Machine Learning

The machine learning test suite helps to benchmark a system for the popular pattern recognition and computational learning algorithms. Mainly different machine learning / deep learning benchmarks.

See how your system performs with this suite using the Phoronix Test Suite. It's as easy as running the phoronix-test-suite benchmark machine-learning command..

Tests In This Suite

  • Mobile Neural Network
  • NCNN
        Target: CPU
  • NCNN
        Target: Vulkan GPU
  • TNN
        Target: CPU - Model: MobileNet v2
  • TNN
        Target: CPU - Model: SqueezeNet v1.1
  • OpenCV
        Test: DNN - Deep Neural Network
  • Caffe
        Model: AlexNet - Acceleration: CPU - Iterations: 100
  • Caffe
        Model: AlexNet - Acceleration: CPU - Iterations: 200
  • Caffe
        Model: AlexNet - Acceleration: CPU - Iterations: 1000
  • Caffe
        Model: GoogleNet - Acceleration: CPU - Iterations: 100
  • Caffe
        Model: GoogleNet - Acceleration: CPU - Iterations: 200
  • Caffe
        Model: GoogleNet - Acceleration: CPU - Iterations: 1000
  • SHOC Scalable HeterOgeneous Computing
  • R Benchmark
  • Numpy Benchmark
  • AI Benchmark Alpha
  • DeepSpeech
        Acceleration: CPU
  • RNNoise
  • Scikit-Learn
  • Mlpack Benchmark
        Benchmark: scikit_svm
  • Mlpack Benchmark
        Benchmark: scikit_linearridgeregression
  • Mlpack Benchmark
        Benchmark: scikit_qda
  • Mlpack Benchmark
        Benchmark: scikit_ica
  • Numenta Anomaly Benchmark
        Detector: Bayesian Changepoint
  • Numenta Anomaly Benchmark
        Detector: Windowed Gaussian
  • Numenta Anomaly Benchmark
        Detector: Relative Entropy
  • Numenta Anomaly Benchmark
        Detector: Earthgecko Skyline
  • Numenta Anomaly Benchmark
        Detector: EXPoSE
  • Tensorflow
        Build: Cifar10
  • TensorFlow Lite
        Model: Mobilenet Float
  • TensorFlow Lite
        Model: Mobilenet Quant
  • TensorFlow Lite
        Model: NASNet Mobile
  • TensorFlow Lite
        Model: SqueezeNet
  • TensorFlow Lite
        Model: Inception ResNet V2
  • TensorFlow Lite
        Model: Inception V4
  • Numenta Anomaly Benchmark
        Detector: Bayesian Changepoint
  • Numenta Anomaly Benchmark
        Detector: Windowed Gaussian
  • Numenta Anomaly Benchmark
        Detector: Relative Entropy
  • Numenta Anomaly Benchmark
        Detector: Earthgecko Skyline
  • Numenta Anomaly Benchmark
        Detector: EXPoSE
  • oneDNN
        Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU
  • oneDNN
        Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU
  • oneDNN
        Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU
  • oneDNN
        Harness: Deconvolution Batch deconv_1d - Data Type: f32 - Engine: CPU
  • oneDNN
        Harness: Deconvolution Batch deconv_1d - Data Type: u8s8f32 - Engine: CPU
  • oneDNN
        Harness: Deconvolution Batch deconv_1d - Data Type: bf16bf16bf16 - Engine: CPU
  • oneDNN
        Harness: Deconvolution Batch deconv_3d - Data Type: f32 - Engine: CPU
  • oneDNN
        Harness: Deconvolution Batch deconv_3d - Data Type: u8s8f32 - Engine: CPU
  • oneDNN
        Harness: Deconvolution Batch deconv_3d - Data Type: bf16bf16bf16 - Engine: CPU
  • oneDNN
        Harness: IP Batch 1D - Data Type: f32 - Engine: CPU
  • oneDNN
        Harness: IP Batch 1D - Data Type: u8s8f32 - Engine: CPU
  • oneDNN
        Harness: IP Batch 1D - Data Type: bf16bf16bf16 - Engine: CPU
  • oneDNN
        Harness: IP Batch All - Data Type: f32 - Engine: CPU
  • oneDNN
        Harness: IP Batch All - Data Type: u8s8f32 - Engine: CPU
  • oneDNN
        Harness: IP Batch All - Data Type: bf16bf16bf16 - Engine: CPU
  • oneDNN
        Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU
  • oneDNN
        Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU
  • oneDNN
        Harness: Matrix Multiply Batch Shapes Transformer - Data Type: bf16bf16bf16 - Engine: CPU
  • oneDNN
        Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU
  • oneDNN
        Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU
  • oneDNN
        Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU
  • oneDNN
        Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU
  • oneDNN
        Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU
  • oneDNN
        Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU
  • OpenVINO
        Model: Face Detection 0106 FP16 - Device: CPU
  • OpenVINO
        Model: Face Detection 0106 FP16 - Device: Intel GPU
  • OpenVINO
        Model: Face Detection 0106 FP32 - Device: CPU
  • OpenVINO
        Model: Face Detection 0106 FP32 - Device: Intel GPU
  • OpenVINO
        Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU
  • OpenVINO
        Model: Age Gender Recognition Retail 0013 FP16 - Device: Intel GPU
  • OpenVINO
        Model: Age Gender Recognition Retail 0013 FP32 - Device: CPU
  • OpenVINO
        Model: Age Gender Recognition Retail 0013 FP32 - Device: Intel GPU
  • OpenVINO
        Model: Person Detection 0106 FP16 - Device: CPU
  • OpenVINO
        Model: Person Detection 0106 FP16 - Device: Intel GPU
  • OpenVINO
        Model: Person Detection 0106 FP32 - Device: CPU
  • OpenVINO
        Model: Person Detection 0106 FP32 - Device: Intel GPU
  • PlaidML
        FP16: No - Mode: Inference - Network: ResNet 50 - Device: CPU
  • PlaidML
        FP16: No - Mode: Inference - Network: VGG16 - Device: CPU
  • LeelaChessZero
        Backend: BLAS

Revision History

pts/machine-learning-1.3.1     08 Oct 2020 09:23 EDT
Add OpenVINO to suite.

pts/machine-learning-1.3.0     04 Oct 2020 13:02 EDT
Add OpenCV, TNN, Caffe, and other updates.

pts/machine-learning-1.2.9     19 Sep 2020 12:54 EDT
Add NCNN to test suite.

pts/machine-learning-1.2.8     17 Sep 2020 20:58 EDT
Add Alibaba Mobile Neural Network (mnn) test profile.

pts/machine-learning-1.2.7     23 Aug 2020 14:17 EDT
Add tensorflow-lite test profile.

pts/machine-learning-1.2.6     08 Jul 2020 14:28 EDT
Add ai-benchmark test profile to machine learning test suite.

pts/machine-learning-1.2.5     17 Jun 2020 16:35 EDT
Use pts/onednn rather than pts/mkl-dnn due to rename.

pts/machine-learning-1.2.4     28 May 2020 15:51 EDT
Add additional tests.

pts/machine-learning-1.2.3     08 Apr 2020 16:21 EDT
Add tensorflow.

pts/machine-learning-1.2.2     08 Apr 2020 14:00 EDT
Add numenta-nab and deepspeech to test suite.

pts/machine-learning-1.2.10     22 Sep 2020 18:11 EDT
Add OpenCV DNN test to machine-learning suite.

pts/machine-learning-1.2.1     24 Feb 2020 09:14 EST
Update machine-learning test suite with batch mode for mlpack given its new options just added.

pts/machine-learning-1.2.0     16 Feb 2020 19:07 EST
Add more tests.

pts/machine-learning-1.1.0     10 May 2019 15:47 EDT
Update tests.

pts/machine-learning-1.0.0     01 Aug 2016 16:30 EDT
Initial commit


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