Benchmarks for a future article..
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, Medium Mesh Size - Execution Time Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 500 1000 1500 2000 2500 1948.06 2161.56 1863.95 2126.10 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 Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 40 80 120 160 200 193.36 199.34 178.11 190.94 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
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 too. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.12-rc0 Device: CPU - Batch Size: 256 - Model: ResNet-50 Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 10 20 30 40 50 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 38.89 40.36 43.88 44.87
ONNX Runtime ONNX Runtime is developed by Microsoft and partners as a open-source, cross-platform, high performance machine learning inferencing and training accelerator. This test profile runs the ONNX Runtime with various models available from the ONNX Model Zoo. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.14 Model: yolov4 - Device: CPU - Executor: Standard Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 20 40 60 80 100 SE +/- 4.87, N = 15 SE +/- 4.06, N = 15 SE +/- 3.62, N = 15 SE +/- 3.19, N = 15 102.27 101.17 101.97 100.75 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
Result
OpenBenchmarking.org Inferences Per Second, More Is Better ONNX Runtime 1.14 Model: yolov4 - Device: CPU - Executor: Standard Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 3 6 9 12 15 SE +/- 0.45158, N = 15 SE +/- 0.40412, N = 15 SE +/- 0.38311, N = 15 SE +/- 0.36261, N = 15 10.07832 10.11033 9.99604 10.08625 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt Inference Time Cost (ms)
OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.14 Model: yolov4 - Device: CPU - Executor: Standard Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 20 40 60 80 100 SE +/- 4.87, N = 15 SE +/- 4.06, N = 15 SE +/- 3.62, N = 15 SE +/- 3.19, N = 15 102.27 101.17 101.97 100.75 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.14 Model: super-resolution-10 - Device: CPU - Executor: Standard Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 2 4 6 8 10 SE +/- 0.40239, N = 15 SE +/- 0.22770, N = 15 SE +/- 0.18428, N = 15 SE +/- 0.19969, N = 13 7.51702 5.85153 6.29145 6.14984 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
Result
OpenBenchmarking.org Inferences Per Second, More Is Better ONNX Runtime 1.14 Model: super-resolution-10 - Device: CPU - Executor: Standard Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 40 80 120 160 200 SE +/- 7.10, N = 15 SE +/- 5.34, N = 15 SE +/- 5.64, N = 15 SE +/- 6.30, N = 13 138.33 173.78 161.23 165.01 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt Inference Time Cost (ms)
OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.14 Model: super-resolution-10 - Device: CPU - Executor: Standard Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 2 4 6 8 10 SE +/- 0.40239, N = 15 SE +/- 0.22770, N = 15 SE +/- 0.18428, N = 15 SE +/- 0.19969, N = 13 7.51702 5.85153 6.29145 6.14984 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.14 Model: ArcFace ResNet-100 - Device: CPU - Executor: Standard Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 6 12 18 24 30 SE +/- 1.05, N = 12 SE +/- 0.86, N = 15 SE +/- 1.02, N = 15 SE +/- 0.66, N = 15 25.56 23.94 27.31 22.57 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
Result
OpenBenchmarking.org Inferences Per Second, More Is Better ONNX Runtime 1.14 Model: ArcFace ResNet-100 - Device: CPU - Executor: Standard Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 10 20 30 40 50 SE +/- 1.38, N = 12 SE +/- 1.23, N = 15 SE +/- 1.50, N = 15 SE +/- 1.19, N = 15 39.74 42.38 37.39 44.79 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt Inference Time Cost (ms)
OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.14 Model: ArcFace ResNet-100 - Device: CPU - Executor: Standard Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 6 12 18 24 30 SE +/- 1.05, N = 12 SE +/- 0.86, N = 15 SE +/- 1.02, N = 15 SE +/- 0.66, N = 15 25.56 23.94 27.31 22.57 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.14 Model: ResNet50 v1-12-int8 - Device: CPU - Executor: Standard Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 0.532 1.064 1.596 2.128 2.66 SE +/- 0.03587, N = 15 SE +/- 0.05616, N = 12 SE +/- 0.04809, N = 15 SE +/- 0.02087, N = 15 2.36463 2.33461 2.06799 2.06309 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
Result
OpenBenchmarking.org Inferences Per Second, More Is Better ONNX Runtime 1.14 Model: ResNet50 v1-12-int8 - Device: CPU - Executor: Standard Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 110 220 330 440 550 SE +/- 6.30, N = 15 SE +/- 10.29, N = 12 SE +/- 9.53, N = 15 SE +/- 4.65, N = 15 424.17 430.96 486.61 485.24 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt Inference Time Cost (ms)
OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.14 Model: ResNet50 v1-12-int8 - Device: CPU - Executor: Standard Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 0.532 1.064 1.596 2.128 2.66 SE +/- 0.03587, N = 15 SE +/- 0.05616, N = 12 SE +/- 0.04809, N = 15 SE +/- 0.02087, N = 15 2.36463 2.33461 2.06799 2.06309 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
LeelaChessZero LeelaChessZero (lc0 / lczero) is a chess engine automated vian neural networks. This test profile can be used for OpenCL, CUDA + cuDNN, and BLAS (CPU-based) benchmarking. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Nodes Per Second, More Is Better LeelaChessZero 0.28 Backend: BLAS Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 400 800 1200 1600 2000 SE +/- 23.20, N = 4 SE +/- 14.80, N = 3 SE +/- 13.05, N = 3 SE +/- 14.71, N = 3 1882 1879 1945 1915 1. (CXX) g++ options: -flto -pthread
OpenBenchmarking.org Nodes Per Second, More Is Better LeelaChessZero 0.28 Backend: Eigen Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 400 800 1200 1600 2000 SE +/- 19.01, N = 4 SE +/- 19.78, N = 3 SE +/- 13.42, N = 3 SE +/- 4.00, N = 3 1767 1772 1787 1773 1. (CXX) g++ options: -flto -pthread
ONNX Runtime ONNX Runtime is developed by Microsoft and partners as a open-source, cross-platform, high performance machine learning inferencing and training accelerator. This test profile runs the ONNX Runtime with various models available from the ONNX Model Zoo. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.14 Model: CaffeNet 12-int8 - Device: CPU - Executor: Standard Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 0.2282 0.4564 0.6846 0.9128 1.141 SE +/- 0.005430, N = 3 SE +/- 0.029891, N = 15 SE +/- 0.033238, N = 15 SE +/- 0.007823, N = 6 0.865505 1.014088 0.938149 0.816994 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
Result
OpenBenchmarking.org Inferences Per Second, More Is Better ONNX Runtime 1.14 Model: CaffeNet 12-int8 - Device: CPU - Executor: Standard Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 300 600 900 1200 1500 SE +/- 7.21, N = 3 SE +/- 31.87, N = 15 SE +/- 39.20, N = 15 SE +/- 11.41, N = 6 1155.14 998.86 1084.91 1224.00 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt Inference Time Cost (ms)
OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.14 Model: CaffeNet 12-int8 - Device: CPU - Executor: Standard Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 0.2282 0.4564 0.6846 0.9128 1.141 SE +/- 0.005430, N = 3 SE +/- 0.029891, N = 15 SE +/- 0.033238, N = 15 SE +/- 0.007823, N = 6 0.865505 1.014088 0.938149 0.816994 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.14 Model: Faster R-CNN R-50-FPN-int8 - Device: CPU - Executor: Standard Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 4 8 12 16 20 SE +/- 0.08, N = 3 SE +/- 0.55, N = 15 SE +/- 0.48, N = 15 SE +/- 0.02, N = 3 14.51 16.88 14.45 14.27 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
Result
OpenBenchmarking.org Inferences Per Second, More Is Better ONNX Runtime 1.14 Model: Faster R-CNN R-50-FPN-int8 - Device: CPU - Executor: Standard Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 16 32 48 64 80 SE +/- 0.38, N = 3 SE +/- 1.94, N = 15 SE +/- 2.04, N = 15 SE +/- 0.09, N = 3 68.92 60.11 70.16 70.09 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt Inference Time Cost (ms)
OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.14 Model: Faster R-CNN R-50-FPN-int8 - Device: CPU - Executor: Standard Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 4 8 12 16 20 SE +/- 0.08, N = 3 SE +/- 0.55, N = 15 SE +/- 0.48, N = 15 SE +/- 0.02, N = 3 14.51 16.88 14.45 14.27 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
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 too. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.12-rc0 Device: CPU - Batch Size: 256 - Model: GoogLeNet Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 30 60 90 120 150 SE +/- 0.04, N = 3 SE +/- 0.02, N = 3 SE +/- 0.03, N = 3 SE +/- 0.03, N = 3 118.96 123.87 137.77 140.76
Zstd Compression This test measures the time needed to compress/decompress a sample file (silesia.tar) using Zstd (Zstandard) compression with options for different compression levels / settings. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org MB/s, More Is Better Zstd Compression 1.5.4 Compression Level: 19 - Decompression Speed Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 500 1000 1500 2000 2500 SE +/- 14.47, N = 15 SE +/- 31.89, N = 3 SE +/- 25.89, N = 15 SE +/- 4.22, N = 3 2082.1 2101.8 2030.5 2104.4 1. (CC) gcc options: -O3 -pthread -lz -llzma -llz4
OpenBenchmarking.org MB/s, More Is Better Zstd Compression 1.5.4 Compression Level: 19 - Compression Speed Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 6 12 18 24 30 SE +/- 0.31, N = 15 SE +/- 0.03, N = 3 SE +/- 0.37, N = 15 SE +/- 0.09, N = 3 25.2 23.4 25.2 23.3 1. (CC) gcc options: -O3 -pthread -lz -llzma -llz4
OpenBenchmarking.org MB/s, More Is Better Zstd Compression 1.5.4 Compression Level: 19, Long Mode - Decompression Speed Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 400 800 1200 1600 2000 SE +/- 29.67, N = 15 SE +/- 8.37, N = 15 SE +/- 16.22, N = 3 SE +/- 6.34, N = 3 1876.3 1997.4 1872.4 1990.0 1. (CC) gcc options: -O3 -pthread -lz -llzma -llz4
OpenBenchmarking.org MB/s, More Is Better Zstd Compression 1.5.4 Compression Level: 19, Long Mode - Compression Speed Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 4 8 12 16 20 SE +/- 0.15, N = 15 SE +/- 0.12, N = 15 SE +/- 0.03, N = 3 SE +/- 0.03, N = 3 14.3 13.0 15.0 12.5 1. (CC) gcc options: -O3 -pthread -lz -llzma -llz4
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, Third Run Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 70 140 210 280 350 SE +/- 1.13, N = 3 SE +/- 3.74, N = 3 SE +/- 3.76, N = 3 SE +/- 0.25, N = 3 308.81 290.14 321.76 276.94 MIN: 14.79 / MAX: 12000 MIN: 16.06 / MAX: 12000 MIN: 15.82 / MAX: 10000 MIN: 15.4 / MAX: 10000
OpenBenchmarking.org Queries Per Minute, Geo Mean, More Is Better ClickHouse 22.12.3.5 100M Rows Hits Dataset, Second Run Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 70 140 210 280 350 SE +/- 0.93, N = 3 SE +/- 0.26, N = 3 SE +/- 2.16, N = 3 SE +/- 3.10, N = 3 303.48 285.41 316.84 275.45 MIN: 14.85 / MAX: 10000 MIN: 16.08 / MAX: 12000 MIN: 16.12 / MAX: 10000 MIN: 16.28 / MAX: 12000
OpenBenchmarking.org Queries Per Minute, Geo Mean, More Is Better ClickHouse 22.12.3.5 100M Rows Hits Dataset, First Run / Cold Cache Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 60 120 180 240 300 SE +/- 1.41, N = 3 SE +/- 1.44, N = 3 SE +/- 1.59, N = 3 SE +/- 0.81, N = 3 269.00 258.64 279.87 250.50 MIN: 14.44 / MAX: 8571.43 MIN: 15.82 / MAX: 10000 MIN: 13.15 / MAX: 7500 MIN: 12.61 / MAX: 10000
ONNX Runtime ONNX Runtime is developed by Microsoft and partners as a open-source, cross-platform, high performance machine learning inferencing and training accelerator. This test profile runs the ONNX Runtime with various models available from the ONNX Model Zoo. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.14 Model: GPT-2 - Device: CPU - Executor: Standard Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 1.327 2.654 3.981 5.308 6.635 SE +/- 0.03513, N = 3 SE +/- 0.06489, N = 15 SE +/- 0.07238, N = 3 SE +/- 0.01353, N = 3 5.10690 5.79435 5.39416 5.89782 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
Result
OpenBenchmarking.org Inferences Per Second, More Is Better ONNX Runtime 1.14 Model: GPT-2 - Device: CPU - Executor: Standard Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 40 80 120 160 200 SE +/- 1.34, N = 3 SE +/- 1.80, N = 15 SE +/- 2.46, N = 3 SE +/- 0.39, N = 3 195.76 172.81 185.38 169.50 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt Inference Time Cost (ms)
OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.14 Model: GPT-2 - Device: CPU - Executor: Standard Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 1.327 2.654 3.981 5.308 6.635 SE +/- 0.03513, N = 3 SE +/- 0.06489, N = 15 SE +/- 0.07238, N = 3 SE +/- 0.01353, N = 3 5.10690 5.79435 5.39416 5.89782 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
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 too. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.12-rc0 Device: CPU - Batch Size: 64 - Model: ResNet-50 Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 10 20 30 40 50 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.04, N = 3 SE +/- 0.02, N = 3 39.06 40.20 44.20 44.58
KTX-Software toktx This is a benchmark of The Khronos Group's KTX-Software library and tools. KTX-Software provides "toktx" for converting/creating in the KTX container format for image textures. This benchmark times how long it takes to convert to KTX 2.0 format with various settings using a reference PNG sample input. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Seconds, Fewer Is Better KTX-Software toktx 4.0 Settings: UASTC 4 + Zstd Compression 19 Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 40 80 120 160 200 SE +/- 0.05, N = 3 SE +/- 0.13, N = 3 SE +/- 0.03, N = 3 SE +/- 0.21, N = 3 169.17 157.11 126.30 119.50
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.org Seconds, Fewer Is Better GPAW 22.1 Input: Carbon Nanotube Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 30 60 90 120 150 SE +/- 0.15, N = 3 SE +/- 0.21, N = 3 SE +/- 0.16, N = 3 SE +/- 0.12, N = 3 143.15 150.87 126.90 138.01 1. (CC) gcc options: -shared -fwrapv -O2 -lxc -lblas -lmpi
Zstd Compression This test measures the time needed to compress/decompress a sample file (silesia.tar) using Zstd (Zstandard) compression with options for different compression levels / settings. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org MB/s, More Is Better Zstd Compression 1.5.4 Compression Level: 8 - Decompression Speed Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 500 1000 1500 2000 2500 SE +/- 4.93, N = 3 SE +/- 6.76, N = 3 SE +/- 15.85, N = 15 SE +/- 7.71, N = 3 2352.9 2393.0 2391.6 2379.1 1. (CC) gcc options: -O3 -pthread -lz -llzma -llz4
OpenBenchmarking.org MB/s, More Is Better Zstd Compression 1.5.4 Compression Level: 8 - Compression Speed Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 200 400 600 800 1000 SE +/- 7.21, N = 3 SE +/- 1.87, N = 3 SE +/- 9.05, N = 15 SE +/- 3.61, N = 3 1026.5 857.4 1053.7 837.4 1. (CC) gcc options: -O3 -pthread -lz -llzma -llz4
ONNX Runtime ONNX Runtime is developed by Microsoft and partners as a open-source, cross-platform, high performance machine learning inferencing and training accelerator. This test profile runs the ONNX Runtime with various models available from the ONNX Model Zoo. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.14 Model: fcn-resnet101-11 - Device: CPU - Executor: Parallel Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 140 280 420 560 700 SE +/- 7.18, N = 5 SE +/- 3.35, N = 3 SE +/- 4.59, N = 3 SE +/- 5.36, N = 3 664.59 633.10 522.69 509.33 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
Result
OpenBenchmarking.org Inferences Per Second, More Is Better ONNX Runtime 1.14 Model: fcn-resnet101-11 - Device: CPU - Executor: Parallel Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 0.4419 0.8838 1.3257 1.7676 2.2095 SE +/- 0.01582, N = 5 SE +/- 0.00841, N = 3 SE +/- 0.01691, N = 3 SE +/- 0.02061, N = 3 1.50536 1.57963 1.91347 1.96381 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt Inference Time Cost (ms)
OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.14 Model: fcn-resnet101-11 - Device: CPU - Executor: Parallel Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 140 280 420 560 700 SE +/- 7.18, N = 5 SE +/- 3.35, N = 3 SE +/- 4.59, N = 3 SE +/- 5.36, N = 3 664.59 633.10 522.69 509.33 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.14 Model: yolov4 - Device: CPU - Executor: Parallel Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 30 60 90 120 150 SE +/- 0.38, N = 3 SE +/- 0.42, N = 3 SE +/- 0.20, N = 3 SE +/- 1.07, N = 5 125.47 116.27 105.93 100.49 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
Result
OpenBenchmarking.org Inferences Per Second, More Is Better ONNX Runtime 1.14 Model: yolov4 - Device: CPU - Executor: Parallel Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 3 6 9 12 15 SE +/- 0.02410, N = 3 SE +/- 0.03144, N = 3 SE +/- 0.01779, N = 3 SE +/- 0.10261, N = 5 7.97025 8.60115 9.44018 9.95491 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt Inference Time Cost (ms)
OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.14 Model: yolov4 - Device: CPU - Executor: Parallel Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 30 60 90 120 150 SE +/- 0.38, N = 3 SE +/- 0.42, N = 3 SE +/- 0.20, N = 3 SE +/- 1.07, N = 5 125.47 116.27 105.93 100.49 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.14 Model: CaffeNet 12-int8 - Device: CPU - Executor: Parallel Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 0.2801 0.5602 0.8403 1.1204 1.4005 SE +/- 0.01782, N = 3 SE +/- 0.01294, N = 5 SE +/- 0.00846, N = 3 SE +/- 0.00816, N = 3 1.24481 1.20427 1.05436 1.08333 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
Result
OpenBenchmarking.org Inferences Per Second, More Is Better ONNX Runtime 1.14 Model: CaffeNet 12-int8 - Device: CPU - Executor: Parallel Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 200 400 600 800 1000 SE +/- 11.49, N = 3 SE +/- 9.08, N = 5 SE +/- 7.64, N = 3 SE +/- 6.96, N = 3 802.98 830.07 947.64 922.34 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt Inference Time Cost (ms)
OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.14 Model: CaffeNet 12-int8 - Device: CPU - Executor: Parallel Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 0.2801 0.5602 0.8403 1.1204 1.4005 SE +/- 0.01782, N = 3 SE +/- 0.01294, N = 5 SE +/- 0.00846, N = 3 SE +/- 0.00816, N = 3 1.24481 1.20427 1.05436 1.08333 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.14 Model: bertsquad-12 - Device: CPU - Executor: Parallel Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 20 40 60 80 100 SE +/- 0.50, N = 3 SE +/- 0.81, N = 3 SE +/- 0.70, N = 4 SE +/- 0.67, N = 3 77.57 72.14 67.55 61.61 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
Result
OpenBenchmarking.org Inferences Per Second, More Is Better ONNX Runtime 1.14 Model: bertsquad-12 - Device: CPU - Executor: Parallel Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 4 8 12 16 20 SE +/- 0.08, N = 3 SE +/- 0.15, N = 3 SE +/- 0.15, N = 4 SE +/- 0.18, N = 3 12.89 13.87 14.81 16.23 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt Inference Time Cost (ms)
OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.14 Model: bertsquad-12 - Device: CPU - Executor: Parallel Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 20 40 60 80 100 SE +/- 0.50, N = 3 SE +/- 0.81, N = 3 SE +/- 0.70, N = 4 SE +/- 0.67, N = 3 77.57 72.14 67.55 61.61 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
NCNN NCNN is a high performance neural network inference framework optimized for mobile and other platforms developed by Tencent. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org ms, Fewer Is Better NCNN 20220729 Target: CPU - Model: FastestDet Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 1.053 2.106 3.159 4.212 5.265 SE +/- 0.07, N = 3 SE +/- 0.19, N = 3 SE +/- 0.02, N = 3 SE +/- 0.03, N = 7 4.36 4.22 4.68 4.46 MIN: 4.18 / MAX: 4.8 MIN: 3.94 / MAX: 4.84 MIN: 4.55 / MAX: 6.08 MIN: 4.27 / MAX: 5.74 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20220729 Target: CPU - Model: vision_transformer Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 20 40 60 80 100 SE +/- 0.54, N = 3 SE +/- 0.26, N = 3 SE +/- 1.49, N = 3 SE +/- 0.63, N = 7 92.65 84.57 82.03 75.76 MIN: 91.31 / MAX: 100.98 MIN: 83.77 / MAX: 112.37 MIN: 80.21 / MAX: 86.13 MIN: 74.12 / MAX: 90.63 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20220729 Target: CPU - Model: regnety_400m Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 3 6 9 12 15 SE +/- 0.02, N = 3 SE +/- 0.12, N = 3 SE +/- 0.02, N = 3 SE +/- 0.09, N = 7 11.06 10.05 11.96 11.48 MIN: 10.51 / MAX: 18 MIN: 9.63 / MAX: 43.59 MIN: 11.54 / MAX: 15.93 MIN: 10.72 / MAX: 48.4 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20220729 Target: CPU - Model: squeezenet_ssd Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 3 6 9 12 15 SE +/- 0.26, N = 3 SE +/- 0.14, N = 3 SE +/- 0.06, N = 3 SE +/- 0.08, N = 7 11.57 11.78 11.72 12.14 MIN: 10.88 / MAX: 89.31 MIN: 11.23 / MAX: 63.22 MIN: 11.48 / MAX: 18.6 MIN: 11.7 / MAX: 20.56 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20220729 Target: CPU - Model: yolov4-tiny Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 4 8 12 16 20 SE +/- 0.47, N = 3 SE +/- 0.14, N = 3 SE +/- 0.06, N = 3 SE +/- 0.06, N = 7 14.73 14.24 14.28 14.21 MIN: 13.78 / MAX: 20.88 MIN: 13.88 / MAX: 55.6 MIN: 13.99 / MAX: 17.85 MIN: 13.76 / MAX: 41.48 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20220729 Target: CPU - Model: resnet50 Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 3 6 9 12 15 SE +/- 0.18, N = 3 SE +/- 0.19, N = 3 SE +/- 0.27, N = 3 SE +/- 0.12, N = 7 12.47 12.38 11.86 12.17 MIN: 11.8 / MAX: 20.06 MIN: 11.55 / MAX: 20.74 MIN: 11.44 / MAX: 44.27 MIN: 11.51 / MAX: 20.61 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20220729 Target: CPU - Model: alexnet Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 1.1205 2.241 3.3615 4.482 5.6025 SE +/- 0.05, N = 3 SE +/- 0.06, N = 3 SE +/- 0.03, N = 3 SE +/- 0.08, N = 7 4.60 4.98 4.28 4.86 MIN: 4.43 / MAX: 11.35 MIN: 4.73 / MAX: 10.59 MIN: 4.13 / MAX: 10.29 MIN: 4.63 / MAX: 9.89 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20220729 Target: CPU - Model: resnet18 Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 2 4 6 8 10 SE +/- 0.31, N = 3 SE +/- 0.25, N = 3 SE +/- 0.01, N = 3 SE +/- 0.10, N = 7 7.08 7.77 6.60 7.46 MIN: 6.25 / MAX: 13.9 MIN: 7.02 / MAX: 14.55 MIN: 6.42 / MAX: 12.76 MIN: 7.15 / MAX: 14.27 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20220729 Target: CPU - Model: vgg16 Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 6 12 18 24 30 SE +/- 0.43, N = 3 SE +/- 0.35, N = 3 SE +/- 0.45, N = 3 SE +/- 0.40, N = 7 25.94 25.74 24.34 24.61 MIN: 24.38 / MAX: 80.6 MIN: 24.62 / MAX: 110.19 MIN: 23.49 / MAX: 49.31 MIN: 23.44 / MAX: 36.14 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20220729 Target: CPU - Model: googlenet Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 3 6 9 12 15 SE +/- 0.35, N = 3 SE +/- 0.23, N = 3 SE +/- 0.00, N = 3 SE +/- 0.15, N = 7 9.03 8.82 8.52 8.58 MIN: 7.88 / MAX: 43.33 MIN: 7.98 / MAX: 72.14 MIN: 8.28 / MAX: 14.26 MIN: 8.16 / MAX: 15.24 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20220729 Target: CPU - Model: blazeface Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 0.3668 0.7336 1.1004 1.4672 1.834 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 SE +/- 0.01, N = 7 1.49 1.38 1.63 1.54 MIN: 1.4 / MAX: 8.23 MIN: 1.31 / MAX: 7.52 MIN: 1.57 / MAX: 4.47 MIN: 1.46 / MAX: 8.06 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20220729 Target: CPU - Model: efficientnet-b0 Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 1.035 2.07 3.105 4.14 5.175 SE +/- 0.08, N = 3 SE +/- 0.09, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 7 4.57 4.31 4.60 4.40 MIN: 4.29 / MAX: 38.08 MIN: 4.09 / MAX: 69.92 MIN: 4.49 / MAX: 8.48 MIN: 4.27 / MAX: 12.06 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20220729 Target: CPU - Model: mnasnet Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 0.765 1.53 2.295 3.06 3.825 SE +/- 0.02, N = 3 SE +/- 0.08, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 7 3.25 3.17 3.40 3.23 MIN: 3.13 / MAX: 9.66 MIN: 3 / MAX: 45.73 MIN: 3.28 / MAX: 7.36 MIN: 3.12 / MAX: 10.32 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20220729 Target: CPU - Model: shufflenet-v2 Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 0.8685 1.737 2.6055 3.474 4.3425 SE +/- 0.02, N = 3 SE +/- 0.03, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 7 3.73 3.46 3.86 3.62 MIN: 3.55 / MAX: 9.54 MIN: 3.36 / MAX: 9.94 MIN: 3.71 / MAX: 9.56 MIN: 3.44 / MAX: 10.54 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20220729 Target: CPU-v3-v3 - Model: mobilenet-v3 Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 0.7448 1.4896 2.2344 2.9792 3.724 SE +/- 0.01, N = 3 SE +/- 0.07, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 7 3.14 3.13 3.31 3.15 MIN: 3.07 / MAX: 7.15 MIN: 2.81 / MAX: 65.6 MIN: 3.21 / MAX: 7.38 MIN: 3.05 / MAX: 9.87 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20220729 Target: CPU-v2-v2 - Model: mobilenet-v2 Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 0.846 1.692 2.538 3.384 4.23 SE +/- 0.01, N = 3 SE +/- 0.04, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 7 3.57 3.50 3.76 3.62 MIN: 3.49 / MAX: 7.6 MIN: 3.31 / MAX: 10.67 MIN: 3.66 / MAX: 7.74 MIN: 3.49 / MAX: 11.58 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20220729 Target: CPU - Model: mobilenet Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 3 6 9 12 15 SE +/- 0.06, N = 3 SE +/- 0.10, N = 3 SE +/- 0.02, N = 3 SE +/- 0.08, N = 7 9.33 8.84 8.87 8.70 MIN: 9.06 / MAX: 16.18 MIN: 8.3 / MAX: 71.01 MIN: 8.73 / MAX: 12.08 MIN: 8.36 / MAX: 15.03 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread
ONNX Runtime ONNX Runtime is developed by Microsoft and partners as a open-source, cross-platform, high performance machine learning inferencing and training accelerator. This test profile runs the ONNX Runtime with various models available from the ONNX Model Zoo. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.14 Model: fcn-resnet101-11 - Device: CPU - Executor: Standard Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 120 240 360 480 600 SE +/- 0.19, N = 3 SE +/- 3.02, N = 3 SE +/- 4.02, N = 3 SE +/- 1.13, N = 3 347.97 571.29 282.64 448.76 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
Result
OpenBenchmarking.org Inferences Per Second, More Is Better ONNX Runtime 1.14 Model: fcn-resnet101-11 - Device: CPU - Executor: Standard Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 0.7964 1.5928 2.3892 3.1856 3.982 SE +/- 0.00156, N = 3 SE +/- 0.00921, N = 3 SE +/- 0.04984, N = 3 SE +/- 0.00558, N = 3 2.87377 1.75053 3.53941 2.22836 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt Inference Time Cost (ms)
OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.14 Model: fcn-resnet101-11 - Device: CPU - Executor: Standard Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 120 240 360 480 600 SE +/- 0.19, N = 3 SE +/- 3.02, N = 3 SE +/- 4.02, N = 3 SE +/- 1.13, N = 3 347.97 571.29 282.64 448.76 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.14 Model: GPT-2 - Device: CPU - Executor: Parallel Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 2 4 6 8 10 SE +/- 0.02269, N = 3 SE +/- 0.07342, N = 3 SE +/- 0.02467, N = 3 SE +/- 0.00930, N = 3 6.35362 6.83177 6.07438 6.82261 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
Result
OpenBenchmarking.org Inferences Per Second, More Is Better ONNX Runtime 1.14 Model: GPT-2 - Device: CPU - Executor: Parallel Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 40 80 120 160 200 SE +/- 0.56, N = 3 SE +/- 1.56, N = 3 SE +/- 0.66, N = 3 SE +/- 0.20, N = 3 157.29 146.34 164.53 146.50 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt Inference Time Cost (ms)
OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.14 Model: GPT-2 - Device: CPU - Executor: Parallel Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 2 4 6 8 10 SE +/- 0.02269, N = 3 SE +/- 0.07342, N = 3 SE +/- 0.02467, N = 3 SE +/- 0.00930, N = 3 6.35362 6.83177 6.07438 6.82261 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.14 Model: bertsquad-12 - Device: CPU - Executor: Standard Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 12 24 36 48 60 SE +/- 0.34, N = 3 SE +/- 0.07, N = 3 SE +/- 0.47, N = 3 SE +/- 0.16, N = 3 53.14 50.69 49.54 47.00 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
Result
OpenBenchmarking.org Inferences Per Second, More Is Better ONNX Runtime 1.14 Model: bertsquad-12 - Device: CPU - Executor: Standard Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 5 10 15 20 25 SE +/- 0.12, N = 3 SE +/- 0.03, N = 3 SE +/- 0.19, N = 3 SE +/- 0.07, N = 3 18.82 19.73 20.19 21.28 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt Inference Time Cost (ms)
OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.14 Model: bertsquad-12 - Device: CPU - Executor: Standard Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 12 24 36 48 60 SE +/- 0.34, N = 3 SE +/- 0.07, N = 3 SE +/- 0.47, N = 3 SE +/- 0.16, N = 3 53.14 50.69 49.54 47.00 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.14 Model: ArcFace ResNet-100 - Device: CPU - Executor: Parallel Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 8 16 24 32 40 SE +/- 0.13, N = 3 SE +/- 0.21, N = 3 SE +/- 0.19, N = 3 SE +/- 0.08, N = 3 35.14 31.99 29.77 27.30 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
Result
OpenBenchmarking.org Inferences Per Second, More Is Better ONNX Runtime 1.14 Model: ArcFace ResNet-100 - Device: CPU - Executor: Parallel Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 8 16 24 32 40 SE +/- 0.11, N = 3 SE +/- 0.21, N = 3 SE +/- 0.21, N = 3 SE +/- 0.11, N = 3 28.46 31.26 33.59 36.63 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt Inference Time Cost (ms)
OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.14 Model: ArcFace ResNet-100 - Device: CPU - Executor: Parallel Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 8 16 24 32 40 SE +/- 0.13, N = 3 SE +/- 0.21, N = 3 SE +/- 0.19, N = 3 SE +/- 0.08, N = 3 35.14 31.99 29.77 27.30 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.14 Model: Faster R-CNN R-50-FPN-int8 - Device: CPU - Executor: Parallel Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 5 10 15 20 25 SE +/- 0.04, N = 3 SE +/- 0.02, N = 3 SE +/- 0.23, N = 3 SE +/- 0.16, N = 3 20.72 20.20 20.14 19.33 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
Result
OpenBenchmarking.org Inferences Per Second, More Is Better ONNX Runtime 1.14 Model: Faster R-CNN R-50-FPN-int8 - Device: CPU - Executor: Parallel Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 12 24 36 48 60 SE +/- 0.10, N = 3 SE +/- 0.05, N = 3 SE +/- 0.55, N = 3 SE +/- 0.42, N = 3 48.26 49.50 49.66 51.74 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt Inference Time Cost (ms)
OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.14 Model: Faster R-CNN R-50-FPN-int8 - Device: CPU - Executor: Parallel Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 5 10 15 20 25 SE +/- 0.04, N = 3 SE +/- 0.02, N = 3 SE +/- 0.23, N = 3 SE +/- 0.16, N = 3 20.72 20.20 20.14 19.33 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.14 Model: ResNet50 v1-12-int8 - Device: CPU - Executor: Parallel Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 0.6701 1.3402 2.0103 2.6804 3.3505 SE +/- 0.01374, N = 3 SE +/- 0.01009, N = 3 SE +/- 0.01408, N = 3 SE +/- 0.00583, N = 3 2.97822 2.67309 2.59883 2.43239 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
Result
OpenBenchmarking.org Inferences Per Second, More Is Better ONNX Runtime 1.14 Model: ResNet50 v1-12-int8 - Device: CPU - Executor: Parallel Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 90 180 270 360 450 SE +/- 1.54, N = 3 SE +/- 1.41, N = 3 SE +/- 2.07, N = 3 SE +/- 0.99, N = 3 335.71 374.01 384.72 411.01 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt Inference Time Cost (ms)
OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.14 Model: ResNet50 v1-12-int8 - Device: CPU - Executor: Parallel Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 0.6701 1.3402 2.0103 2.6804 3.3505 SE +/- 0.01374, N = 3 SE +/- 0.01009, N = 3 SE +/- 0.01408, N = 3 SE +/- 0.00583, N = 3 2.97822 2.67309 2.59883 2.43239 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.14 Model: super-resolution-10 - Device: CPU - Executor: Parallel Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 3 6 9 12 15 SE +/- 0.00988, N = 3 SE +/- 0.01908, N = 3 SE +/- 0.01572, N = 3 SE +/- 0.02538, N = 3 10.09470 8.89505 8.02960 7.17184 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
Result
OpenBenchmarking.org Inferences Per Second, More Is Better ONNX Runtime 1.14 Model: super-resolution-10 - Device: CPU - Executor: Parallel Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 30 60 90 120 150 SE +/- 0.10, N = 3 SE +/- 0.24, N = 3 SE +/- 0.24, N = 3 SE +/- 0.49, N = 3 99.05 112.42 124.53 139.43 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt Inference Time Cost (ms)
OpenBenchmarking.org Inference Time Cost (ms), Fewer Is Better ONNX Runtime 1.14 Model: super-resolution-10 - Device: CPU - Executor: Parallel Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 3 6 9 12 15 SE +/- 0.00988, N = 3 SE +/- 0.01908, N = 3 SE +/- 0.01572, N = 3 SE +/- 0.02538, N = 3 10.09470 8.89505 8.02960 7.17184 1. (CXX) g++ options: -ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto=auto -fno-fat-lto-objects -ldl -lrt
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 too. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.12-rc0 Device: CPU - Batch Size: 32 - Model: ResNet-50 Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 10 20 30 40 50 SE +/- 0.06, N = 3 SE +/- 0.01, N = 3 SE +/- 0.06, N = 3 SE +/- 0.03, N = 3 39.01 40.00 44.27 44.39
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 - Degridding Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 600 1200 1800 2400 3000 SE +/- 24.29, N = 3 SE +/- 39.07, N = 3 SE +/- 7.84, N = 3 SE +/- 6.59, N = 3 2906.78 2755.49 2995.19 2833.49 1. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp
OpenBenchmarking.org Million Grid Points Per Second, More Is Better ASKAP 1.0 Test: tConvolve MT - Gridding Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 500 1000 1500 2000 2500 SE +/- 11.10, N = 3 SE +/- 11.79, N = 3 SE +/- 8.06, N = 3 SE +/- 8.23, N = 3 2100.99 2002.69 2293.31 2173.95 1. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp
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 3.0 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 300 600 900 1200 1500 SE +/- 1.50, N = 3 SE +/- 1.79, N = 3 SE +/- 2.36, N = 3 SE +/- 1.31, N = 3 1560.86 1434.06 1209.12 1130.44 MIN: 1554.07 MIN: 1423.92 MIN: 1195.27 MIN: 1121.32 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.0 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 200 400 600 800 1000 SE +/- 2.26, N = 3 SE +/- 1.56, N = 3 SE +/- 1.70, N = 3 SE +/- 4.41, N = 3 803.71 731.38 623.39 578.91 MIN: 796.39 MIN: 721.81 MIN: 614.18 MIN: 566.67 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread
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 too. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.12-rc0 Device: CPU - Batch Size: 256 - Model: AlexNet Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 100 200 300 400 500 SE +/- 0.33, N = 3 SE +/- 0.11, N = 3 SE +/- 0.24, N = 3 SE +/- 0.19, N = 3 328.37 353.60 418.97 439.54
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.org Ns Per Day, More Is Better GROMACS 2023 Implementation: MPI CPU - Input: water_GMX50_bare Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 0.6064 1.2128 1.8192 2.4256 3.032 SE +/- 0.002, N = 3 SE +/- 0.004, N = 3 SE +/- 0.002, N = 3 SE +/- 0.004, N = 3 2.278 2.270 2.695 2.607 1. (CXX) g++ options: -O3
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.org Seconds, Fewer Is Better Xcompact3d Incompact3d 2021-03-11 Input: input.i3d 193 Cells Per Direction Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 15 30 45 60 75 SE +/- 0.70, N = 4 SE +/- 0.82, N = 3 SE +/- 0.66, N = 4 SE +/- 0.31, N = 3 61.96 68.22 58.77 66.21 1. (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
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 Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 3K 6K 9K 12K 15K SE +/- 76.91, N = 3 SE +/- 111.27, N = 3 SE +/- 69.71, N = 3 SE +/- 39.19, N = 3 13564.7 13863.0 15627.4 13188.9 1. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc
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.org ms, Fewer Is Better OpenVINO 2022.3 Model: Person Detection FP16 - Device: CPU Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 200 400 600 800 1000 SE +/- 3.14, N = 3 SE +/- 7.16, N = 3 SE +/- 2.36, N = 3 SE +/- 1.82, N = 3 1065.82 1000.88 1085.08 1040.72 MIN: 618.47 / MAX: 1180.09 MIN: 603.97 / MAX: 1146.51 MIN: 997.16 / MAX: 1282.69 MIN: 623.58 / MAX: 1238.55 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenBenchmarking.org FPS, More Is Better OpenVINO 2022.3 Model: Person Detection FP16 - Device: CPU Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 2 4 6 8 10 SE +/- 0.02, N = 3 SE +/- 0.05, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 5.60 5.97 7.32 7.65 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2022.3 Model: Person Detection FP32 - Device: CPU Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 200 400 600 800 1000 SE +/- 2.18, N = 3 SE +/- 3.50, N = 3 SE +/- 6.09, N = 3 SE +/- 8.14, N = 3 1064.33 1012.48 1094.43 1057.42 MIN: 940.91 / MAX: 1184.64 MIN: 584.86 / MAX: 1150.29 MIN: 672.11 / MAX: 1267.85 MIN: 582.42 / MAX: 1238.03 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenBenchmarking.org FPS, More Is Better OpenVINO 2022.3 Model: Person Detection FP32 - Device: CPU Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 2 4 6 8 10 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 SE +/- 0.04, N = 3 SE +/- 0.06, N = 3 5.61 5.90 7.27 7.53 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
Zstd Compression This test measures the time needed to compress/decompress a sample file (silesia.tar) using Zstd (Zstandard) compression with options for different compression levels / settings. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org MB/s, More Is Better Zstd Compression 1.5.4 Compression Level: 3, Long Mode - Decompression Speed Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 500 1000 1500 2000 2500 SE +/- 5.96, N = 3 SE +/- 3.63, N = 3 SE +/- 3.72, N = 3 SE +/- 4.39, N = 3 2217.4 2249.4 2254.0 2223.8 1. (CC) gcc options: -O3 -pthread -lz -llzma -llz4
OpenBenchmarking.org MB/s, More Is Better Zstd Compression 1.5.4 Compression Level: 3, Long Mode - Compression Speed Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 300 600 900 1200 1500 SE +/- 7.40, N = 3 SE +/- 1.62, N = 3 SE +/- 1.80, N = 3 SE +/- 3.37, N = 3 1319.6 1393.7 1338.3 1413.9 1. (CC) gcc options: -O3 -pthread -lz -llzma -llz4
OpenBenchmarking.org MB/s, More Is Better Zstd Compression 1.5.4 Compression Level: 3 - Decompression Speed Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 500 1000 1500 2000 2500 SE +/- 7.53, N = 3 SE +/- 5.24, N = 3 SE +/- 6.56, N = 3 SE +/- 3.32, N = 3 2162.4 2184.0 2203.6 2170.1 1. (CC) gcc options: -O3 -pthread -lz -llzma -llz4
OpenBenchmarking.org MB/s, More Is Better Zstd Compression 1.5.4 Compression Level: 3 - Compression Speed Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 900 1800 2700 3600 4500 SE +/- 10.85, N = 3 SE +/- 10.25, N = 3 SE +/- 2.07, N = 3 SE +/- 22.63, N = 3 3710.7 4014.3 3959.6 4227.6 1. (CC) gcc options: -O3 -pthread -lz -llzma -llz4
OpenBenchmarking.org MB/s, More Is Better Zstd Compression 1.5.4 Compression Level: 12 - Decompression Speed Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 500 1000 1500 2000 2500 SE +/- 2.91, N = 3 SE +/- 16.52, N = 3 SE +/- 9.67, N = 3 SE +/- 6.83, N = 3 2453.8 2452.0 2452.8 2439.9 1. (CC) gcc options: -O3 -pthread -lz -llzma -llz4
OpenBenchmarking.org MB/s, More Is Better Zstd Compression 1.5.4 Compression Level: 12 - Compression Speed Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 60 120 180 240 300 SE +/- 2.69, N = 3 SE +/- 0.55, N = 3 SE +/- 1.20, N = 3 SE +/- 1.42, N = 3 298.3 248.8 292.4 253.6 1. (CC) gcc options: -O3 -pthread -lz -llzma -llz4
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.org ms, Fewer Is Better OpenVINO 2022.3 Model: Face Detection FP16 - Device: CPU Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 130 260 390 520 650 SE +/- 0.29, N = 3 SE +/- 0.69, N = 3 SE +/- 0.95, N = 3 SE +/- 0.39, N = 3 589.39 546.20 589.45 554.42 MIN: 309.39 / MAX: 685.91 MIN: 275.75 / MAX: 574.42 MIN: 407.34 / MAX: 615.98 MIN: 280.02 / MAX: 579.26 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenBenchmarking.org FPS, More Is Better OpenVINO 2022.3 Model: Face Detection FP16 - Device: CPU Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 4 8 12 16 20 SE +/- 0.00, N = 3 SE +/- 0.02, N = 3 SE +/- 0.03, N = 3 SE +/- 0.02, N = 3 10.15 10.95 13.53 14.38 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2022.3 Model: Face Detection FP16-INT8 - Device: CPU Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 70 140 210 280 350 SE +/- 0.08, N = 3 SE +/- 0.86, N = 3 SE +/- 1.12, N = 3 SE +/- 0.86, N = 3 304.86 279.48 304.02 281.59 MIN: 160.61 / MAX: 318.49 MIN: 148.87 / MAX: 292.1 MIN: 154.56 / MAX: 315.21 MIN: 146.44 / MAX: 293.54 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenBenchmarking.org FPS, More Is Better OpenVINO 2022.3 Model: Face Detection FP16-INT8 - Device: CPU Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 7 14 21 28 35 SE +/- 0.01, N = 3 SE +/- 0.07, N = 3 SE +/- 0.09, N = 3 SE +/- 0.09, N = 3 19.64 21.44 26.26 28.37 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
Zstd Compression This test measures the time needed to compress/decompress a sample file (silesia.tar) using Zstd (Zstandard) compression with options for different compression levels / settings. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org MB/s, More Is Better Zstd Compression 1.5.4 Compression Level: 8, Long Mode - Decompression Speed Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 500 1000 1500 2000 2500 SE +/- 4.07, N = 3 SE +/- 0.74, N = 3 SE +/- 12.98, N = 3 SE +/- 0.47, N = 3 2365.3 2410.4 2422.1 2390.4 1. (CC) gcc options: -O3 -pthread -lz -llzma -llz4
OpenBenchmarking.org MB/s, More Is Better Zstd Compression 1.5.4 Compression Level: 8, Long Mode - Compression Speed Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 200 400 600 800 1000 SE +/- 4.92, N = 3 SE +/- 0.92, N = 3 SE +/- 1.52, N = 3 SE +/- 0.72, N = 3 940.9 808.5 1004.2 845.7 1. (CC) gcc options: -O3 -pthread -lz -llzma -llz4
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.org ms, Fewer Is Better OpenVINO 2022.3 Model: Machine Translation EN To DE FP16 - Device: CPU Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 13 26 39 52 65 SE +/- 0.23, N = 3 SE +/- 0.10, N = 3 SE +/- 0.23, N = 3 SE +/- 0.22, N = 3 55.65 53.54 58.99 57.85 MIN: 26.86 / MAX: 87.31 MIN: 31.21 / MAX: 70.2 MIN: 30.71 / MAX: 70.41 MIN: 27.45 / MAX: 68.1 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenBenchmarking.org FPS, More Is Better OpenVINO 2022.3 Model: Machine Translation EN To DE FP16 - Device: CPU Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 30 60 90 120 150 SE +/- 0.45, N = 3 SE +/- 0.21, N = 3 SE +/- 0.53, N = 3 SE +/- 0.55, N = 3 107.76 112.02 135.50 138.14 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2022.3 Model: Person Vehicle Bike Detection FP16 - Device: CPU Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 1.134 2.268 3.402 4.536 5.67 SE +/- 0.03, N = 3 SE +/- 0.04, N = 3 SE +/- 0.01, N = 3 SE +/- 0.03, N = 3 5.04 4.74 4.82 4.78 MIN: 3.53 / MAX: 13.4 MIN: 3.18 / MAX: 12.15 MIN: 3.33 / MAX: 13.06 MIN: 3.45 / MAX: 12.82 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenBenchmarking.org FPS, More Is Better OpenVINO 2022.3 Model: Person Vehicle Bike Detection FP16 - Device: CPU Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 400 800 1200 1600 2000 SE +/- 6.32, N = 3 SE +/- 11.19, N = 3 SE +/- 1.97, N = 3 SE +/- 9.91, N = 3 1188.17 1265.14 1658.15 1670.93 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2022.3 Model: Vehicle Detection FP16-INT8 - Device: CPU Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 1.0733 2.1466 3.2199 4.2932 5.3665 SE +/- 0.00, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 4.77 4.41 4.68 4.34 MIN: 2.89 / MAX: 23.9 MIN: 2.6 / MAX: 12.74 MIN: 2.79 / MAX: 16.02 MIN: 2.71 / MAX: 12.09 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenBenchmarking.org FPS, More Is Better OpenVINO 2022.3 Model: Vehicle Detection FP16-INT8 - Device: CPU Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 400 800 1200 1600 2000 SE +/- 0.73, N = 3 SE +/- 6.32, N = 3 SE +/- 3.94, N = 3 SE +/- 2.59, N = 3 1257.38 1358.90 1706.68 1843.30 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2022.3 Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 0.0878 0.1756 0.2634 0.3512 0.439 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 0.39 0.35 0.39 0.35 MIN: 0.24 / MAX: 61.73 MIN: 0.21 / MAX: 8.31 MIN: 0.22 / MAX: 8.71 MIN: 0.21 / MAX: 7.04 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenBenchmarking.org FPS, More Is Better OpenVINO 2022.3 Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 10K 20K 30K 40K 50K SE +/- 15.66, N = 3 SE +/- 51.92, N = 3 SE +/- 72.52, N = 3 SE +/- 86.54, N = 3 30316.75 33984.40 40658.96 44741.97 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2022.3 Model: Vehicle Detection FP16 - Device: CPU Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 3 6 9 12 15 SE +/- 0.02, N = 3 SE +/- 0.12, N = 3 SE +/- 0.02, N = 3 SE +/- 0.04, N = 3 7.48 9.00 7.97 10.19 MIN: 4.3 / MAX: 42.8 MIN: 4.65 / MAX: 19.47 MIN: 4.7 / MAX: 18.6 MIN: 4.41 / MAX: 24.5 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenBenchmarking.org FPS, More Is Better OpenVINO 2022.3 Model: Vehicle Detection FP16 - Device: CPU Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 200 400 600 800 1000 SE +/- 2.18, N = 3 SE +/- 9.18, N = 3 SE +/- 3.11, N = 3 SE +/- 3.17, N = 3 801.87 666.35 1003.48 784.25 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2022.3 Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 0.1508 0.3016 0.4524 0.6032 0.754 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 0.67 0.60 0.67 0.61 MIN: 0.37 / MAX: 45.37 MIN: 0.33 / MAX: 7.83 MIN: 0.35 / MAX: 9.57 MIN: 0.34 / MAX: 7.64 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenBenchmarking.org FPS, More Is Better OpenVINO 2022.3 Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 6K 12K 18K 24K 30K SE +/- 3.40, N = 3 SE +/- 119.95, N = 3 SE +/- 77.85, N = 3 SE +/- 29.30, N = 3 17663.84 19661.30 23679.43 26015.99 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2022.3 Model: Weld Porosity Detection FP16-INT8 - Device: CPU Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 2 4 6 8 10 SE +/- 0.00, N = 3 SE +/- 0.03, N = 3 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 6.12 5.51 6.11 5.53 MIN: 3.22 / MAX: 17.67 MIN: 2.96 / MAX: 12.69 MIN: 3.19 / MAX: 13.31 MIN: 2.99 / MAX: 13.65 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenBenchmarking.org FPS, More Is Better OpenVINO 2022.3 Model: Weld Porosity Detection FP16-INT8 - Device: CPU Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 600 1200 1800 2400 3000 SE +/- 0.41, N = 3 SE +/- 13.39, N = 3 SE +/- 2.92, N = 3 SE +/- 2.33, N = 3 1959.52 2176.11 2616.08 2892.63 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2022.3 Model: Weld Porosity Detection FP16 - Device: CPU Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 2 4 6 8 10 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 SE +/- 0.01, N = 3 5.99 5.50 6.01 5.54 MIN: 3.12 / MAX: 18.55 MIN: 2.79 / MAX: 16.27 MIN: 3.17 / MAX: 13.52 MIN: 2.85 / MAX: 12.56 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenBenchmarking.org FPS, More Is Better OpenVINO 2022.3 Model: Weld Porosity Detection FP16 - Device: CPU Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 300 600 900 1200 1500 SE +/- 0.24, N = 3 SE +/- 0.21, N = 3 SE +/- 0.83, N = 3 SE +/- 1.85, N = 3 1000.47 1089.16 1330.53 1442.53 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
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: Wownero - Hash Count: 1M Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 4K 8K 12K 16K 20K SE +/- 23.48, N = 3 SE +/- 13.65, N = 3 SE +/- 21.89, N = 3 SE +/- 28.90, N = 3 14966.1 15870.6 19562.9 20609.4 1. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc
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 - Execution Time Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 40 80 120 160 200 138.74 171.62 125.99 161.67 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 - Mesh Time Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 6 12 18 24 30 26.21 25.02 23.91 22.79 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
PyHPC Benchmarks PyHPC-Benchmarks is a suite of Python high performance computing benchmarks for execution on CPUs and GPUs using various popular Python HPC libraries. The PyHPC CPU-based benchmarks focus on sequential CPU performance. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Seconds, Fewer Is Better PyHPC Benchmarks 3.0 Device: CPU - Backend: Numpy - Project Size: 4194304 - Benchmark: Isoneutral Mixing Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 0.2432 0.4864 0.7296 0.9728 1.216 SE +/- 0.002, N = 3 SE +/- 0.001, N = 3 SE +/- 0.008, N = 3 SE +/- 0.001, N = 3 1.081 1.057 1.074 1.057
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 too. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.12-rc0 Device: CPU - Batch Size: 64 - Model: GoogLeNet Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 30 60 90 120 150 SE +/- 0.03, N = 3 SE +/- 0.06, N = 3 SE +/- 0.14, N = 3 SE +/- 0.10, N = 3 123.26 125.62 145.29 143.88
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 3.0 Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 0.2419 0.4838 0.7257 0.9676 1.2095 SE +/- 0.002405, N = 4 SE +/- 0.004105, N = 4 SE +/- 0.010030, N = 15 SE +/- 0.006372, N = 15 1.075100 0.979499 0.729510 0.664360 MIN: 1.03 MIN: 0.91 MIN: 0.63 MIN: 0.59 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread
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 too. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.12-rc0 Device: CPU - Batch Size: 16 - Model: ResNet-50 Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 10 20 30 40 50 SE +/- 0.04, N = 3 SE +/- 0.00, N = 3 SE +/- 0.08, N = 3 SE +/- 0.02, N = 3 38.11 38.90 43.19 43.08
PyHPC Benchmarks PyHPC-Benchmarks is a suite of Python high performance computing benchmarks for execution on CPUs and GPUs using various popular Python HPC libraries. The PyHPC CPU-based benchmarks focus on sequential CPU performance. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Seconds, Fewer Is Better PyHPC Benchmarks 3.0 Device: CPU - Backend: Numpy - Project Size: 4194304 - Benchmark: Equation of State Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 0.1645 0.329 0.4935 0.658 0.8225 SE +/- 0.011, N = 12 SE +/- 0.001, N = 3 SE +/- 0.000, N = 3 SE +/- 0.001, N = 3 0.726 0.714 0.731 0.727
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 Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 11 22 33 44 55 SE +/- 0.07, N = 3 SE +/- 0.50, N = 3 SE +/- 0.10, N = 3 SE +/- 0.12, N = 3 31.28 49.63 29.18 47.00 1. (F9X) gfortran options: -O3 -march=native -funroll-loops -fopenmp
srsRAN srsRAN is an open-source LTE/5G software radio suite created by Software Radio Systems (SRS). The srsRAN radio suite was formerly known as srsLTE and can be used for building your own software-defined radio (SDR) 4G/5G mobile network. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org UE Mb/s, More Is Better srsRAN 22.04.1 Test: 4G PHY_DL_Test 100 PRB MIMO 64-QAM Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 50 100 150 200 250 SE +/- 2.56, N = 11 SE +/- 0.87, N = 3 SE +/- 0.33, N = 3 SE +/- 0.72, N = 3 235.3 240.6 243.8 236.9 1. (CXX) g++ options: -std=c++14 -fno-strict-aliasing -march=native -mfpmath=sse -mavx2 -fvisibility=hidden -O3 -fno-trapping-math -fno-math-errno -mavx512f -mavx512cd -mavx512bw -mavx512dq -ldl -lpthread -lm
OpenBenchmarking.org eNb Mb/s, More Is Better srsRAN 22.04.1 Test: 4G PHY_DL_Test 100 PRB MIMO 64-QAM Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 140 280 420 560 700 SE +/- 4.54, N = 11 SE +/- 1.85, N = 3 SE +/- 1.67, N = 3 SE +/- 0.43, N = 3 614.9 627.1 638.3 617.8 1. (CXX) g++ options: -std=c++14 -fno-strict-aliasing -march=native -mfpmath=sse -mavx2 -fvisibility=hidden -O3 -fno-trapping-math -fno-math-errno -mavx512f -mavx512cd -mavx512bw -mavx512dq -ldl -lpthread -lm
Pennant Pennant is an application focused on hydrodynamics on general unstructured meshes in 2D. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Hydro Cycle Time - Seconds, Fewer Is Better Pennant 1.0.1 Test: sedovbig Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 8 16 24 32 40 SE +/- 0.29, N = 3 SE +/- 0.14, N = 3 SE +/- 0.11, N = 3 SE +/- 0.02, N = 3 30.94 36.88 27.04 34.85 1. (CXX) g++ options: -fopenmp -lmpi_cxx -lmpi
Embree Intel Embree is a collection of high-performance ray-tracing kernels for execution on CPUs (and GPUs via SYCL) and supporting instruction sets such as SSE, AVX, AVX2, and AVX-512. Embree also supports making use of the Intel SPMD Program Compiler (ISPC). Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Frames Per Second, More Is Better Embree 4.0 Binary: Pathtracer - Model: Asian Dragon Obj Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 7 14 21 28 35 SE +/- 0.00, N = 3 SE +/- 0.02, N = 3 SE +/- 0.03, N = 3 SE +/- 0.04, N = 3 23.83 23.82 31.01 29.82 MIN: 23.72 / MAX: 24.15 MIN: 23.68 / MAX: 24.06 MIN: 30.82 / MAX: 31.62 MIN: 29.53 / MAX: 30.29
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 - Gridding Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 3K 6K 9K 12K 15K SE +/- 124.23, N = 3 SE +/- 116.93, N = 3 SE +/- 0.00, N = 3 SE +/- 111.37, N = 6 12051.3 11693.2 12495.0 11211.2 1. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp
OpenBenchmarking.org Mpix/sec, More Is Better ASKAP 1.0 Test: tConvolve MPI - Degridding Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 2K 4K 6K 8K 10K SE +/- 84.09, N = 3 SE +/- 0.00, N = 3 SE +/- 74.40, N = 3 SE +/- 106.21, N = 6 9923.93 10092.10 10858.80 10788.80 1. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp
srsRAN srsRAN is an open-source LTE/5G software radio suite created by Software Radio Systems (SRS). The srsRAN radio suite was formerly known as srsLTE and can be used for building your own software-defined radio (SDR) 4G/5G mobile network. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org UE Mb/s, More Is Better srsRAN 22.04.1 Test: 4G PHY_DL_Test 100 PRB SISO 256-QAM Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 60 120 180 240 300 SE +/- 0.42, N = 15 SE +/- 0.59, N = 4 SE +/- 1.65, N = 4 SE +/- 0.18, N = 4 215.8 264.6 258.5 261.8 1. (CXX) g++ options: -std=c++14 -fno-strict-aliasing -march=native -mfpmath=sse -mavx2 -fvisibility=hidden -O3 -fno-trapping-math -fno-math-errno -mavx512f -mavx512cd -mavx512bw -mavx512dq -ldl -lpthread -lm
OpenBenchmarking.org eNb Mb/s, More Is Better srsRAN 22.04.1 Test: 4G PHY_DL_Test 100 PRB SISO 256-QAM Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 140 280 420 560 700 SE +/- 3.59, N = 15 SE +/- 2.31, N = 4 SE +/- 3.65, N = 4 SE +/- 2.30, N = 4 585.9 669.4 660.1 665.8 1. (CXX) g++ options: -std=c++14 -fno-strict-aliasing -march=native -mfpmath=sse -mavx2 -fvisibility=hidden -O3 -fno-trapping-math -fno-math-errno -mavx512f -mavx512cd -mavx512bw -mavx512dq -ldl -lpthread -lm
Embree Intel Embree is a collection of high-performance ray-tracing kernels for execution on CPUs (and GPUs via SYCL) and supporting instruction sets such as SSE, AVX, AVX2, and AVX-512. Embree also supports making use of the Intel SPMD Program Compiler (ISPC). Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Frames Per Second, More Is Better Embree 4.0 Binary: Pathtracer ISPC - Model: Asian Dragon Obj Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 8 16 24 32 40 SE +/- 0.01, N = 3 SE +/- 0.04, N = 3 SE +/- 0.07, N = 3 SE +/- 0.01, N = 3 26.96 26.49 34.16 31.78 MIN: 26.76 / MAX: 27.4 MIN: 26.24 / MAX: 27.06 MIN: 33.76 / MAX: 35.23 MIN: 31.44 / MAX: 32.76
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 too. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.12-rc0 Device: CPU - Batch Size: 32 - Model: GoogLeNet Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 30 60 90 120 150 SE +/- 0.03, N = 3 SE +/- 0.13, N = 3 SE +/- 0.15, N = 3 SE +/- 0.17, N = 3 126.27 127.67 149.39 147.08
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 3.0 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: bf16bf16bf16 - Engine: CPU Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 0.0683 0.1366 0.2049 0.2732 0.3415 SE +/- 0.004459, N = 15 SE +/- 0.000581, N = 4 SE +/- 0.000569, N = 4 SE +/- 0.000189, N = 4 0.303464 0.264826 0.229773 0.212801 MIN: 0.29 MIN: 0.25 MIN: 0.22 MIN: 0.2 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread
ACES DGEMM This is a multi-threaded DGEMM benchmark. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org GFLOP/s, More Is Better ACES DGEMM 1.0 Sustained Floating-Point Rate Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 3 6 9 12 15 SE +/- 0.008361, N = 3 SE +/- 0.062303, N = 3 SE +/- 0.160508, N = 3 SE +/- 0.134859, N = 3 8.215552 8.248120 11.258406 10.983997 1. (CC) gcc options: -O3 -march=native -fopenmp
srsRAN srsRAN is an open-source LTE/5G software radio suite created by Software Radio Systems (SRS). The srsRAN radio suite was formerly known as srsLTE and can be used for building your own software-defined radio (SDR) 4G/5G mobile network. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org UE Mb/s, More Is Better srsRAN 22.04.1 Test: 4G PHY_DL_Test 100 PRB MIMO 256-QAM Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 60 120 180 240 300 SE +/- 2.06, N = 3 SE +/- 1.39, N = 3 SE +/- 0.67, N = 3 SE +/- 0.25, N = 3 250.3 254.9 256.8 250.7 1. (CXX) g++ options: -std=c++14 -fno-strict-aliasing -march=native -mfpmath=sse -mavx2 -fvisibility=hidden -O3 -fno-trapping-math -fno-math-errno -mavx512f -mavx512cd -mavx512bw -mavx512dq -ldl -lpthread -lm
OpenBenchmarking.org eNb Mb/s, More Is Better srsRAN 22.04.1 Test: 4G PHY_DL_Test 100 PRB MIMO 256-QAM Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 150 300 450 600 750 SE +/- 7.85, N = 3 SE +/- 1.63, N = 3 SE +/- 1.62, N = 3 SE +/- 0.74, N = 3 665.2 677.8 686.0 667.0 1. (CXX) g++ options: -std=c++14 -fno-strict-aliasing -march=native -mfpmath=sse -mavx2 -fvisibility=hidden -O3 -fno-trapping-math -fno-math-errno -mavx512f -mavx512cd -mavx512bw -mavx512dq -ldl -lpthread -lm
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 too. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.12-rc0 Device: CPU - Batch Size: 64 - Model: AlexNet Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 80 160 240 320 400 SE +/- 0.09, N = 3 SE +/- 0.30, N = 3 SE +/- 0.40, N = 3 SE +/- 0.64, N = 3 278.30 294.49 339.80 351.07
Embree Intel Embree is a collection of high-performance ray-tracing kernels for execution on CPUs (and GPUs via SYCL) and supporting instruction sets such as SSE, AVX, AVX2, and AVX-512. Embree also supports making use of the Intel SPMD Program Compiler (ISPC). Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Frames Per Second, More Is Better Embree 4.0 Binary: Pathtracer - Model: Crown Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 8 16 24 32 40 SE +/- 0.03, N = 3 SE +/- 0.03, N = 3 SE +/- 0.16, N = 3 SE +/- 0.05, N = 3 24.23 24.68 32.07 32.53 MIN: 23.99 / MAX: 24.64 MIN: 24.44 / MAX: 25.19 MIN: 31.5 / MAX: 32.66 MIN: 32.17 / MAX: 33.24
OpenBenchmarking.org Frames Per Second, More Is Better Embree 4.0 Binary: Pathtracer - Model: Asian Dragon Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 8 16 24 32 40 SE +/- 0.01, N = 3 SE +/- 0.04, N = 3 SE +/- 0.05, N = 3 SE +/- 0.03, N = 3 26.55 26.51 34.70 33.63 MIN: 26.42 / MAX: 26.93 MIN: 26.37 / MAX: 26.79 MIN: 34.46 / MAX: 35.13 MIN: 33.39 / MAX: 34.01
Pennant Pennant is an application focused on hydrodynamics on general unstructured meshes in 2D. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Hydro Cycle Time - Seconds, Fewer Is Better Pennant 1.0.1 Test: leblancbig Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 6 12 18 24 30 SE +/- 0.03, N = 3 SE +/- 0.01, N = 3 SE +/- 0.03, N = 3 SE +/- 0.02, N = 3 19.31 25.15 16.86 24.36 1. (CXX) g++ options: -fopenmp -lmpi_cxx -lmpi
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 3.0 Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 1.1659 2.3318 3.4977 4.6636 5.8295 SE +/- 0.01434, N = 3 SE +/- 0.04268, N = 3 SE +/- 0.03845, N = 3 SE +/- 0.02903, N = 3 5.18172 4.71013 3.95886 3.60748 MIN: 4.98 MIN: 4.54 MIN: 3.72 MIN: 3.43 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread
Embree Intel Embree is a collection of high-performance ray-tracing kernels for execution on CPUs (and GPUs via SYCL) and supporting instruction sets such as SSE, AVX, AVX2, and AVX-512. Embree also supports making use of the Intel SPMD Program Compiler (ISPC). Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Frames Per Second, More Is Better Embree 4.0 Binary: Pathtracer ISPC - Model: Crown Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 8 16 24 32 40 SE +/- 0.04, N = 3 SE +/- 0.10, N = 3 SE +/- 0.10, N = 3 SE +/- 0.12, N = 3 27.05 27.64 36.24 36.55 MIN: 26.79 / MAX: 27.57 MIN: 27.15 / MAX: 28.38 MIN: 35.78 / MAX: 36.89 MIN: 35.98 / MAX: 37.5
OpenBenchmarking.org Frames Per Second, More Is Better Embree 4.0 Binary: Pathtracer ISPC - Model: Asian Dragon Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 9 18 27 36 45 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.04, N = 4 SE +/- 0.01, N = 3 31.43 30.89 39.71 37.22 MIN: 31.23 / MAX: 32 MIN: 30.69 / MAX: 31.38 MIN: 39.34 / MAX: 40.55 MIN: 36.85 / MAX: 38.38
srsRAN srsRAN is an open-source LTE/5G software radio suite created by Software Radio Systems (SRS). The srsRAN radio suite was formerly known as srsLTE and can be used for building your own software-defined radio (SDR) 4G/5G mobile network. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Samples / Second, More Is Better srsRAN 22.04.1 Test: OFDM_Test Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 50M 100M 150M 200M 250M SE +/- 1519137.18, N = 3 SE +/- 1266227.99, N = 3 SE +/- 1072898.46, N = 3 SE +/- 1178982.61, N = 3 237333333 237000000 245966667 236600000 1. (CXX) g++ options: -std=c++14 -fno-strict-aliasing -march=native -mfpmath=sse -mavx2 -fvisibility=hidden -O3 -fno-trapping-math -fno-math-errno -mavx512f -mavx512cd -mavx512bw -mavx512dq -ldl -lpthread -lm
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 too. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.12-rc0 Device: CPU - Batch Size: 16 - Model: GoogLeNet Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 30 60 90 120 150 SE +/- 0.02, N = 4 SE +/- 0.09, N = 4 SE +/- 0.07, N = 4 SE +/- 0.14, N = 4 124.65 128.74 147.01 146.99
OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.12-rc0 Device: CPU - Batch Size: 32 - Model: AlexNet Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 60 120 180 240 300 SE +/- 0.10, N = 3 SE +/- 0.05, N = 4 SE +/- 0.06, N = 4 SE +/- 0.14, N = 4 223.03 232.30 258.77 264.33
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.org Seconds, Fewer Is Better Xcompact3d Incompact3d 2021-03-11 Input: input.i3d 129 Cells Per Direction Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 4 8 12 16 20 SE +/- 0.05, N = 4 SE +/- 0.05, N = 4 SE +/- 0.02, N = 4 SE +/- 0.04, N = 4 12.69 14.61 12.54 14.63 1. (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
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 Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 120 240 360 480 600 SE +/- 1.12, N = 5 SE +/- 2.17, N = 5 SE +/- 0.74, N = 5 SE +/- 1.79, N = 5 545.86 440.18 548.25 448.46 1. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp
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 3.0 Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 0.4744 0.9488 1.4232 1.8976 2.372 SE +/- 0.00176, N = 7 SE +/- 0.00247, N = 7 SE +/- 0.00908, N = 7 SE +/- 0.37855, N = 15 1.38144 1.81291 1.08640 2.10831 MIN: 1.34 MIN: 1.74 MIN: 1.01 MIN: 1.63 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread
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 too. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.12-rc0 Device: CPU - Batch Size: 16 - Model: AlexNet Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 40 80 120 160 200 SE +/- 0.07, N = 4 SE +/- 0.22, N = 4 SE +/- 0.18, N = 5 SE +/- 0.11, N = 5 158.97 162.66 176.22 176.72
KTX-Software toktx This is a benchmark of The Khronos Group's KTX-Software library and tools. KTX-Software provides "toktx" for converting/creating in the KTX container format for image textures. This benchmark times how long it takes to convert to KTX 2.0 format with various settings using a reference PNG sample input. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Seconds, Fewer Is Better KTX-Software toktx 4.0 Settings: Zstd Compression 19 Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 3 6 9 12 15 SE +/- 0.03, N = 4 SE +/- 0.07, N = 4 SE +/- 0.06, N = 5 SE +/- 0.05, N = 5 11.53 11.64 11.46 11.22
srsRAN srsRAN is an open-source LTE/5G software radio suite created by Software Radio Systems (SRS). The srsRAN radio suite was formerly known as srsLTE and can be used for building your own software-defined radio (SDR) 4G/5G mobile network. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org UE Mb/s, More Is Better srsRAN 22.04.1 Test: 5G PHY_DL_NR Test 52 PRB SISO 64-QAM Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 30 60 90 120 150 SE +/- 4.42, N = 5 SE +/- 0.21, N = 5 SE +/- 0.93, N = 5 SE +/- 0.23, N = 5 136.8 145.3 144.2 142.9 1. (CXX) g++ options: -std=c++14 -fno-strict-aliasing -march=native -mfpmath=sse -mavx2 -fvisibility=hidden -O3 -fno-trapping-math -fno-math-errno -mavx512f -mavx512cd -mavx512bw -mavx512dq -ldl -lpthread -lm
OpenBenchmarking.org eNb Mb/s, More Is Better srsRAN 22.04.1 Test: 5G PHY_DL_NR Test 52 PRB SISO 64-QAM Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 50 100 150 200 250 SE +/- 1.58, N = 5 SE +/- 0.81, N = 5 SE +/- 1.38, N = 5 SE +/- 0.56, N = 5 209.9 211.6 211.5 209.5 1. (CXX) g++ options: -std=c++14 -fno-strict-aliasing -march=native -mfpmath=sse -mavx2 -fvisibility=hidden -O3 -fno-trapping-math -fno-math-errno -mavx512f -mavx512cd -mavx512bw -mavx512dq -ldl -lpthread -lm
OpenBenchmarking.org UE Mb/s, More Is Better srsRAN 22.04.1 Test: 4G PHY_DL_Test 100 PRB SISO 64-QAM Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 60 120 180 240 300 SE +/- 0.45, N = 5 SE +/- 0.34, N = 5 SE +/- 0.83, N = 5 SE +/- 0.90, N = 5 250.6 251.1 252.0 247.4 1. (CXX) g++ options: -std=c++14 -fno-strict-aliasing -march=native -mfpmath=sse -mavx2 -fvisibility=hidden -O3 -fno-trapping-math -fno-math-errno -mavx512f -mavx512cd -mavx512bw -mavx512dq -ldl -lpthread -lm
OpenBenchmarking.org eNb Mb/s, More Is Better srsRAN 22.04.1 Test: 4G PHY_DL_Test 100 PRB SISO 64-QAM Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 130 260 390 520 650 SE +/- 1.40, N = 5 SE +/- 1.26, N = 5 SE +/- 4.56, N = 5 SE +/- 6.18, N = 5 619.7 622.7 616.3 609.0 1. (CXX) g++ options: -std=c++14 -fno-strict-aliasing -march=native -mfpmath=sse -mavx2 -fvisibility=hidden -O3 -fno-trapping-math -fno-math-errno -mavx512f -mavx512cd -mavx512bw -mavx512dq -ldl -lpthread -lm
KTX-Software toktx This is a benchmark of The Khronos Group's KTX-Software library and tools. KTX-Software provides "toktx" for converting/creating in the KTX container format for image textures. This benchmark times how long it takes to convert to KTX 2.0 format with various settings using a reference PNG sample input. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Seconds, Fewer Is Better KTX-Software toktx 4.0 Settings: UASTC 3 + Zstd Compression 19 Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 3 6 9 12 15 SE +/- 0.014, N = 5 SE +/- 0.013, N = 5 SE +/- 0.012, N = 5 SE +/- 0.005, N = 5 10.037 9.698 8.747 8.405
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 3.0 Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 0.3425 0.685 1.0275 1.37 1.7125 SE +/- 0.00690, N = 5 SE +/- 0.01359, N = 5 SE +/- 0.00875, N = 5 SE +/- 0.00933, N = 5 1.16165 1.51749 1.08373 1.52232 MIN: 1.08 MIN: 1.4 MIN: 0.97 MIN: 1.4 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread
LULESH LULESH is the Livermore Unstructured Lagrangian Explicit Shock Hydrodynamics. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org z/s, More Is Better LULESH 2.0.3 Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 2K 4K 6K 8K 10K SE +/- 19.85, N = 7 SE +/- 18.50, N = 6 SE +/- 15.81, N = 7 SE +/- 22.43, N = 6 8953.05 8484.57 8987.94 8479.88 1. (CXX) g++ options: -O3 -fopenmp -lm -lmpi_cxx -lmpi
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 OpenMP - Degridding Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 2K 4K 6K 8K 10K SE +/- 76.62, N = 7 SE +/- 107.63, N = 6 SE +/- 97.44, N = 7 SE +/- 35.18, N = 4 10078.06 5756.77 11369.60 6156.82 1. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp
OpenBenchmarking.org Million Grid Points Per Second, More Is Better ASKAP 1.0 Test: tConvolve OpenMP - Gridding Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 1500 3000 4500 6000 7500 SE +/- 30.03, N = 7 SE +/- 34.63, N = 6 SE +/- 61.20, N = 7 SE +/- 46.08, N = 6 6052.16 5024.89 6780.79 6099.22 1. (CXX) g++ options: -O3 -fstrict-aliasing -fopenmp
KTX-Software toktx This is a benchmark of The Khronos Group's KTX-Software library and tools. KTX-Software provides "toktx" for converting/creating in the KTX container format for image textures. This benchmark times how long it takes to convert to KTX 2.0 format with various settings using a reference PNG sample input. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Seconds, Fewer Is Better KTX-Software toktx 4.0 Settings: UASTC 3 Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 2 4 6 8 10 SE +/- 0.004, N = 6 SE +/- 0.006, N = 7 SE +/- 0.019, N = 7 SE +/- 0.003, N = 7 6.374 5.944 5.126 4.885
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 3.0 Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU Ryzen 9 7900X3D Ryzen 9 7900X Ryzen 9 79500X3D Ryzen 9 7950X 0.4565 0.913 1.3695 1.826 2.2825 SE +/- 0.00266, N = 9 SE +/- 0.00295, N = 9 SE +/- 0.00172, N = 9 SE +/- 0.00250, N = 9 2.02903 1.79830 1.50715 1.40849 MIN: 1.97 MIN: 1.7 MIN: 1.46 MIN: 1.34 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread
KTX-Software toktx This is a benchmark of The Khronos Group's KTX-Software library and tools. KTX-Software provides "toktx" for converting/creating in the KTX container format for image textures. This benchmark times how long it takes to convert to KTX 2.0 format with various settings using a reference PNG sample input. Learn more via the OpenBenchmarking.org test page.
Settings: Zstd Compression 9
Ryzen 9 7900X3D: The test run did not produce a result.
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Open Porous Media Git This is a test of Open Porous Media, a set of open-source tools concerning simulation of flow and transport of fluids in porous media. This test profile builds OPM and its dependencies from upstream Git. Learn more via the OpenBenchmarking.org test page.
OPM Benchmark: Drogon - Threads: 16
Ryzen 9 7900X3D: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16
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OPM Benchmark: Flow MPI Norne - Threads: 16
Ryzen 9 7900X3D: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16
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OPM Benchmark: PUNQ-S3 - Threads: 16
Ryzen 9 7900X3D: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16
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OPM Benchmark: Flow MPI Norne-4C MSW - Threads: 16
Ryzen 9 7900X3D: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16
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Ryzen 9 79500X3D: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access
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OPM Benchmark: Flow MPI Extra - Threads: 16
Ryzen 9 7900X3D: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16
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OPM Benchmark: SPE10 Model 1 - Threads: 16
Ryzen 9 7900X3D: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16
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OPM Benchmark: Smeaheia - Threads: 16
Ryzen 9 7900X3D: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16
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Ryzen 9 79500X3D: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access
Ryzen 9 7950X: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access
OPM Benchmark: SPE10 Model 2 - Threads: 16
Ryzen 9 7900X3D: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16
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Ryzen 9 79500X3D: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access
Ryzen 9 7950X: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access
OPM Benchmark: Upscale-Relperm - Threads: 16
Ryzen 9 7900X3D: The test run did not produce a result. E: There are not enough slots available in the system to satisfy the 16
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Ryzen 9 79500X3D: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access
Ryzen 9 7950X: The test run did not produce a result. E: mpirun was unable to launch the specified application as it could not access
PyHPC Benchmarks PyHPC-Benchmarks is a suite of Python high performance computing benchmarks for execution on CPUs and GPUs using various popular Python HPC libraries. The PyHPC CPU-based benchmarks focus on sequential CPU performance. Learn more via the OpenBenchmarking.org test page.
Device: CPU - Backend: Aesara - Project Size: 4194304 - Benchmark: Equation of State
Ryzen 9 7900X3D: The test run did not produce a result.
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Device: CPU - Backend: Aesara - Project Size: 4194304 - Benchmark: Isoneutral Mixing
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Device: CPU - Backend: PyTorch - Project Size: 4194304 - Benchmark: Equation of State
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Device: CPU - Backend: PyTorch - Project Size: 4194304 - Benchmark: Isoneutral Mixing
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Device: CPU - Backend: JAX - Project Size: 4194304 - Benchmark: Equation of State
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Device: CPU - Backend: TensorFlow - Project Size: 4194304 - Benchmark: Equation of State
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Device: CPU - Backend: TensorFlow - Project Size: 4194304 - Benchmark: Isoneutral Mixing
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Device: CPU - Backend: Numba - Project Size: 4194304 - Benchmark: Equation of State
Ryzen 9 7900X3D: The test run did not produce a result.
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Device: CPU - Backend: Numba - Project Size: 4194304 - Benchmark: Isoneutral Mixing
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Device: CPU - Backend: JAX - Project Size: 4194304 - Benchmark: Isoneutral Mixing
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Ryzen 9 79500X3D: The test run did not produce a result.
Ryzen 9 7950X: The test run did not produce a result.
Ryzen 9 7900X3D Processor: AMD Ryzen 9 7900X3D 12-Core @ 4.40GHz (12 Cores / 24 Threads), Motherboard: ASUS ROG CROSSHAIR X670E HERO (9922 BIOS), Chipset: AMD Device 14d8, Memory: 32GB, Disk: Western Digital WD_BLACK SN850X 1000GB + 2000GB, Graphics: AMD Radeon RX 7900 XTX 24GB (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: 6.2.2-060202-generic (x86_64), Desktop: GNOME Shell 43.2, Display Server: X Server 1.21.1.6 + Wayland, OpenGL: 4.6 Mesa 23.1.0-devel (git-efcb639 2023-02-13 lunar-oibaf-ppa) (LLVM 15.0.7 DRM 3.49), 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-AKimc9/gcc-12-12.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-12-AKimc9/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: 0xa601203Python Notes: Python 3.11.1Security 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 3 March 2023 20:08 by user phoronix.
Ryzen 9 7900X Processor: AMD Ryzen 9 7900X 12-Core @ 4.70GHz (12 Cores / 24 Threads), Motherboard: ASUS ROG CROSSHAIR X670E HERO (9922 BIOS), Chipset: AMD Device 14d8, Memory: 32GB, Disk: Western Digital WD_BLACK SN850X 1000GB + 2000GB, Graphics: AMD Radeon RX 7900 XTX 24GB (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: 6.2.2-060202-generic (x86_64), Desktop: GNOME Shell 43.2, Display Server: X Server 1.21.1.6 + Wayland, OpenGL: 4.6 Mesa 23.1.0-devel (git-efcb639 2023-02-13 lunar-oibaf-ppa) (LLVM 15.0.7 DRM 3.49), 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-AKimc9/gcc-12-12.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-12-AKimc9/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: 0xa601203Python Notes: Python 3.11.1Security 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 4 March 2023 06:58 by user phoronix.
Ryzen 9 79500X3D Processor: AMD Ryzen 9 7950X3D 16-Core @ 4.20GHz (16 Cores / 32 Threads), Motherboard: ASUS ROG CROSSHAIR X670E HERO (9922 BIOS), Chipset: AMD Device 14d8, Memory: 32GB, Disk: Western Digital WD_BLACK SN850X 1000GB + 2000GB, Graphics: AMD Radeon RX 7900 XTX 24GB (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: 6.2.2-060202-generic (x86_64), Desktop: GNOME Shell 43.2, Display Server: X Server 1.21.1.6 + Wayland, OpenGL: 4.6 Mesa 23.1.0-devel (git-efcb639 2023-02-13 lunar-oibaf-ppa) (LLVM 15.0.7 DRM 3.49), 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-AKimc9/gcc-12-12.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-12-AKimc9/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: 0xa601203Python Notes: Python 3.11.1Security 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 4 March 2023 21:15 by user phoronix.
Ryzen 9 7950X Processor: AMD Ryzen 9 7950X 16-Core @ 4.50GHz (16 Cores / 32 Threads), Motherboard: ASUS ROG CROSSHAIR X670E HERO (9922 BIOS), Chipset: AMD Device 14d8, Memory: 32GB, Disk: Western Digital WD_BLACK SN850X 1000GB + 2000GB, Graphics: AMD Radeon RX 7900 XTX 24GB (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: 6.2.2-060202-generic (x86_64), Desktop: GNOME Shell 43.2, Display Server: X Server 1.21.1.6 + Wayland, OpenGL: 4.6 Mesa 23.1.0-devel (git-efcb639 2023-02-13 lunar-oibaf-ppa) (LLVM 15.0.7 DRM 3.49), 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-AKimc9/gcc-12-12.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-12-AKimc9/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: 0xa601203Python Notes: Python 3.11.1Security 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 March 2023 06:57 by user phoronix.