ml_test_results1
wsl testing on Ubuntu 20.04 via the Phoronix Test Suite.
rtx3080_12900K
Processor: Intel Core i9-12900K (12 Cores / 24 Threads), Memory: 16GB, Disk: 4 x 275GB Virtual Disk, Graphics: NVIDIA GeForce RTX 3080 10GB
OS: Ubuntu 20.04, Kernel: 5.10.16.3-microsoft-standard-WSL2 (x86_64), Display Server: Wayland, Vulkan: 1.1.182, Compiler: GCC 9.4.0, File-System: ext4, System Layer: wsl
Kernel Notes: Transparent Huge Pages: always
Compiler 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-Av3uEd/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 -v
Processor Notes: CPU Microcode: 0xffffffff
Python Notes: Python 3.9.12
Security Notes: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: 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 Enhanced IBRS IBPB: conditional RSB filling + srbds: Not affected + tsx_async_abort: Not affected
PlaidML
This test profile uses PlaidML deep learning framework developed by Intel for offering up various benchmarks. Learn more via the OpenBenchmarking.org test page.
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.
Model: Face Detection 0106 FP16 - Device: CPU
rtx3080_12900K: 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: ./openvino: line 2: ./openvino-github-2021/bin/intel64/Release/benchmark_app: No such file or directory
Model: Face Detection 0106 FP32 - Device: CPU
rtx3080_12900K: 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: ./openvino: line 2: ./openvino-github-2021/bin/intel64/Release/benchmark_app: No such file or directory
Model: Person Detection 0106 FP16 - Device: CPU
rtx3080_12900K: 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: ./openvino: line 2: ./openvino-github-2021/bin/intel64/Release/benchmark_app: No such file or directory
Model: Person Detection 0106 FP32 - Device: CPU
rtx3080_12900K: 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: ./openvino: line 2: ./openvino-github-2021/bin/intel64/Release/benchmark_app: No such file or directory
Model: Face Detection 0106 FP16 - Device: Intel GPU
rtx3080_12900K: 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: ./openvino: line 2: ./openvino-github-2021/bin/intel64/Release/benchmark_app: No such file or directory
Model: Face Detection 0106 FP32 - Device: Intel GPU
rtx3080_12900K: 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: ./openvino: line 2: ./openvino-github-2021/bin/intel64/Release/benchmark_app: No such file or directory
Model: Person Detection 0106 FP16 - Device: Intel GPU
rtx3080_12900K: 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: ./openvino: line 2: ./openvino-github-2021/bin/intel64/Release/benchmark_app: No such file or directory
Model: Person Detection 0106 FP32 - Device: Intel GPU
rtx3080_12900K: 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: ./openvino: line 2: ./openvino-github-2021/bin/intel64/Release/benchmark_app: No such file or directory
Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU
rtx3080_12900K: 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: ./openvino: line 2: ./openvino-github-2021/bin/intel64/Release/benchmark_app: No such file or directory
Model: Age Gender Recognition Retail 0013 FP32 - Device: CPU
rtx3080_12900K: 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: ./openvino: line 2: ./openvino-github-2021/bin/intel64/Release/benchmark_app: No such file or directory
Model: Age Gender Recognition Retail 0013 FP16 - Device: Intel GPU
rtx3080_12900K: 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: ./openvino: line 2: ./openvino-github-2021/bin/intel64/Release/benchmark_app: No such file or directory
Model: Age Gender Recognition Retail 0013 FP32 - Device: Intel GPU
rtx3080_12900K: 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: ./openvino: line 2: ./openvino-github-2021/bin/intel64/Release/benchmark_app: No such file or directory
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 Zoo. Learn more via the OpenBenchmarking.org test page.
Model: GPT-2 - Device: CPU - Executor: Parallel
rtx3080_12900K: 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: ./onnx: line 2: ./onnxruntime/build/Linux/Release/onnxruntime_perf_test: No such file or directory
Model: GPT-2 - Device: CPU - Executor: Standard
rtx3080_12900K: 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: ./onnx: line 2: ./onnxruntime/build/Linux/Release/onnxruntime_perf_test: No such file or directory
Model: yolov4 - Device: CPU - Executor: Parallel
rtx3080_12900K: 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: ./onnx: line 2: ./onnxruntime/build/Linux/Release/onnxruntime_perf_test: No such file or directory
Model: yolov4 - Device: CPU - Executor: Standard
rtx3080_12900K: 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: ./onnx: line 2: ./onnxruntime/build/Linux/Release/onnxruntime_perf_test: No such file or directory
Model: bertsquad-12 - Device: CPU - Executor: Parallel
rtx3080_12900K: 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: ./onnx: line 2: ./onnxruntime/build/Linux/Release/onnxruntime_perf_test: No such file or directory
Model: bertsquad-12 - Device: CPU - Executor: Standard
rtx3080_12900K: 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: ./onnx: line 2: ./onnxruntime/build/Linux/Release/onnxruntime_perf_test: No such file or directory
Model: fcn-resnet101-11 - Device: CPU - Executor: Parallel
rtx3080_12900K: 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: ./onnx: line 2: ./onnxruntime/build/Linux/Release/onnxruntime_perf_test: No such file or directory
Model: fcn-resnet101-11 - Device: CPU - Executor: Standard
rtx3080_12900K: 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: ./onnx: line 2: ./onnxruntime/build/Linux/Release/onnxruntime_perf_test: No such file or directory
Model: ArcFace ResNet-100 - Device: CPU - Executor: Parallel
rtx3080_12900K: 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: ./onnx: line 2: ./onnxruntime/build/Linux/Release/onnxruntime_perf_test: No such file or directory
Model: ArcFace ResNet-100 - Device: CPU - Executor: Standard
rtx3080_12900K: 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: ./onnx: line 2: ./onnxruntime/build/Linux/Release/onnxruntime_perf_test: No such file or directory
Model: super-resolution-10 - Device: CPU - Executor: Parallel
rtx3080_12900K: 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: ./onnx: line 2: ./onnxruntime/build/Linux/Release/onnxruntime_perf_test: No such file or directory
Model: super-resolution-10 - Device: CPU - Executor: Standard
rtx3080_12900K: 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: ./onnx: line 2: ./onnxruntime/build/Linux/Release/onnxruntime_perf_test: No such file or directory
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.
Numpy Benchmark
This is a test to obtain the general Numpy performance. Learn more via the OpenBenchmarking.org test page.
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.
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.
Model: AlexNet - Acceleration: CPU - Iterations: 100
rtx3080_12900K: 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: ./caffe: 3: ./tools/caffe: not found
Model: AlexNet - Acceleration: CPU - Iterations: 200
rtx3080_12900K: 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: ./caffe: 3: ./tools/caffe: not found
Model: AlexNet - Acceleration: CPU - Iterations: 1000
rtx3080_12900K: 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: ./caffe: 3: ./tools/caffe: not found
Model: GoogleNet - Acceleration: CPU - Iterations: 100
rtx3080_12900K: 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: ./caffe: 3: ./tools/caffe: not found
Model: GoogleNet - Acceleration: CPU - Iterations: 200
rtx3080_12900K: 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: ./caffe: 3: ./tools/caffe: not found
Model: GoogleNet - Acceleration: CPU - Iterations: 1000
rtx3080_12900K: 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: ./caffe: 3: ./tools/caffe: not found
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 Intel oneAPI. Learn more via the OpenBenchmarking.org test page.
Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU
rtx3080_12900K: 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
rtx3080_12900K: 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
rtx3080_12900K: 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
rtx3080_12900K: 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_3d - Data Type: bf16bf16bf16 - Engine: CPU
rtx3080_12900K: 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: Matrix Multiply Batch Shapes Transformer - Data Type: bf16bf16bf16 - Engine: CPU
rtx3080_12900K: The test run did not produce a result. The test run did not produce a result. The test run did not produce a result.
Mobile Neural Network
MNN is the Mobile Neural Network as a highly efficient, lightweight deep learning framework developed by Alibaba. Learn more via the OpenBenchmarking.org test page.
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.
TNN
TNN is an open-source deep learning reasoning framework developed by Tencent. Learn more via the OpenBenchmarking.org test page.
OpenCV
This is a benchmark of the OpenCV (Computer Vision) library's built-in performance tests. Learn more via the OpenBenchmarking.org test page.
Test: DNN - Deep Neural Network
rtx3080_12900K: 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: ./opencv: 4: ./opencv_perf_dnn: not found
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.
R Benchmark
This test is a quick-running survey of general R performance Learn more via the OpenBenchmarking.org test page.
rtx3080_12900K: 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: ERROR: Rscript is not found on the system!
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.
Tensorflow
This is a benchmark of the Tensorflow deep learning framework using the CIFAR10 data set. Learn more via the OpenBenchmarking.org test page.
Build: Cifar10
rtx3080_12900K: 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: AttributeError: module 'tensorflow' has no attribute 'app'
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.
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 timeseries 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.
Mlpack Benchmark
Mlpack benchmark scripts for machine learning libraries Learn more via the OpenBenchmarking.org test page.
Benchmark: scikit_ica
rtx3080_12900K: 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: load_all() missing 1 required positional argument: 'Loader'
Benchmark: scikit_qda
rtx3080_12900K: 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: load_all() missing 1 required positional argument: 'Loader'
Benchmark: scikit_svm
rtx3080_12900K: 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: load_all() missing 1 required positional argument: 'Loader'
Benchmark: scikit_linearridgeregression
rtx3080_12900K: 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: load_all() missing 1 required positional argument: 'Loader'
Scikit-Learn
Scikit-learn is a Python module for machine learning Learn more via the OpenBenchmarking.org test page.
rtx3080_12900K
Processor: Intel Core i9-12900K (12 Cores / 24 Threads), Memory: 16GB, Disk: 4 x 275GB Virtual Disk, Graphics: NVIDIA GeForce RTX 3080 10GB
OS: Ubuntu 20.04, Kernel: 5.10.16.3-microsoft-standard-WSL2 (x86_64), Display Server: Wayland, Vulkan: 1.1.182, Compiler: GCC 9.4.0, File-System: ext4, System Layer: wsl
Kernel Notes: Transparent Huge Pages: always
Compiler 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-Av3uEd/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 -v
Processor Notes: CPU Microcode: 0xffffffff
Python Notes: Python 3.9.12
Security Notes: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: 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 Enhanced IBRS IBPB: conditional RSB filling + srbds: Not affected + tsx_async_abort: Not affected
Testing initiated at 4 August 2022 01:36 by user allanlago.