AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C+6G testing with a ASRock A320M-HDV R4.0 (P2.00 BIOS) and llvmpipe on Ubuntu 20.04 via the Phoronix Test Suite.
llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C Processor: AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C+6G @ 3.10GHz (2 Cores / 4 Threads), Motherboard: ASRock A320M-HDV R4.0 (P2.00 BIOS), Chipset: AMD 15h, Memory: 3584MB, Disk: 1000GB Western Digital WDS100T2B0A, Graphics: llvmpipe, Audio: AMD Kabini HDMI/DP, Network: Realtek RTL8111/8168/8411
OS: Ubuntu 20.04, Kernel: 5.15.0-89-generic (x86_64), Desktop: GNOME Shell 3.36.9, Display Server: X Server 1.20.13, OpenGL: 4.5 Mesa 21.2.6 (LLVM 12.0.0 256 bits), Vulkan: 1.1.182, Compiler: GCC 9.4.0, File-System: ext4, Screen Resolution: 1368x768
Kernel Notes: Transparent Huge Pages: madviseCompiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++,gm2 --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-9-9QDOt0/gcc-9-9.4.0/debian/tmp-nvptx/usr,hsa --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 ondemand (Boost: Enabled) - CPU Microcode: 0x600611aPython Notes: Python 3.8.10Security Notes: gather_data_sampling: Not affected + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Mitigation of untrained return thunk; SMT vulnerable + spec_rstack_overflow: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Retpolines IBPB: conditional STIBP: disabled RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected
Whisper.cpp Whisper.cpp is a port of OpenAI's Whisper model in C/C++. Whisper.cpp is developed by Georgi Gerganov for transcribing WAV audio files to text / speech recognition. Whisper.cpp supports ARM NEON, x86 AVX, and other advanced CPU features. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Seconds, Fewer Is Better Whisper.cpp 1.4 Model: ggml-medium.en - Input: 2016 State of the Union llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 6K 12K 18K 24K 30K SE +/- 3.98, N = 3 29217.40 1. (CXX) g++ options: -O3 -std=c++11 -fPIC -pthread
OpenBenchmarking.org Seconds, Fewer Is Better Whisper.cpp 1.4 Model: ggml-small.en - Input: 2016 State of the Union llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 2K 4K 6K 8K 10K SE +/- 4.12, N = 3 8252.81 1. (CXX) g++ options: -O3 -std=c++11 -fPIC -pthread
OpenBenchmarking.org Seconds, Fewer Is Better Whisper.cpp 1.4 Model: ggml-base.en - Input: 2016 State of the Union llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 500 1000 1500 2000 2500 SE +/- 3.14, N = 3 2498.67 1. (CXX) g++ options: -O3 -std=c++11 -fPIC -pthread
OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Kernel PCA Solvers / Time vs. N Components llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 70 140 210 280 350 SE +/- 0.55, N = 3 329.19 1. (F9X) gfortran options: -O0
OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Kernel PCA Solvers / Time vs. N Samples llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 160 320 480 640 800 SE +/- 1.47, N = 3 720.17 1. (F9X) gfortran options: -O0
OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Hist Gradient Boosting Categorical Only llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 14 28 42 56 70 SE +/- 0.19, N = 3 61.35 1. (F9X) gfortran options: -O0
OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Plot Polynomial Kernel Approximation llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 160 320 480 640 800 SE +/- 0.98, N = 3 761.96 1. (F9X) gfortran options: -O0
OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: 20 Newsgroups / Logistic Regression llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 30 60 90 120 150 SE +/- 0.05, N = 3 126.69 1. (F9X) gfortran options: -O0
OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Hist Gradient Boosting Higgs Boson llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 70 140 210 280 350 SE +/- 2.43, N = 3 309.51 1. (F9X) gfortran options: -O0
OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Plot Singular Value Decomposition llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 150 300 450 600 750 SE +/- 2.73, N = 3 692.64 1. (F9X) gfortran options: -O0
OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Hist Gradient Boosting Threading llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 200 400 600 800 1000 SE +/- 1.98, N = 3 838.41 1. (F9X) gfortran options: -O0
OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Hist Gradient Boosting Adult llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 40 80 120 160 200 SE +/- 2.73, N = 3 202.00 1. (F9X) gfortran options: -O0
OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Covertype Dataset Benchmark llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 200 400 600 800 1000 SE +/- 1.44, N = 3 965.03 1. (F9X) gfortran options: -O0
OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Sample Without Replacement llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 70 140 210 280 350 SE +/- 2.47, N = 3 338.63 1. (F9X) gfortran options: -O0
OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Hist Gradient Boosting llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 90 180 270 360 450 SE +/- 0.77, N = 3 414.92 1. (F9X) gfortran options: -O0
OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Plot Incremental PCA llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 20 40 60 80 100 SE +/- 0.25, N = 3 110.29 1. (F9X) gfortran options: -O0
OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: TSNE MNIST Dataset llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 300 600 900 1200 1500 SE +/- 3.72, N = 3 1425.79 1. (F9X) gfortran options: -O0
OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: LocalOutlierFactor llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 120 240 360 480 600 SE +/- 2.37, N = 3 559.54 1. (F9X) gfortran options: -O0
OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Feature Expansions llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 110 220 330 440 550 SE +/- 0.21, N = 3 491.63 1. (F9X) gfortran options: -O0
OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Plot OMP vs. LARS llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 80 160 240 320 400 SE +/- 4.35, N = 3 355.35 1. (F9X) gfortran options: -O0
OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Plot Hierarchical llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 160 320 480 640 800 SE +/- 0.36, N = 3 722.27 1. (F9X) gfortran options: -O0
OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Text Vectorizers llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 40 80 120 160 200 SE +/- 0.44, N = 3 171.50 1. (F9X) gfortran options: -O0
OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Plot Lasso Path llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 200 400 600 800 1000 SE +/- 1.49, N = 3 835.04 1. (F9X) gfortran options: -O0
OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: SGD Regression llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 80 160 240 320 400 SE +/- 0.51, N = 3 358.67 1. (F9X) gfortran options: -O0
OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Plot Neighbors llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 130 260 390 520 650 SE +/- 1.93, N = 3 599.88 1. (F9X) gfortran options: -O0
OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: MNIST Dataset llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 40 80 120 160 200 SE +/- 0.10, N = 3 177.39 1. (F9X) gfortran options: -O0
OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Plot Ward llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 40 80 120 160 200 SE +/- 0.33, N = 3 202.93 1. (F9X) gfortran options: -O0
OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Sparsify llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 50 100 150 200 250 SE +/- 0.05, N = 3 226.79 1. (F9X) gfortran options: -O0
OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Lasso llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 300 600 900 1200 1500 SE +/- 2.47, N = 3 1312.06 1. (F9X) gfortran options: -O0
OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: Tree llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 20 40 60 80 100 SE +/- 0.84, N = 15 103.79 1. (F9X) gfortran options: -O0
OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: SAGA llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 400 800 1200 1600 2000 SE +/- 9.65, N = 3 1919.81 1. (F9X) gfortran options: -O0
OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.2.2 Benchmark: GLM llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 400 800 1200 1600 2000 SE +/- 3.03, N = 3 1877.54 1. (F9X) gfortran options: -O0
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.
Numenta Anomaly Benchmark Numenta Anomaly Benchmark (NAB) is a benchmark for evaluating algorithms for anomaly detection in streaming, real-time applications. It is comprised of over 50 labeled real-world and artificial time-series data files plus a novel scoring mechanism designed for real-time applications. This test profile currently measures the time to run various detectors. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Seconds, Fewer Is Better Numenta Anomaly Benchmark 1.1 Detector: Contextual Anomaly Detector OSE llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 60 120 180 240 300 SE +/- 0.36, N = 3 272.34
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 2023.2.dev Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.6525 1.305 1.9575 2.61 3.2625 SE +/- 0.01, N = 3 2.90 MIN: 1.7 / MAX: 21.02 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org FPS, More Is Better OpenVINO 2023.2.dev Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 150 300 450 600 750 SE +/- 2.10, N = 3 681.70 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2023.2.dev Model: Handwritten English Recognition FP16-INT8 - Device: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 130 260 390 520 650 SE +/- 7.12, N = 4 587.13 MIN: 363.64 / MAX: 654.95 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org FPS, More Is Better OpenVINO 2023.2.dev Model: Handwritten English Recognition FP16-INT8 - Device: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.7673 1.5346 2.3019 3.0692 3.8365 SE +/- 0.04, N = 4 3.41 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2023.2.dev Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 1.0215 2.043 3.0645 4.086 5.1075 SE +/- 0.01, N = 3 4.54 MIN: 2.6 / MAX: 35.33 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org FPS, More Is Better OpenVINO 2023.2.dev Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 90 180 270 360 450 SE +/- 1.43, N = 3 438.38 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2023.2.dev Model: Person Vehicle Bike Detection FP16 - Device: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 20 40 60 80 100 SE +/- 1.13, N = 3 84.09 MIN: 43.23 / MAX: 147.08 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org FPS, More Is Better OpenVINO 2023.2.dev Model: Person Vehicle Bike Detection FP16 - Device: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 6 12 18 24 30 SE +/- 0.32, N = 3 23.78 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2023.2.dev Model: Weld Porosity Detection FP16-INT8 - Device: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 15 30 45 60 75 SE +/- 0.29, N = 3 67.76 MIN: 39.77 / MAX: 88.07 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org FPS, More Is Better OpenVINO 2023.2.dev Model: Weld Porosity Detection FP16-INT8 - Device: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 7 14 21 28 35 SE +/- 0.13, N = 3 29.49 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2023.2.dev Model: Machine Translation EN To DE FP16 - Device: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 150 300 450 600 750 SE +/- 1.68, N = 3 716.36 MIN: 663.2 / MAX: 742.36 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org FPS, More Is Better OpenVINO 2023.2.dev Model: Machine Translation EN To DE FP16 - Device: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.6278 1.2556 1.8834 2.5112 3.139 SE +/- 0.00, N = 3 2.79 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2023.2.dev Model: Road Segmentation ADAS FP16-INT8 - Device: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 40 80 120 160 200 SE +/- 1.03, N = 3 202.73 MIN: 172.53 / MAX: 241.67 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org FPS, More Is Better OpenVINO 2023.2.dev Model: Road Segmentation ADAS FP16-INT8 - Device: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 3 6 9 12 15 SE +/- 0.05, N = 3 9.86 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2023.2.dev Model: Face Detection Retail FP16-INT8 - Device: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 7 14 21 28 35 SE +/- 0.25, N = 15 30.73 MIN: 17.23 / MAX: 53.2 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org FPS, More Is Better OpenVINO 2023.2.dev Model: Face Detection Retail FP16-INT8 - Device: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 15 30 45 60 75 SE +/- 0.53, N = 15 65.08 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2023.2.dev Model: Weld Porosity Detection FP16 - Device: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 20 40 60 80 100 SE +/- 0.25, N = 3 92.76 MIN: 67.15 / MAX: 134.83 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org FPS, More Is Better OpenVINO 2023.2.dev Model: Weld Porosity Detection FP16 - Device: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 5 10 15 20 25 SE +/- 0.06, N = 3 21.55 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2023.2.dev Model: Vehicle Detection FP16-INT8 - Device: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 20 40 60 80 100 SE +/- 0.80, N = 3 98.95 MIN: 63.4 / MAX: 121.43 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org FPS, More Is Better OpenVINO 2023.2.dev Model: Vehicle Detection FP16-INT8 - Device: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 5 10 15 20 25 SE +/- 0.16, N = 3 20.20 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2023.2.dev Model: Road Segmentation ADAS FP16 - Device: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 90 180 270 360 450 SE +/- 1.31, N = 3 426.61 MIN: 366.94 / MAX: 466.48 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org FPS, More Is Better OpenVINO 2023.2.dev Model: Road Segmentation ADAS FP16 - Device: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 1.0553 2.1106 3.1659 4.2212 5.2765 SE +/- 0.01, N = 3 4.69 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2023.2.dev Model: Face Detection Retail FP16 - Device: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 10 20 30 40 50 SE +/- 0.09, N = 3 42.70 MIN: 20.92 / MAX: 63.97 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org FPS, More Is Better OpenVINO 2023.2.dev Model: Face Detection Retail FP16 - Device: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 11 22 33 44 55 SE +/- 0.10, N = 3 46.80 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2023.2.dev Model: Face Detection FP16-INT8 - Device: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 1400 2800 4200 5600 7000 SE +/- 12.52, N = 3 6728.06 MIN: 6553.59 / MAX: 7002.51 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org FPS, More Is Better OpenVINO 2023.2.dev Model: Face Detection FP16-INT8 - Device: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.0675 0.135 0.2025 0.27 0.3375 SE +/- 0.00, N = 3 0.3 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2023.2.dev Model: Vehicle Detection FP16 - Device: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 40 80 120 160 200 SE +/- 0.99, N = 3 168.71 MIN: 119.34 / MAX: 195.23 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org FPS, More Is Better OpenVINO 2023.2.dev Model: Vehicle Detection FP16 - Device: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 3 6 9 12 15 SE +/- 0.07, N = 3 11.85 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2023.2.dev Model: Person Detection FP32 - Device: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 200 400 600 800 1000 SE +/- 1.28, N = 3 1044.45 MIN: 970.14 / MAX: 1115.69 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org FPS, More Is Better OpenVINO 2023.2.dev Model: Person Detection FP32 - Device: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.4298 0.8596 1.2894 1.7192 2.149 SE +/- 0.00, N = 3 1.91 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2023.2.dev Model: Person Detection FP16 - Device: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 200 400 600 800 1000 SE +/- 1.70, N = 3 1042.19 MIN: 990.71 / MAX: 1084.32 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org FPS, More Is Better OpenVINO 2023.2.dev Model: Person Detection FP16 - Device: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.432 0.864 1.296 1.728 2.16 SE +/- 0.00, N = 3 1.92 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2023.2.dev Model: Face Detection FP16 - Device: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 2K 4K 6K 8K 10K SE +/- 5.44, N = 3 8841.25 MIN: 8808.56 / MAX: 8886.06 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org FPS, More Is Better OpenVINO 2023.2.dev Model: Face Detection FP16 - Device: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.0518 0.1036 0.1554 0.2072 0.259 SE +/- 0.00, N = 3 0.23 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org FPS, More Is Better PlaidML FP16: No - Mode: Inference - Network: VGG16 - Device: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.2993 0.5986 0.8979 1.1972 1.4965 SE +/- 0.01, N = 3 1.33
TNN TNN is an open-source deep learning reasoning framework developed by Tencent. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org ms, Fewer Is Better TNN 0.3 Target: CPU - Model: SqueezeNet v1.1 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 120 240 360 480 600 SE +/- 2.06, N = 3 557.95 MIN: 553.57 / MAX: 564.29 1. (CXX) g++ options: -fopenmp -pthread -fvisibility=hidden -fvisibility=default -O3 -rdynamic -ldl
OpenBenchmarking.org ms, Fewer Is Better TNN 0.3 Target: CPU - Model: SqueezeNet v2 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 30 60 90 120 150 SE +/- 0.52, N = 3 135.31 MIN: 132.96 / MAX: 140.41 1. (CXX) g++ options: -fopenmp -pthread -fvisibility=hidden -fvisibility=default -O3 -rdynamic -ldl
OpenBenchmarking.org ms, Fewer Is Better TNN 0.3 Target: CPU - Model: MobileNet v2 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 140 280 420 560 700 SE +/- 1.60, N = 3 656.29 MIN: 647.62 / MAX: 668.3 1. (CXX) g++ options: -fopenmp -pthread -fvisibility=hidden -fvisibility=default -O3 -rdynamic -ldl
OpenBenchmarking.org ms, Fewer Is Better TNN 0.3 Target: CPU - Model: DenseNet llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 2K 4K 6K 8K 10K SE +/- 65.94, N = 3 8874.35 MIN: 8585.49 / MAX: 9341.04 1. (CXX) g++ options: -fopenmp -pthread -fvisibility=hidden -fvisibility=default -O3 -rdynamic -ldl
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 20230517 Target: Vulkan GPU - Model: FastestDet llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 5 10 15 20 25 SE +/- 0.05, N = 3 22.62 MIN: 22.2 / MAX: 28.41 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread -pthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: Vulkan GPU - Model: vision_transformer llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 200 400 600 800 1000 SE +/- 0.81, N = 3 1140.71 MIN: 1116.02 / MAX: 1259.95 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread -pthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: Vulkan GPU - Model: regnety_400m llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 8 16 24 32 40 SE +/- 0.03, N = 3 33.20 MIN: 32.32 / MAX: 52.57 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread -pthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: Vulkan GPU - Model: squeezenet_ssd llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 15 30 45 60 75 SE +/- 0.35, N = 3 68.80 MIN: 67.79 / MAX: 146.66 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread -pthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: Vulkan GPU - Model: yolov4-tiny llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 30 60 90 120 150 SE +/- 0.25, N = 3 139.80 MIN: 137.44 / MAX: 150.14 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread -pthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: Vulkan GPU - Model: resnet50 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 30 60 90 120 150 SE +/- 0.11, N = 3 135.98 MIN: 134.41 / MAX: 153.95 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread -pthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: Vulkan GPU - Model: alexnet llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 10 20 30 40 50 SE +/- 0.10, N = 3 42.25 MIN: 41.49 / MAX: 44.6 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread -pthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: Vulkan GPU - Model: resnet18 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 14 28 42 56 70 SE +/- 0.12, N = 3 61.47 MIN: 60.86 / MAX: 79.52 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread -pthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: Vulkan GPU - Model: vgg16 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 70 140 210 280 350 SE +/- 1.47, N = 3 335.23 MIN: 328.93 / MAX: 356.34 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread -pthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: Vulkan GPU - Model: googlenet llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 20 40 60 80 100 SE +/- 0.17, N = 3 75.41 MIN: 73.99 / MAX: 100.71 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread -pthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: Vulkan GPU - Model: blazeface llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 1.197 2.394 3.591 4.788 5.985 SE +/- 0.03, N = 3 5.32 MIN: 5.19 / MAX: 8.52 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread -pthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: Vulkan GPU - Model: efficientnet-b0 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 9 18 27 36 45 SE +/- 0.08, N = 3 39.25 MIN: 38.83 / MAX: 45.93 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread -pthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: Vulkan GPU - Model: mnasnet llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 6 12 18 24 30 SE +/- 0.04, N = 3 25.62 MIN: 25.19 / MAX: 58.61 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread -pthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: Vulkan GPU - Model: shufflenet-v2 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 4 8 12 16 20 SE +/- 0.10, N = 3 16.53 MIN: 16.14 / MAX: 36.47 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread -pthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 5 10 15 20 25 SE +/- 0.09, N = 3 22.45 MIN: 21.93 / MAX: 41.71 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread -pthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 7 14 21 28 35 SE +/- 0.10, N = 3 31.44 MIN: 31.12 / MAX: 34.77 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread -pthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: Vulkan GPU - Model: mobilenet llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 20 40 60 80 100 SE +/- 0.16, N = 3 100.53 MIN: 99.32 / MAX: 121.45 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread -pthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: FastestDet llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 5 10 15 20 25 SE +/- 0.11, N = 3 22.26 MIN: 21.72 / MAX: 40.61 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread -pthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: vision_transformer llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 200 400 600 800 1000 SE +/- 0.72, N = 3 1141.93 MIN: 1114.61 / MAX: 1288.76 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread -pthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: regnety_400m llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 8 16 24 32 40 SE +/- 0.11, N = 3 33.68 MIN: 32.55 / MAX: 40.17 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread -pthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: squeezenet_ssd llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 15 30 45 60 75 SE +/- 0.46, N = 3 68.66 MIN: 67.06 / MAX: 88.53 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread -pthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: yolov4-tiny llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 30 60 90 120 150 SE +/- 0.30, N = 3 139.59 MIN: 136.68 / MAX: 156.49 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread -pthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: resnet50 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 30 60 90 120 150 SE +/- 0.32, N = 3 135.48 MIN: 134.06 / MAX: 143.27 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread -pthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: alexnet llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 10 20 30 40 50 SE +/- 0.13, N = 3 42.29 MIN: 41.47 / MAX: 57.39 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread -pthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: resnet18 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 14 28 42 56 70 SE +/- 0.25, N = 3 60.75 MIN: 59.78 / MAX: 79.65 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread -pthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: vgg16 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 70 140 210 280 350 SE +/- 1.44, N = 3 333.56 MIN: 326.64 / MAX: 373.95 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread -pthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: googlenet llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 20 40 60 80 100 SE +/- 0.12, N = 3 75.15 MIN: 73.47 / MAX: 97.99 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread -pthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: blazeface llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 1.1993 2.3986 3.5979 4.7972 5.9965 SE +/- 0.02, N = 3 5.33 MIN: 5.2 / MAX: 5.68 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread -pthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: efficientnet-b0 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 9 18 27 36 45 SE +/- 0.04, N = 3 39.50 MIN: 39.16 / MAX: 43.83 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread -pthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: mnasnet llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 6 12 18 24 30 SE +/- 0.04, N = 3 25.63 MIN: 25.22 / MAX: 28.14 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread -pthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: shufflenet-v2 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 4 8 12 16 20 SE +/- 0.23, N = 3 16.32 MIN: 15.65 / MAX: 36.76 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread -pthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU-v3-v3 - Model: mobilenet-v3 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 5 10 15 20 25 SE +/- 0.11, N = 3 22.58 MIN: 22.01 / MAX: 65.55 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread -pthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU-v2-v2 - Model: mobilenet-v2 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 7 14 21 28 35 SE +/- 0.13, N = 3 31.61 MIN: 31.19 / MAX: 35.08 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread -pthread
OpenBenchmarking.org ms, Fewer Is Better NCNN 20230517 Target: CPU - Model: mobilenet llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 20 40 60 80 100 SE +/- 0.14, N = 3 100.21 MIN: 99.08 / MAX: 122.54 1. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread -pthread
Mobile Neural Network MNN is the Mobile Neural Network as a highly efficient, lightweight deep learning framework developed by Alibaba. This MNN test profile is building the OpenMP / CPU threaded version for processor benchmarking and not any GPU-accelerated test. MNN does allow making use of AVX-512 extensions. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org ms, Fewer Is Better Mobile Neural Network 2.1 Model: inception-v3 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 40 80 120 160 200 SE +/- 0.98, N = 3 163.10 MIN: 160.43 / MAX: 252.41 1. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl
OpenBenchmarking.org ms, Fewer Is Better Mobile Neural Network 2.1 Model: mobilenet-v1-1.0 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 5 10 15 20 25 SE +/- 0.09, N = 3 20.46 MIN: 20.1 / MAX: 40.6 1. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl
OpenBenchmarking.org ms, Fewer Is Better Mobile Neural Network 2.1 Model: MobileNetV2_224 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 4 8 12 16 20 SE +/- 0.06, N = 3 17.25 MIN: 16.89 / MAX: 37.42 1. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl
OpenBenchmarking.org ms, Fewer Is Better Mobile Neural Network 2.1 Model: SqueezeNetV1.0 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 8 16 24 32 40 SE +/- 0.08, N = 3 32.41 MIN: 31.77 / MAX: 53.11 1. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl
OpenBenchmarking.org ms, Fewer Is Better Mobile Neural Network 2.1 Model: resnet-v2-50 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 30 60 90 120 150 SE +/- 0.22, N = 3 130.58 MIN: 129.32 / MAX: 174.02 1. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl
OpenBenchmarking.org ms, Fewer Is Better Mobile Neural Network 2.1 Model: squeezenetv1.1 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 4 8 12 16 20 SE +/- 0.12, N = 3 17.63 MIN: 17.14 / MAX: 37.87 1. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl
OpenBenchmarking.org ms, Fewer Is Better Mobile Neural Network 2.1 Model: mobilenetV3 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 2 4 6 8 10 SE +/- 0.031, N = 3 6.958 MIN: 6.82 / MAX: 9.38 1. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl
OpenBenchmarking.org ms, Fewer Is Better Mobile Neural Network 2.1 Model: nasnet llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 11 22 33 44 55 SE +/- 0.18, N = 3 46.61 MIN: 45.85 / MAX: 67.49 1. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl
Caffe This is a benchmark of the Caffe deep learning framework and currently supports the AlexNet and Googlenet model and execution on both CPUs and NVIDIA GPUs. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Milli-Seconds, Fewer Is Better Caffe 2020-02-13 Model: GoogleNet - Acceleration: CPU - Iterations: 1000 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 500K 1000K 1500K 2000K 2500K SE +/- 23558.22, N = 3 2318550 1. (CXX) g++ options: -fPIC -O3 -rdynamic -lglog -lgflags -lprotobuf -lpthread -lsz -lz -ldl -lm -llmdb -lopenblas
OpenBenchmarking.org Milli-Seconds, Fewer Is Better Caffe 2020-02-13 Model: GoogleNet - Acceleration: CPU - Iterations: 200 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 100K 200K 300K 400K 500K SE +/- 498.93, N = 3 457100 1. (CXX) g++ options: -fPIC -O3 -rdynamic -lglog -lgflags -lprotobuf -lpthread -lsz -lz -ldl -lm -llmdb -lopenblas
OpenBenchmarking.org Milli-Seconds, Fewer Is Better Caffe 2020-02-13 Model: GoogleNet - Acceleration: CPU - Iterations: 100 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 50K 100K 150K 200K 250K SE +/- 2399.23, N = 3 231503 1. (CXX) g++ options: -fPIC -O3 -rdynamic -lglog -lgflags -lprotobuf -lpthread -lsz -lz -ldl -lm -llmdb -lopenblas
OpenBenchmarking.org Milli-Seconds, Fewer Is Better Caffe 2020-02-13 Model: AlexNet - Acceleration: CPU - Iterations: 1000 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 200K 400K 600K 800K 1000K SE +/- 2982.40, N = 3 1079113 1. (CXX) g++ options: -fPIC -O3 -rdynamic -lglog -lgflags -lprotobuf -lpthread -lsz -lz -ldl -lm -llmdb -lopenblas
OpenBenchmarking.org Milli-Seconds, Fewer Is Better Caffe 2020-02-13 Model: AlexNet - Acceleration: CPU - Iterations: 200 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 50K 100K 150K 200K 250K SE +/- 882.15, N = 3 216588 1. (CXX) g++ options: -fPIC -O3 -rdynamic -lglog -lgflags -lprotobuf -lpthread -lsz -lz -ldl -lm -llmdb -lopenblas
OpenBenchmarking.org Milli-Seconds, Fewer Is Better Caffe 2020-02-13 Model: AlexNet - Acceleration: CPU - Iterations: 100 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 20K 40K 60K 80K 100K SE +/- 551.70, N = 3 107310 1. (CXX) g++ options: -fPIC -O3 -rdynamic -lglog -lgflags -lprotobuf -lpthread -lsz -lz -ldl -lm -llmdb -lopenblas
Neural Magic DeepSparse This is a benchmark of Neural Magic's DeepSparse using its built-in deepsparse.benchmark utility and various models from their SparseZoo (https://sparsezoo.neuralmagic.com/). Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 300 600 900 1200 1500 SE +/- 1.17, N = 3 1354.91
OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.1661 0.3322 0.4983 0.6644 0.8305 SE +/- 0.0006, N = 3 0.7380
OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 600 1200 1800 2400 3000 SE +/- 1.19, N = 3 2788.65
OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.1613 0.3226 0.4839 0.6452 0.8065 SE +/- 0.0003, N = 3 0.7168
OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 30 60 90 120 150 SE +/- 0.53, N = 3 157.31
OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 2 4 6 8 10 SE +/- 0.0214, N = 3 6.3561
OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 70 140 210 280 350 SE +/- 3.55, N = 3 316.59
OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 2 4 6 8 10 SE +/- 0.0711, N = 3 6.3146
OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 200 400 600 800 1000 SE +/- 1.84, N = 3 1041.22
OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.2161 0.4322 0.6483 0.8644 1.0805 SE +/- 0.0017, N = 3 0.9604
OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 500 1000 1500 2000 2500 SE +/- 0.75, N = 3 2218.22
OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.2028 0.4056 0.6084 0.8112 1.014 SE +/- 0.0003, N = 3 0.9012
OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 40 80 120 160 200 SE +/- 0.23, N = 3 181.79
OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 1.2376 2.4752 3.7128 4.9504 6.188 SE +/- 0.0069, N = 3 5.5004
OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 70 140 210 280 350 SE +/- 0.05, N = 3 325.30
OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 2 4 6 8 10 SE +/- 0.0051, N = 3 6.1356
OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Stream llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 50 100 150 200 250 SE +/- 0.34, N = 3 250.61
OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Stream llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.8977 1.7954 2.6931 3.5908 4.4885 SE +/- 0.0054, N = 3 3.9896
OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 120 240 360 480 600 SE +/- 1.23, N = 3 565.80
OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.7937 1.5874 2.3811 3.1748 3.9685 SE +/- 0.0022, N = 3 3.5275
OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 30 60 90 120 150 SE +/- 0.12, N = 3 120.21
OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 2 4 6 8 10 SE +/- 0.0084, N = 3 8.3171
OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 60 120 180 240 300 SE +/- 0.37, N = 3 261.94
OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 2 4 6 8 10 SE +/- 0.0155, N = 3 7.6267
OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Stream llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 200 400 600 800 1000 SE +/- 10.83, N = 9 1089.99
OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Stream llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.2066 0.4132 0.6198 0.8264 1.033 SE +/- 0.0086, N = 9 0.9181
OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 500 1000 1500 2000 2500 SE +/- 11.37, N = 3 2245.61
OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.1998 0.3996 0.5994 0.7992 0.999 SE +/- 0.0040, N = 3 0.8881
OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.8879 1.7758 2.6637 3.5516 4.4395 SE +/- 0.0017, N = 3 3.9464
OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.8105 1.621 2.4315 3.242 4.0525 SE +/- 0.0115, N = 3 3.6022
OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Stream llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 16 32 48 64 80 SE +/- 0.04, N = 3 74.18
OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Stream llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 3 6 9 12 15 SE +/- 0.01, N = 3 13.48
OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 30 60 90 120 150 SE +/- 0.10, N = 3 137.27
OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 4 8 12 16 20 SE +/- 0.01, N = 3 14.56
OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 300 600 900 1200 1500 SE +/- 7.57, N = 3 1351.89
OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.1665 0.333 0.4995 0.666 0.8325 SE +/- 0.0042, N = 3 0.7398
OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 600 1200 1800 2400 3000 SE +/- 3.11, N = 3 2785.40
OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.1606 0.3212 0.4818 0.6424 0.803 SE +/- 0.0019, N = 3 0.7139
TensorFlow This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries if desired for complementary metrics. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.12 Device: CPU - Batch Size: 256 - Model: GoogLeNet llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.6795 1.359 2.0385 2.718 3.3975 SE +/- 0.03, N = 3 3.02
OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.12 Device: CPU - Batch Size: 64 - Model: ResNet-50 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.2295 0.459 0.6885 0.918 1.1475 SE +/- 0.01, N = 3 1.02
OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.12 Device: CPU - Batch Size: 64 - Model: GoogLeNet llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 1.0305 2.061 3.0915 4.122 5.1525 SE +/- 0.00, N = 3 4.58
OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.12 Device: CPU - Batch Size: 32 - Model: ResNet-50 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.3375 0.675 1.0125 1.35 1.6875 SE +/- 0.00, N = 3 1.50
OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.12 Device: CPU - Batch Size: 32 - Model: GoogLeNet llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 1.0193 2.0386 3.0579 4.0772 5.0965 SE +/- 0.00, N = 3 4.53
OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.12 Device: CPU - Batch Size: 16 - Model: ResNet-50 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.3308 0.6616 0.9924 1.3232 1.654 SE +/- 0.01, N = 3 1.47
OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.12 Device: CPU - Batch Size: 16 - Model: GoogLeNet llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 1.008 2.016 3.024 4.032 5.04 SE +/- 0.01, N = 3 4.48
OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.12 Device: CPU - Batch Size: 512 - Model: AlexNet llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 3 6 9 12 15 SE +/- 0.02, N = 3 12.23
OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.12 Device: CPU - Batch Size: 256 - Model: AlexNet llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 3 6 9 12 15 SE +/- 0.01, N = 3 12.02
OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.12 Device: CPU - Batch Size: 64 - Model: AlexNet llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 3 6 9 12 15 SE +/- 0.01, N = 3 10.54
OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.12 Device: CPU - Batch Size: 32 - Model: AlexNet llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 3 6 9 12 15 SE +/- 0.00, N = 3 9.07
OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.12 Device: CPU - Batch Size: 16 - Model: AlexNet llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 2 4 6 8 10 SE +/- 0.03, N = 3 7.02
OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.12 Device: CPU - Batch Size: 64 - Model: VGG-16 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.1013 0.2026 0.3039 0.4052 0.5065 SE +/- 0.00, N = 3 0.45
OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.12 Device: CPU - Batch Size: 32 - Model: VGG-16 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.1193 0.2386 0.3579 0.4772 0.5965 SE +/- 0.00, N = 3 0.53
OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.12 Device: CPU - Batch Size: 16 - Model: VGG-16 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.1373 0.2746 0.4119 0.5492 0.6865 SE +/- 0.00, N = 3 0.61
PyTorch OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_l llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.135 0.27 0.405 0.54 0.675 SE +/- 0.01, N = 3 0.60 MIN: 0.45 / MAX: 0.66
OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_l llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.135 0.27 0.405 0.54 0.675 SE +/- 0.00, N = 3 0.60 MIN: 0.45 / MAX: 0.66
OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.135 0.27 0.405 0.54 0.675 SE +/- 0.01, N = 3 0.60 MIN: 0.44 / MAX: 0.66
OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.1328 0.2656 0.3984 0.5312 0.664 SE +/- 0.01, N = 5 0.59 MIN: 0.45 / MAX: 0.66
OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.1328 0.2656 0.3984 0.5312 0.664 SE +/- 0.00, N = 3 0.59 MIN: 0.45 / MAX: 0.66
OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.2475 0.495 0.7425 0.99 1.2375 SE +/- 0.01, N = 3 1.10 MIN: 0.79 / MAX: 1.16
OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 512 - Model: ResNet-152 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.2093 0.4186 0.6279 0.8372 1.0465 SE +/- 0.00, N = 3 0.93 MIN: 0.56 / MAX: 0.96
OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 256 - Model: ResNet-152 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.207 0.414 0.621 0.828 1.035 SE +/- 0.00, N = 3 0.92 MIN: 0.58 / MAX: 0.96
OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 64 - Model: ResNet-152 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.207 0.414 0.621 0.828 1.035 SE +/- 0.00, N = 3 0.92 MIN: 0.59 / MAX: 0.96
OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 512 - Model: ResNet-50 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.5018 1.0036 1.5054 2.0072 2.509 SE +/- 0.02, N = 3 2.23 MIN: 1.47 / MAX: 2.34
OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 32 - Model: ResNet-152 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.2093 0.4186 0.6279 0.8372 1.0465 SE +/- 0.01, N = 3 0.93 MIN: 0.58 / MAX: 0.96
OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 256 - Model: ResNet-50 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.4883 0.9766 1.4649 1.9532 2.4415 SE +/- 0.02, N = 5 2.17 MIN: 1.45 / MAX: 2.3
OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 16 - Model: ResNet-152 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.2048 0.4096 0.6144 0.8192 1.024 SE +/- 0.01, N = 3 0.91 MIN: 0.58 / MAX: 0.96
OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 64 - Model: ResNet-50 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.4973 0.9946 1.4919 1.9892 2.4865 SE +/- 0.02, N = 3 2.21 MIN: 1.41 / MAX: 2.32
OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 32 - Model: ResNet-50 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.4973 0.9946 1.4919 1.9892 2.4865 SE +/- 0.02, N = 8 2.21 MIN: 1.46 / MAX: 2.33
OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 16 - Model: ResNet-50 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.504 1.008 1.512 2.016 2.52 SE +/- 0.01, N = 3 2.24 MIN: 1.48 / MAX: 2.34
OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 1 - Model: ResNet-152 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.3645 0.729 1.0935 1.458 1.8225 SE +/- 0.01, N = 3 1.62 MIN: 1.04 / MAX: 1.7
OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 1 - Model: ResNet-50 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.8663 1.7326 2.5989 3.4652 4.3315 SE +/- 0.02, N = 3 3.85 MIN: 2.63 / MAX: 4.09
TensorFlow Lite This is a benchmark of the TensorFlow Lite implementation focused on TensorFlow machine learning for mobile, IoT, edge, and other cases. The current Linux support is limited to running on CPUs. This test profile is measuring the average inference time. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Microseconds, Fewer Is Better TensorFlow Lite 2022-05-18 Model: Inception ResNet V2 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 90K 180K 270K 360K 450K SE +/- 439.95, N = 3 419892
RNNoise RNNoise is a recurrent neural network for audio noise reduction developed by Mozilla and Xiph.Org. This test profile is a single-threaded test measuring the time to denoise a sample 26 minute long 16-bit RAW audio file using this recurrent neural network noise suppression library. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Seconds, Fewer Is Better RNNoise 2020-06-28 llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 8 16 24 32 40 SE +/- 0.07, N = 3 36.44 1. (CC) gcc options: -O2 -pedantic -fvisibility=hidden
DeepSpeech Mozilla DeepSpeech is a speech-to-text engine powered by TensorFlow for machine learning and derived from Baidu's Deep Speech research paper. This test profile times the speech-to-text process for a roughly three minute audio recording. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org Seconds, Fewer Is Better DeepSpeech 0.6 Acceleration: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 80 160 240 320 400 SE +/- 0.80, N = 3 378.78
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 3.3 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 5K 10K 15K 20K 25K SE +/- 32.23, N = 3 21318.6 MIN: 21195.4 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.3 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 8K 16K 24K 32K 40K SE +/- 123.68, N = 3 38767.3 MIN: 38319.3 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.3 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 5K 10K 15K 20K 25K SE +/- 10.14, N = 3 21148.2 MIN: 21028.3 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.3 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 8K 16K 24K 32K 40K SE +/- 111.64, N = 3 38464.9 MIN: 38219.3 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.3 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 5K 10K 15K 20K 25K SE +/- 31.33, N = 3 21158.0 MIN: 21017.1 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.3 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 8K 16K 24K 32K 40K SE +/- 25.25, N = 3 38466.3 MIN: 38310.5 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.3 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 14 28 42 56 70 SE +/- 0.80, N = 12 60.62 MIN: 55.57 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.3 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 8 16 24 32 40 SE +/- 0.05, N = 3 32.51 MIN: 31.99 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.3 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 16 32 48 64 80 SE +/- 0.22, N = 3 70.48 MIN: 69.03 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.3 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 12 24 36 48 60 SE +/- 0.06, N = 3 54.13 MIN: 51.76 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.3 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 12 24 36 48 60 SE +/- 0.30, N = 3 53.30 MIN: 50.67 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.3 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 20 40 60 80 100 SE +/- 0.17, N = 3 90.59 MIN: 89.23 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.3 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 3 6 9 12 15 SE +/- 0.04, N = 3 12.00 MIN: 11.72 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.3 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 6 12 18 24 30 SE +/- 0.13, N = 3 23.79 MIN: 23.16 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.3 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 10 20 30 40 50 SE +/- 0.10, N = 3 45.54 MIN: 44.65 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.3 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 10 20 30 40 50 SE +/- 0.27, N = 3 42.23 MIN: 40.72 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -lpthread -ldl
OpenCV This is a benchmark of the OpenCV (Computer Vision) library's built-in performance tests. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org ms, Fewer Is Better OpenCV 4.7 Test: DNN - Deep Neural Network llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 20K 40K 60K 80K 100K SE +/- 2616.66, N = 15 106960 1. (CXX) g++ options: -fsigned-char -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections -msse -msse2 -msse3 -fvisibility=hidden -O3 -ldl -lm -lpthread -lrt
Scikit-Learn Scikit-learn is a Python module for machine learning built on NumPy, SciPy, and is BSD-licensed. Learn more via the OpenBenchmarking.org test page.
Benchmark: Plot Non-Negative Matrix Factorization
llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: KeyError:
Benchmark: Isotonic / Perturbed Logarithm
llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status.
Benchmark: RCV1 Logreg Convergencet
llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: IndexError: list index out of range
Benchmark: Isotonic / Pathological
llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status.
Benchmark: Plot Parallel Pairwise
llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: numpy.core._exceptions.MemoryError: Unable to allocate 74.5 GiB for an array with shape (100000, 100000) and data type float64
Benchmark: Isotonic / Logistic
llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status.
Benchmark: Plot Fast KMeans
llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status.
Benchmark: Isolation Forest
llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status.
Benchmark: SGDOneClassSVM
llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status.
Benchmark: Glmnet
llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ModuleNotFoundError: No module named 'glmnet.elastic_net'
Mlpack Benchmark Mlpack benchmark scripts for machine learning libraries Learn more via the OpenBenchmarking.org test page.
Benchmark: scikit_linearridgeregression
llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C: The test run did not produce a result. The test run did not produce a result. The test run did not produce a result.
Benchmark: scikit_qda
llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C: The test run did not produce a result. The test run did not produce a result. The test run did not produce a result.
AI Benchmark Alpha AI Benchmark Alpha is a Python library for evaluating artificial intelligence (AI) performance on diverse hardware platforms and relies upon the TensorFlow machine learning library. Learn more via the OpenBenchmarking.org test page.
llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C: The test quit with a non-zero exit status. E: AttributeError: module 'numpy' has no attribute 'typeDict'
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.
Model: yolov4 - Device: CPU - Executor: Standard
llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: onnxruntime/onnxruntime/test/onnx/onnx_model_info.cc:45 void OnnxModelInfo::InitOnnxModelInfo(const PATH_CHAR_TYPE*) open file "yolov4/yolov4.onnx" failed: No such file or directory
Model: yolov4 - Device: CPU - Executor: Parallel
llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: onnxruntime/onnxruntime/test/onnx/onnx_model_info.cc:45 void OnnxModelInfo::InitOnnxModelInfo(const PATH_CHAR_TYPE*) open file "yolov4/yolov4.onnx" failed: No such file or directory
ECP-CANDLE The CANDLE benchmark codes implement deep learning architectures relevant to problems in cancer. These architectures address problems at different biological scales, specifically problems at the molecular, cellular and population scales. Learn more via the OpenBenchmarking.org test page.
Benchmark: P3B2
llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C: The test quit with a non-zero exit status. E: ImportError: initialization failed
Benchmark: P3B1
llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C: The test quit with a non-zero exit status. E: ImportError: initialization failed
Benchmark: P1B2
llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C: The test quit with a non-zero exit status. E: ImportError: initialization failed
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 2023.2.dev Model: Handwritten English Recognition FP16 - Device: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 130 260 390 520 650 SE +/- 12.86, N = 15 593.05 MIN: 368.67 / MAX: 676.18 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
OpenBenchmarking.org FPS, More Is Better OpenVINO 2023.2.dev Model: Handwritten English Recognition FP16 - Device: CPU llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C 0.765 1.53 2.295 3.06 3.825 SE +/- 0.08, N = 15 3.40 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared -ldl
spaCy The spaCy library is an open-source solution for advanced neural language processing (NLP). The spaCy library leverages Python and is a leading neural language processing solution. This test profile times the spaCy CPU performance with various models. Learn more via the OpenBenchmarking.org test page.
llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: TypeError: issubclass() arg 1 must be a class
TensorFlow This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries if desired for complementary metrics. Learn more via the OpenBenchmarking.org test page.
Device: CPU - Batch Size: 512 - Model: ResNet-50
llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status.
Device: CPU - Batch Size: 512 - Model: GoogLeNet
llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status.
Device: CPU - Batch Size: 256 - Model: ResNet-50
llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status.
Device: CPU - Batch Size: 512 - Model: VGG-16
llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: Fatal Python error: Aborted
Device: CPU - Batch Size: 256 - Model: VGG-16
llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: Fatal Python error: Aborted
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.
Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU
llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C: The test run did not produce a result. The test run did not produce a result. The test run did not produce a result.
Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU
llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C: The test run did not produce a result. The test run did not produce a result. The test run did not produce a result.
Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU
llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C: The test run did not produce a result. The test run did not produce a result. The test run did not produce a result.
Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU
llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C: The test run did not produce a result. The test run did not produce a result. The test run did not produce a result.
Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU
llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C: The test run did not produce a result. The test run did not produce a result. The test run did not produce a result.
llvmpipe - AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C Processor: AMD A8-9600 RADEON R7 10 COMPUTE CORES 4C+6G @ 3.10GHz (2 Cores / 4 Threads), Motherboard: ASRock A320M-HDV R4.0 (P2.00 BIOS), Chipset: AMD 15h, Memory: 3584MB, Disk: 1000GB Western Digital WDS100T2B0A, Graphics: llvmpipe, Audio: AMD Kabini HDMI/DP, Network: Realtek RTL8111/8168/8411
OS: Ubuntu 20.04, Kernel: 5.15.0-89-generic (x86_64), Desktop: GNOME Shell 3.36.9, Display Server: X Server 1.20.13, OpenGL: 4.5 Mesa 21.2.6 (LLVM 12.0.0 256 bits), Vulkan: 1.1.182, Compiler: GCC 9.4.0, File-System: ext4, Screen Resolution: 1368x768
Kernel Notes: Transparent Huge Pages: madviseCompiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++,gm2 --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-9-9QDOt0/gcc-9-9.4.0/debian/tmp-nvptx/usr,hsa --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 ondemand (Boost: Enabled) - CPU Microcode: 0x600611aPython Notes: Python 3.8.10Security Notes: gather_data_sampling: Not affected + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Mitigation of untrained return thunk; SMT vulnerable + spec_rstack_overflow: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Retpolines IBPB: conditional STIBP: disabled RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected
Testing initiated at 12 December 2023 15:12 by user hertz.