AMD Ryzen 7 7800X3D 8-Core testing with a ASUS ROG CROSSHAIR X670E HERO (9927 BIOS) and AMD Radeon RX 7900 XTX on Ubuntu 23.04 via the Phoronix Test Suite.
a Kernel Notes: Transparent Huge Pages: madviseCompiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --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-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-defaulted --enable-offload-targets=nvptx-none=/build/gcc-12-Pa930Z/gcc-12-12.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-12-Pa930Z/gcc-12-12.2.0/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-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 -vProcessor Notes: Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0xa601203Java Notes: OpenJDK Runtime Environment (build 17.0.6+10-Ubuntu-1ubuntu2)Python Notes: Python 3.11.2Security Notes: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Retpolines IBPB: conditional IBRS_FW STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected
b Processor: AMD Ryzen 7 7800X3D 8-Core @ 4.20GHz (8 Cores / 16 Threads), Motherboard: ASUS ROG CROSSHAIR X670E HERO (9927 BIOS), Chipset: AMD Device 14d8, Memory: 32GB, Disk: Western Digital WD_BLACK SN850X 1000GB, Graphics: AMD Radeon RX 7900 XTX (2304/1249MHz), Audio: AMD Device ab30, Monitor: ASUS MG28U, Network: Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411
OS: Ubuntu 23.04, Kernel: 6.2.8-060208-generic (x86_64), Desktop: GNOME Shell 44.0, Display Server: X Server 1.21.1.7 + Wayland, OpenGL: 4.6 Mesa 23.1.0-devel (git-de8b14f 2023-03-24 lunar-oibaf-ppa) (LLVM 15.0.7 DRM 3.49), OpenCL: OpenCL 2.1 AMD-APP (3513.0), Compiler: GCC 12.2.0, File-System: ext4, Screen Resolution: 3840x2160
AMD Ryzen 7 7800X3D Linux OpenBenchmarking.org Phoronix Test Suite AMD Ryzen 7 7800X3D 8-Core @ 4.20GHz (8 Cores / 16 Threads) ASUS ROG CROSSHAIR X670E HERO (9927 BIOS) AMD Device 14d8 32GB Western Digital WD_BLACK SN850X 1000GB AMD Radeon RX 7900 XTX (2304/1249MHz) AMD Device ab30 ASUS MG28U Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411 Ubuntu 23.04 6.2.8-060208-generic (x86_64) GNOME Shell 44.0 X Server 1.21.1.7 + Wayland 4.6 Mesa 23.1.0-devel (git-de8b14f 2023-03-24 lunar-oibaf-ppa) (LLVM 15.0.7 DRM 3.49) OpenCL 2.1 AMD-APP (3513.0) GCC 12.2.0 ext4 3840x2160 Processor Motherboard Chipset Memory Disk Graphics Audio Monitor Network OS Kernel Desktop Display Server OpenGL OpenCL Compiler File-System Screen Resolution AMD Ryzen 7 7800X3D Linux Benchmarks System Logs - Transparent Huge Pages: madvise - --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --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-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-defaulted --enable-offload-targets=nvptx-none=/build/gcc-12-Pa930Z/gcc-12-12.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-12-Pa930Z/gcc-12-12.2.0/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-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: 0xa601203 - OpenJDK Runtime Environment (build 17.0.6+10-Ubuntu-1ubuntu2) - Python 3.11.2 - itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Retpolines IBPB: conditional IBRS_FW STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected
a vs. b Comparison Phoronix Test Suite Baseline +2.5% +2.5% +5% +5% +7.5% +7.5% +10% +10% 4.3% 4.2% 3.7% 3.3% 3% 2.5% d.S.M.S - Mesh Time 10% F.B.t.B.F.F 6.2% tConvolve OpenMP - Gridding 6.1% tConvolve MT - Degridding 4.3% S.F.P.R tConvolve MPI - Gridding D.B.s - f32 - CPU ALS Movie Lens tConvolve MPI - Degridding 3.2% A.U.C.T 3.2% Apache Spark Bayes tConvolve MT - Gridding 2.8% F.D.F 200 2.2% OpenFOAM GNU Radio ASKAP ASKAP ACES DGEMM ASKAP oneDNN Renaissance ASKAP Renaissance Renaissance ASKAP GNU Radio Apache HTTP Server a b
AMD Ryzen 7 7800X3D Linux amg: mt-dgemm: Sustained Floating-Point Rate xmrig: Monero - 1M xmrig: Wownero - 1M tensorflow: CPU - 32 - AlexNet tensorflow: CPU - 64 - AlexNet tensorflow: CPU - 32 - GoogLeNet tensorflow: CPU - 32 - ResNet-50 tensorflow: CPU - 64 - GoogLeNet tensorflow: CPU - 64 - ResNet-50 askap: Hogbom Clean OpenMP gnuradio: Five Back to Back FIR Filters gnuradio: Signal Source (Cosine) gnuradio: FIR Filter gnuradio: IIR Filter gnuradio: FM Deemphasis Filter gnuradio: Hilbert Transform askap: tConvolve MT - Gridding askap: tConvolve MT - Degridding askap: tConvolve OpenMP - Gridding askap: tConvolve OpenMP - Degridding compress-7zip: Compression Rating compress-7zip: Decompression Rating askap: tConvolve MPI - Degridding askap: tConvolve MPI - Gridding astcenc: Fast astcenc: Medium astcenc: Thorough astcenc: Exhaustive memcached: 1:5 memcached: 1:10 memcached: 1:100 clickhouse: 100M Rows Hits Dataset, First Run / Cold Cache clickhouse: 100M Rows Hits Dataset, Second Run clickhouse: 100M Rows Hits Dataset, Third Run nginx: 100 nginx: 200 nginx: 500 nginx: 1000 apache: 100 apache: 200 apache: 500 apache: 1000 pennant: sedovbig pennant: leblancbig renaissance: Scala Dotty renaissance: Rand Forest renaissance: ALS Movie Lens renaissance: Apache Spark ALS renaissance: Apache Spark Bayes renaissance: Savina Reactors.IO renaissance: Apache Spark PageRank renaissance: Finagle HTTP Requests renaissance: Akka Unbalanced Cobwebbed Tree renaissance: Genetic Algorithm Using Jenetics + Futures onednn: IP Shapes 1D - f32 - CPU onednn: IP Shapes 3D - f32 - CPU onednn: IP Shapes 1D - u8s8f32 - CPU onednn: IP Shapes 3D - u8s8f32 - CPU onednn: IP Shapes 1D - bf16bf16bf16 - CPU onednn: IP Shapes 3D - bf16bf16bf16 - CPU onednn: Convolution Batch Shapes Auto - f32 - CPU onednn: Deconvolution Batch shapes_1d - f32 - CPU onednn: Deconvolution Batch shapes_3d - f32 - CPU onednn: Convolution Batch Shapes Auto - u8s8f32 - CPU onednn: Deconvolution Batch shapes_1d - u8s8f32 - CPU onednn: Deconvolution Batch shapes_3d - u8s8f32 - CPU onednn: Recurrent Neural Network Training - f32 - CPU onednn: Recurrent Neural Network Inference - f32 - CPU onednn: Recurrent Neural Network Training - u8s8f32 - CPU onednn: Convolution Batch Shapes Auto - bf16bf16bf16 - CPU onednn: Deconvolution Batch shapes_1d - bf16bf16bf16 - CPU onednn: Deconvolution Batch shapes_3d - bf16bf16bf16 - CPU onednn: Recurrent Neural Network Inference - u8s8f32 - CPU onednn: Recurrent Neural Network Training - bf16bf16bf16 - CPU onednn: Recurrent Neural Network Inference - bf16bf16bf16 - CPU cloverleaf: Lagrangian-Eulerian Hydrodynamics openfoam: drivaerFastback, Small Mesh Size - Mesh Time openfoam: drivaerFastback, Small Mesh Size - Execution Time openfoam: drivaerFastback, Medium Mesh Size - Mesh Time openfoam: drivaerFastback, Medium Mesh Size - Execution Time build-godot: Time To Compile build-linux-kernel: defconfig build2: Time To Compile blender: BMW27 - CPU-Only numenta-nab: KNN CAD numenta-nab: Relative Entropy numenta-nab: Windowed Gaussian numenta-nab: Earthgecko Skyline numenta-nab: Bayesian Changepoint numenta-nab: Contextual Anomaly Detector OSE a b 406211800 6.112455 9490.8 10015.9 177.73 209.51 101.24 33.57 96.41 32.74 735.294 1821.2 5454.6 1391.1 500.9 1113.8 704.4 1914.65 2252.83 8068.36 9861.33 112513 87240 8464.38 10495.8 181.0022 63.3194 7.822 0.8299 3272684.62 2921694.2 2841542.11 247.77 274.60 278.90 97810.4 98163.47 96954.32 93560.28 179311.78 193855.44 185789.3 182530.28 42.31317 27.25888 439.9 402.3 5903.6 1931.2 900.0 3153.6 1787.6 1879.6 5680.7 953.8 3.33782 3.09967 0.620111 0.365467 1.25071 1.21056 5.16302 5.51978 4.1026 4.74584 0.830924 1.01001 2226.82 1121 2227.52 2.04864 7.66355 2.47403 1122.76 2227.01 1121.9 39.39 27.199787 169.69825 222.26157 2121.7484 300.001 80.728 119.412 104.47 152.925 9.848 5.654 61.734 17.331 25.456 406014500 6.373565 9531.3 10011.1 177.84 209.54 101.27 33.66 96.61 32.78 735.294 1715.3 5472.7 1398.4 506.6 1141.3 702.9 1861.93 2159.2 7607.31 9861.33 113370 86914 8199.86 10933.2 181.1977 63.2296 7.8537 0.8305 3250299.72 2902278.7 2829008.81 247.75 270.69 273.75 97914.05 98262.15 96692.89 93822.98 181582.13 189635.84 183386.87 183626.22 42.33833 27.24618 436.6 400.5 5716.0 1941.4 873.8 3128.9 1807.0 1843.8 5860.4 942.4 3.34819 3.09914 0.619937 0.367087 1.25253 1.20831 5.14851 5.32498 4.10323 4.71913 0.830898 1.00696 2226.86 1121.34 2229.02 2.04844 7.71613 2.47255 1122.58 2227.67 1123.68 39.15 29.932709 170.15311 223.41288 2118.7619 298.68 80.833 119.155 104.5 152.884 9.948 5.599 62.237 17.196 25.286 OpenBenchmarking.org
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 Xmlrig CPU mining performance. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org H/s, More Is Better Xmrig 6.18.1 Variant: Monero - Hash Count: 1M a b 2K 4K 6K 8K 10K 9490.8 9531.3 1. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc
OpenBenchmarking.org H/s, More Is Better Xmrig 6.18.1 Variant: Wownero - Hash Count: 1M b a 2K 4K 6K 8K 10K 10011.1 10015.9 1. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc
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.org images/sec, More Is Better TensorFlow 2.12 Device: CPU - Batch Size: 32 - Model: AlexNet a b 40 80 120 160 200 177.73 177.84
ASKAP ASKAP is a set of benchmarks from the Australian SKA Pathfinder. The principal ASKAP benchmarks are the Hogbom Clean Benchmark (tHogbomClean) and Convolutional Resamping Benchmark (tConvolve) as well as some previous ASKAP benchmarks being included as well for OpenCL and CUDA execution of tConvolve. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Iterations Per Second, More Is Better ASKAP 1.0 Test: Hogbom Clean OpenMP a b 160 320 480 640 800 735.29 735.29 1. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp
ASKAP ASKAP is a set of benchmarks from the Australian SKA Pathfinder. The principal ASKAP benchmarks are the Hogbom Clean Benchmark (tHogbomClean) and Convolutional Resamping Benchmark (tConvolve) as well as some previous ASKAP benchmarks being included as well for OpenCL and CUDA execution of tConvolve. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Million Grid Points Per Second, More Is Better ASKAP 1.0 Test: tConvolve MT - Gridding b a 400 800 1200 1600 2000 1861.93 1914.65 1. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp
OpenBenchmarking.org Million Grid Points Per Second, More Is Better ASKAP 1.0 Test: tConvolve MT - Degridding b a 500 1000 1500 2000 2500 2159.20 2252.83 1. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp
Test: tConvolve OpenCL
a: The test run did not produce a result.
b: The test run did not produce a result.
OpenBenchmarking.org Million Grid Points Per Second, More Is Better ASKAP 1.0 Test: tConvolve OpenMP - Gridding b a 2K 4K 6K 8K 10K 7607.31 8068.36 1. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp
OpenBenchmarking.org Million Grid Points Per Second, More Is Better ASKAP 1.0 Test: tConvolve OpenMP - Degridding a b 2K 4K 6K 8K 10K 9861.33 9861.33 1. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp
ASKAP ASKAP is a set of benchmarks from the Australian SKA Pathfinder. The principal ASKAP benchmarks are the Hogbom Clean Benchmark (tHogbomClean) and Convolutional Resamping Benchmark (tConvolve) as well as some previous ASKAP benchmarks being included as well for OpenCL and CUDA execution of tConvolve. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Mpix/sec, More Is Better ASKAP 1.0 Test: tConvolve MPI - Degridding b a 2K 4K 6K 8K 10K 8199.86 8464.38 1. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp
OpenBenchmarking.org Mpix/sec, More Is Better ASKAP 1.0 Test: tConvolve MPI - Gridding a b 2K 4K 6K 8K 10K 10495.8 10933.2 1. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp
Memcached Memcached is a high performance, distributed memory object caching system. This Memcached test profiles makes use of memtier_benchmark for excuting this CPU/memory-focused server benchmark. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Ops/sec, More Is Better Memcached 1.6.19 Set To Get Ratio: 1:5 b a 700K 1400K 2100K 2800K 3500K 3250299.72 3272684.62 1. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre
OpenBenchmarking.org Ops/sec, More Is Better Memcached 1.6.19 Set To Get Ratio: 1:10 b a 600K 1200K 1800K 2400K 3000K 2902278.7 2921694.2 1. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre
OpenBenchmarking.org Ops/sec, More Is Better Memcached 1.6.19 Set To Get Ratio: 1:100 b a 600K 1200K 1800K 2400K 3000K 2829008.81 2841542.11 1. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre
ClickHouse ClickHouse is an open-source, high performance OLAP data management system. This test profile uses ClickHouse's standard benchmark recommendations per https://clickhouse.com/docs/en/operations/performance-test/ / https://github.com/ClickHouse/ClickBench/tree/main/clickhouse with the 100 million rows web analytics dataset. The reported value is the query processing time using the geometric mean of all separate queries performed as an aggregate. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Queries Per Minute, Geo Mean, More Is Better ClickHouse 22.12.3.5 100M Rows Hits Dataset, First Run / Cold Cache b a 50 100 150 200 250 247.75 247.77 MIN: 9.76 / MAX: 7500 MIN: 9.7 / MAX: 7500
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.org Requests Per Second, More Is Better nginx 1.23.2 Connections: 100 a b 20K 40K 60K 80K 100K 97810.40 97914.05 1. (CC) gcc options: -lluajit-5.1 -lm -lssl -lcrypto -lpthread -ldl -std=c99 -O2
OpenBenchmarking.org Requests Per Second, More Is Better nginx 1.23.2 Connections: 200 a b 20K 40K 60K 80K 100K 98163.47 98262.15 1. (CC) gcc options: -lluajit-5.1 -lm -lssl -lcrypto -lpthread -ldl -std=c99 -O2
OpenBenchmarking.org Requests Per Second, More Is Better nginx 1.23.2 Connections: 500 b a 20K 40K 60K 80K 100K 96692.89 96954.32 1. (CC) gcc options: -lluajit-5.1 -lm -lssl -lcrypto -lpthread -ldl -std=c99 -O2
OpenBenchmarking.org Requests Per Second, More Is Better nginx 1.23.2 Connections: 1000 a b 20K 40K 60K 80K 100K 93560.28 93822.98 1. (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.org Requests Per Second, More Is Better Apache HTTP Server 2.4.56 Concurrent Requests: 100 a b 40K 80K 120K 160K 200K 179311.78 181582.13 1. (CC) gcc options: -lluajit-5.1 -lm -lssl -lcrypto -lpthread -ldl -std=c99 -O2
Test: In-Memory Database Shootout
a: The test run did not produce a result.
b: The test run did not produce a result.
OpenBenchmarking.org ms, Fewer Is Better Renaissance 0.14 Test: Genetic Algorithm Using Jenetics + Futures a b 200 400 600 800 1000 953.8 942.4 MIN: 940.04 / MAX: 966.17 MIN: 923.34 / MAX: 952.77
oneDNN This is a test of the Intel oneDNN as an Intel-optimized library for Deep Neural Networks and making use of its built-in benchdnn functionality. The result is the total perf time reported. Intel oneDNN was formerly known as DNNL (Deep Neural Network Library) and MKL-DNN before being rebranded as part of the Intel oneAPI toolkit. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.1 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU b a 0.7533 1.5066 2.2599 3.0132 3.7665 3.34819 3.33782 MIN: 3.14 MIN: 3.16 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.1 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU a b 0.6974 1.3948 2.0922 2.7896 3.487 3.09967 3.09914 MIN: 3.05 MIN: 3.05 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.1 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU a b 0.1395 0.279 0.4185 0.558 0.6975 0.620111 0.619937 MIN: 0.61 MIN: 0.61 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.1 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU b a 0.0826 0.1652 0.2478 0.3304 0.413 0.367087 0.365467 MIN: 0.35 MIN: 0.35 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.1 Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU b a 0.2818 0.5636 0.8454 1.1272 1.409 1.25253 1.25071 MIN: 1.23 MIN: 1.23 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.1 Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU a b 0.2724 0.5448 0.8172 1.0896 1.362 1.21056 1.20831 MIN: 1.17 MIN: 1.17 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.1 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU a b 1.1617 2.3234 3.4851 4.6468 5.8085 5.16302 5.14851 MIN: 5.06 MIN: 5.06 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.1 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU a b 1.242 2.484 3.726 4.968 6.21 5.51978 5.32498 MIN: 4.31 MIN: 4.32 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.1 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU b a 0.9232 1.8464 2.7696 3.6928 4.616 4.10323 4.10260 MIN: 4.05 MIN: 4.05 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.1 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU a b 1.0678 2.1356 3.2034 4.2712 5.339 4.74584 4.71913 MIN: 4.62 MIN: 4.64 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.1 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU a b 0.187 0.374 0.561 0.748 0.935 0.830924 0.830898 MIN: 0.82 MIN: 0.82 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.1 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU a b 0.2273 0.4546 0.6819 0.9092 1.1365 1.01001 1.00696 MIN: 0.99 MIN: 0.98 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.1 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU b a 500 1000 1500 2000 2500 2226.86 2226.82 MIN: 2222.67 MIN: 2223.91 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.1 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU b a 200 400 600 800 1000 1121.34 1121.00 MIN: 1117.68 MIN: 1117.71 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.1 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU b a 500 1000 1500 2000 2500 2229.02 2227.52 MIN: 2222.68 MIN: 2223.04 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.1 Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU a b 0.4609 0.9218 1.3827 1.8436 2.3045 2.04864 2.04844 MIN: 2.01 MIN: 2.01 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.1 Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU b a 2 4 6 8 10 7.71613 7.66355 MIN: 7.42 MIN: 7.39 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.1 Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU a b 0.5567 1.1134 1.6701 2.2268 2.7835 2.47403 2.47255 MIN: 2.42 MIN: 2.41 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.1 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU a b 200 400 600 800 1000 1122.76 1122.58 MIN: 1118.01 MIN: 1118.65 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.1 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU b a 500 1000 1500 2000 2500 2227.67 2227.01 MIN: 2223.36 MIN: 2223.59 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.1 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU b a 200 400 600 800 1000 1123.68 1121.90 MIN: 1118.61 MIN: 1117.18 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
CloverLeaf CloverLeaf is a Lagrangian-Eulerian hydrodynamics benchmark. This test profile currently makes use of CloverLeaf's OpenMP version and benchmarked with the clover_bm.in input file (Problem 5). Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Seconds, Fewer Is Better CloverLeaf Lagrangian-Eulerian Hydrodynamics a b 9 18 27 36 45 39.39 39.15 1. (F9X) gfortran options: -O3 -march=native -funroll-loops -fopenmp
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.org Seconds, Fewer Is Better OpenFOAM 10 Input: drivaerFastback, Small Mesh Size - Mesh Time b a 7 14 21 28 35 29.93 27.20 1. (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.org Seconds, Fewer Is Better OpenFOAM 10 Input: drivaerFastback, Small Mesh Size - Execution Time b a 40 80 120 160 200 170.15 169.70 1. (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.org Seconds, Fewer Is Better OpenFOAM 10 Input: drivaerFastback, Medium Mesh Size - Mesh Time b a 50 100 150 200 250 223.41 222.26 1. (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.org Seconds, Fewer Is Better OpenFOAM 10 Input: drivaerFastback, Medium Mesh Size - Execution Time a b 500 1000 1500 2000 2500 2121.75 2118.76 1. (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
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.org Seconds, Fewer Is Better Blender 3.5 Blend File: BMW27 - Compute: CPU-Only b a 20 40 60 80 100 104.50 104.47
Numenta Anomaly Benchmark Numenta Anomaly Benchmark (NAB) is a benchmark for evaluating algorithms for anomaly detection in streaming, real-time applications. It is comprised of over 50 labeled real-world and artificial time-series data files plus a novel scoring mechanism designed for real-time applications. This test profile currently measures the time to run various detectors. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Seconds, Fewer Is Better Numenta Anomaly Benchmark 1.1 Detector: KNN CAD a b 30 60 90 120 150 152.93 152.88
a Kernel Notes: Transparent Huge Pages: madviseCompiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --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-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-defaulted --enable-offload-targets=nvptx-none=/build/gcc-12-Pa930Z/gcc-12-12.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-12-Pa930Z/gcc-12-12.2.0/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-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 -vProcessor Notes: Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0xa601203Java Notes: OpenJDK Runtime Environment (build 17.0.6+10-Ubuntu-1ubuntu2)Python Notes: Python 3.11.2Security Notes: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Retpolines IBPB: conditional IBRS_FW STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected
Testing initiated at 5 April 2023 11:20 by user pts.
b Processor: AMD Ryzen 7 7800X3D 8-Core @ 4.20GHz (8 Cores / 16 Threads), Motherboard: ASUS ROG CROSSHAIR X670E HERO (9927 BIOS), Chipset: AMD Device 14d8, Memory: 32GB, Disk: Western Digital WD_BLACK SN850X 1000GB, Graphics: AMD Radeon RX 7900 XTX (2304/1249MHz), Audio: AMD Device ab30, Monitor: ASUS MG28U, Network: Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411
OS: Ubuntu 23.04, Kernel: 6.2.8-060208-generic (x86_64), Desktop: GNOME Shell 44.0, Display Server: X Server 1.21.1.7 + Wayland, OpenGL: 4.6 Mesa 23.1.0-devel (git-de8b14f 2023-03-24 lunar-oibaf-ppa) (LLVM 15.0.7 DRM 3.49), OpenCL: OpenCL 2.1 AMD-APP (3513.0), Compiler: GCC 12.2.0, File-System: ext4, Screen Resolution: 3840x2160
Kernel Notes: Transparent Huge Pages: madviseCompiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --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-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-defaulted --enable-offload-targets=nvptx-none=/build/gcc-12-Pa930Z/gcc-12-12.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-12-Pa930Z/gcc-12-12.2.0/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-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 -vProcessor Notes: Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0xa601203Java Notes: OpenJDK Runtime Environment (build 17.0.6+10-Ubuntu-1ubuntu2)Python Notes: Python 3.11.2Security Notes: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Retpolines IBPB: conditional IBRS_FW STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected
Testing initiated at 5 April 2023 13:36 by user pts.