -lz

Y-Cruncher

Y-Cruncher is a multi-threaded Pi benchmark capable of computing Pi to trillions of digits. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterY-Cruncher 0.8.3Pi Digits To Calculate: 500MZen 1 - EPYC 760148121620SE +/- 0.12, N = 315.69

OpenBenchmarking.orgSeconds, Fewer Is BetterY-Cruncher 0.8.3Pi Digits To Calculate: 1BZen 1 - EPYC 7601816243240SE +/- 0.09, N = 333.92

Timed MrBayes Analysis

This test performs a bayesian analysis of a set of primate genome sequences in order to estimate their phylogeny. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed MrBayes Analysis 3.2.7Primate Phylogeny AnalysisZen 1 - EPYC 76014080120160200SE +/- 4.88, N = 12201.181. (CC) gcc options: -mmmx -msse -msse2 -msse3 -mssse3 -msse4.1 -msse4.2 -msse4a -msha -maes -mavx -mfma -mavx2 -mrdrnd -mbmi -mbmi2 -madx -mabm -O3 -std=c99 -pedantic -lm -lreadline

Blender

Blender is an open-source 3D creation and modeling software project. This test is of Blender's Cycles performance with various sample files. GPU computing via NVIDIA OptiX and NVIDIA CUDA is currently supported as well as HIP for AMD Radeon GPUs and Intel oneAPI for Intel Graphics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.0Blend File: BMW27 - Compute: CPU-OnlyZen 1 - EPYC 76011632486480SE +/- 0.35, N = 373.00

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.0Blend File: Classroom - Compute: CPU-OnlyZen 1 - EPYC 76014080120160200SE +/- 1.40, N = 3192.80

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.0Blend File: Fishy Cat - Compute: CPU-OnlyZen 1 - EPYC 760120406080100SE +/- 0.13, N = 3101.20

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.0Blend File: Pabellon Barcelona - Compute: CPU-OnlyZen 1 - EPYC 760150100150200250SE +/- 0.13, N = 3247.24

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.0Blend File: Barbershop - Compute: CPU-OnlyZen 1 - EPYC 7601170340510680850SE +/- 0.52, N = 3767.15

221 Results Shown

CPU Power Consumption Monitor:
  Phoronix Test Suite System Monitoring
  CPU - 1 - ResNet-50
  CPU - 256 - ResNet-50
PyTorch:
  CPU - 1 - ResNet-50
  CPU - 256 - ResNet-50
miniBUDE:
  OpenMP - BM1
  OpenMP - BM2
miniBUDE:
  OpenMP - BM1
  OpenMP - BM2
OpenSSL:
  SHA256
  SHA512
OpenSSL
OpenSSL:
  AES-128-GCM
  AES-256-GCM
  ChaCha20
OpenSSL
OpenSSL
OpenSSL:
  SHA512
  AES-256-GCM
  ChaCha20
  ChaCha20-Poly1305
Quicksilver:
  CORAL2 P1
  CORAL2 P2
Quicksilver
Quicksilver
FFmpeg
FFmpeg:
  libx265 - Live
  libx265 - Platform
FFmpeg
FFmpeg:
  libx265 - Upload
  libx265 - Video On Demand
OpenVINO:
  Face Detection FP16-INT8 - CPU
  Age Gender Recognition Retail 0013 FP16-INT8 - CPU
  Person Detection FP16 - CPU
  Weld Porosity Detection FP16-INT8 - CPU
  Vehicle Detection FP16-INT8 - CPU
  Person Vehicle Bike Detection FP16 - CPU
  Machine Translation EN To DE FP16 - CPU
  Face Detection Retail FP16-INT8 - CPU
  Handwritten English Recognition FP16-INT8 - CPU
  Road Segmentation ADAS FP16-INT8 - CPU
Embree
Embree:
  Pathtracer ISPC - Asian Dragon
  Pathtracer ISPC - Crown
SVT-AV1:
  Preset 13 - Bosphorus 4K
  Preset 12 - Bosphorus 4K
  Preset 8 - Bosphorus 4K
  Preset 4 - Bosphorus 4K
uvg266:
  Bosphorus 4K - Very Fast
  Bosphorus 4K - Ultra Fast
VVenC
rav1e
rav1e
rav1e
uvg266:
  Bosphorus 4K - Medium
  Bosphorus 4K - Super Fast
rav1e:
  5
  1
  Bosphorus 4K
  Bosphorus 4K - Fast
rav1e:
  5
  1
x265
VVenC
miniBUDE:
  OpenMP - BM1
  OpenMP - BM2
ACES DGEMM
ACES DGEMM
Xmrig:
  Wownero - 1M
  CryptoNight-Femto UPX2 - 1M
  CryptoNight-Heavy - 1M
  KawPow - 1M
  GhostRider - 1M
Xmrig
Xmrig
Intel Open Image Denoise
TensorFlow
OSPRay:
  particle_volume/ao/real_time
  particle_volume/pathtracer/real_time
OSPRay:
  gravity_spheres_volume/dim_512/ao/real_time
  gravity_spheres_volume/dim_512/scivis/real_time
  gravity_spheres_volume/dim_512/pathtracer/real_time
  particle_volume/ao/real_time
  particle_volume/scivis/real_time
  particle_volume/pathtracer/real_time
Neural Magic DeepSparse:
  NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Asynchronous Multi-Stream
  NLP Text Classification, DistilBERT mnli - Asynchronous Multi-Stream
  CV Classification, ResNet-50 ImageNet - Asynchronous Multi-Stream
  NLP Token Classification, BERT base uncased conll2003 - Asynchronous Multi-Stream
  CV Detection, YOLOv5s COCO - Asynchronous Multi-Stream
  CV Detection, YOLOv5s COCO, Sparse INT8 - Asynchronous Multi-Stream
  NLP Document Classification, oBERT base uncased on IMDB - Asynchronous Multi-Stream
  CV Segmentation, 90% Pruned YOLACT Pruned - Asynchronous Multi-Stream
  ResNet-50, Baseline - Asynchronous Multi-Stream
  ResNet-50, Sparse INT8 - Asynchronous Multi-Stream
  BERT-Large, NLP Question Answering - Asynchronous Multi-Stream
  BERT-Large, NLP Question Answering, Sparse INT8 - Asynchronous Multi-Stream
IndigoBench:
  CPU - Supercar
  CPU - Bedroom
QuantLib
7-Zip Compression
7-Zip Compression:
  Compression Rating
  Decompression Rating
GROMACS
LAMMPS Molecular Dynamics Simulator
Apache Cassandra
Speedb:
  Rand Read
  Read While Writing
  Read Rand Write Rand
  Update Rand
RocksDB:
  Rand Read
  Read While Writing
  Read Rand Write Rand
  Update Rand
RocksDB:
  Rand Read
  Read While Writing
  Read Rand Write Rand
  Update Rand
Redis 7.0.12 + memtier_benchmark
Redis 7.0.12 + memtier_benchmark:
  Redis - 100 - 1:10
  Redis - 100 - 1:5
Meta Performance Per Watts
Apache IoTDB:
  500 - 100 - 200 - 100
  500 - 100 - 200 - 400
  500 - 100 - 500 - 100
  500 - 100 - 500 - 400
  500 - 100 - 800 - 100
  500 - 100 - 800 - 400
  800 - 100 - 200 - 100
  800 - 100 - 200 - 400
  800 - 100 - 500 - 100
  800 - 100 - 500 - 400
  800 - 100 - 800 - 100
  800 - 100 - 800 - 400
nginx:
  1000:
    Requests Per Second Per Watt
    Requests Per Second Per Watt
nginx:
  500
  1000
Apache HTTP Server
OpenSSL
Kripke
Kripke
OpenSSL
OpenSSL
Chaos Group V-RAY
Chaos Group V-RAY
Apache IoTDB:
  500 - 100 - 200 - 100
  500 - 100 - 200 - 400
  500 - 100 - 500 - 100
  500 - 100 - 500 - 400
  500 - 100 - 800 - 100
  500 - 100 - 800 - 400
  800 - 100 - 200 - 100
  800 - 100 - 200 - 400
  800 - 100 - 500 - 100
  800 - 100 - 500 - 400
  800 - 100 - 800 - 100
  800 - 100 - 800 - 400
NAMD
OSPRay Studio:
  1 - 4K - 1 - Path Tracer - CPU
  1 - 4K - 16 - Path Tracer - CPU
  1 - 4K - 32 - Path Tracer - CPU
  3 - 4K - 1 - Path Tracer - CPU
  3 - 4K - 16 - Path Tracer - CPU
  3 - 4K - 32 - Path Tracer - CPU
OpenVINO:
  Face Detection FP16-INT8 - CPU
  Age Gender Recognition Retail 0013 FP16-INT8 - CPU
  Person Detection FP16 - CPU
  Weld Porosity Detection FP16-INT8 - CPU
  Vehicle Detection FP16-INT8 - CPU
  Person Vehicle Bike Detection FP16 - CPU
  Machine Translation EN To DE FP16 - CPU
  Face Detection Retail FP16-INT8 - CPU
  Handwritten English Recognition FP16-INT8 - CPU
  Road Segmentation ADAS FP16-INT8 - CPU
Neural Magic DeepSparse:
  NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Asynchronous Multi-Stream
  NLP Text Classification, DistilBERT mnli - Asynchronous Multi-Stream
  CV Classification, ResNet-50 ImageNet - Asynchronous Multi-Stream
  NLP Token Classification, BERT base uncased conll2003 - Asynchronous Multi-Stream
  CV Detection, YOLOv5s COCO - Asynchronous Multi-Stream
  CV Detection, YOLOv5s COCO, Sparse INT8 - Asynchronous Multi-Stream
  NLP Document Classification, oBERT base uncased on IMDB - Asynchronous Multi-Stream
  CV Segmentation, 90% Pruned YOLACT Pruned - Asynchronous Multi-Stream
  ResNet-50, Baseline - Asynchronous Multi-Stream
  ResNet-50, Sparse INT8 - Asynchronous Multi-Stream
  BERT-Large, NLP Question Answering - Asynchronous Multi-Stream
  BERT-Large, NLP Question Answering, Sparse INT8 - Asynchronous Multi-Stream
DuckDB:
  IMDB
  TPC-H Parquet
Timed Linux Kernel Compilation:
  defconfig
  allmodconfig
Timed LLVM Compilation:
  Ninja
  Unix Makefiles
Timed Node.js Compilation
Timed Gem5 Compilation
Timed FFmpeg Compilation
SPECFEM3D:
  Layered Halfspace
  Water-layered Halfspace
  Homogeneous Halfspace
  Mount St. Helens
  Tomographic Model
OpenFOAM:
  drivaerFastback, Small Mesh Size - Mesh Time
  drivaerFastback, Small Mesh Size - Execution Time
  drivaerFastback, Medium Mesh Size - Mesh Time
  drivaerFastback, Medium Mesh Size - Execution Time
OpenRadioss
easyWave:
  e2Asean Grid + BengkuluSept2007 Source - 1200
  e2Asean Grid + BengkuluSept2007 Source - 2400
GPAW
CloverLeaf:
  clover_bm64_short
  clover_bm16
Xcompact3d Incompact3d:
  input.i3d 193 Cells Per Direction
  X3D-benchmarking input.i3d
Y-Cruncher:
  500M
  1B
Timed MrBayes Analysis
Blender:
  BMW27 - CPU-Only
  Classroom - CPU-Only
  Fishy Cat - CPU-Only
  Pabellon Barcelona - CPU-Only
  Barbershop - CPU-Only