MBP M1 Max Machine Learning, sys76-kudu-ML

Apple M1 Max testing with a Apple MacBook Pro and Apple M1 Max on macOS 12.1 via the Phoronix Test Suite.

sys76-kudu-ML: AMD Ryzen 9 5900HX testing with a System76 Kudu (1.07.09RSA1 BIOS) and AMD Cezanne on Pop 21.10 via the Phoronix Test Suite.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2202161-NE-MBPM1MAXM40
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BLAS (Basic Linear Algebra Sub-Routine) Tests 2 Tests
CPU Massive 7 Tests
Creator Workloads 4 Tests
HPC - High Performance Computing 20 Tests
Machine Learning 20 Tests
Multi-Core 2 Tests
NVIDIA GPU Compute 4 Tests
Intel oneAPI 2 Tests
Python 3 Tests
Server CPU Tests 3 Tests
Single-Threaded 3 Tests
Speech 2 Tests
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  Test
  Duration
MBP M1 Max Machine Learning
February 16 2022
  6 Hours, 21 Minutes
ML Tests
February 15 2022
  7 Hours, 15 Minutes
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  6 Hours, 48 Minutes
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MBP M1 Max Machine Learning, sys76-kudu-ML Apple M1 Max testing with a Apple MacBook Pro and Apple M1 Max on macOS 12.1 via the Phoronix Test Suite. sys76-kudu-ML: AMD Ryzen 9 5900HX testing with a System76 Kudu (1.07.09RSA1 BIOS) and AMD Cezanne on Pop 21.10 via the Phoronix Test Suite. MBP M1 Max Machine Learning: Processor: Apple M1 Max (10 Cores), Motherboard: Apple MacBook Pro, Memory: 64GB, Disk: 1859GB, Graphics: Apple M1 Max, Monitor: Color LCD OS: macOS 12.1, Kernel: 21.2.0 (arm64), OpenCL: OpenCL 1.2 (Nov 13 2021 00:45:09), Compiler: GCC 13.0.0 + Clang 13.0.0, File-System: APFS, Screen Resolution: 3456x2234 ML Tests: Processor: AMD Ryzen 9 5900HX @ 3.30GHz (8 Cores / 16 Threads), Motherboard: System76 Kudu (1.07.09RSA1 BIOS), Chipset: AMD Renoir/Cezanne, Memory: 16GB, Disk: Samsung SSD 970 EVO Plus 500GB, Graphics: AMD Cezanne (2100/400MHz), Audio: AMD Renoir Radeon HD Audio, Network: Realtek RTL8125 2.5GbE + Intel Wi-Fi 6 AX200 OS: Pop 21.10, Kernel: 5.15.15-76051515-generic (x86_64), Desktop: GNOME Shell 40.5, Display Server: X Server 1.20.13, OpenGL: 4.6 Mesa 21.2.2 (LLVM 12.0.1), Vulkan: 1.2.182, Compiler: GCC 11.2.0, File-System: ext4, Screen Resolution: 1920x1080 NCNN 20210720 Target: Vulkan GPU - Model: alexnet ms < Lower Is Better MBP M1 Max Machine Learning . 29.89 |========================================== ML Tests .................... 6.32 |========= Mobile Neural Network 1.2 Model: MobileNetV2_224 ms < Lower Is Better MBP M1 Max Machine Learning . 10.677 |========================================= ML Tests .................... 2.387 |========= NCNN 20210720 Target: Vulkan GPU - Model: resnet50 ms < Lower Is Better MBP M1 Max Machine Learning . 43.08 |========================================== ML Tests .................... 13.12 |============= NCNN 20210720 Target: Vulkan GPU - Model: googlenet ms < Lower Is Better MBP M1 Max Machine Learning . 24.90 |========================================== ML Tests .................... 8.73 |=============== NCNN 20210720 Target: Vulkan GPU - Model: resnet18 ms < Lower Is Better MBP M1 Max Machine Learning . 16.80 |========================================== ML Tests .................... 6.09 |=============== NCNN 20210720 Target: CPU - Model: alexnet ms < Lower Is Better MBP M1 Max Machine Learning . 29.93 |========================================== ML Tests .................... 14.55 |==================== NCNN 20210720 Target: Vulkan GPU - Model: mobilenet ms < Lower Is Better MBP M1 Max Machine Learning . 20.30 |========================================== ML Tests .................... 10.27 |===================== NCNN 20210720 Target: CPU - Model: googlenet ms < Lower Is Better MBP M1 Max Machine Learning . 24.96 |========================================== ML Tests .................... 13.74 |======================= NCNN 20210720 Target: CPU - Model: resnet50 ms < Lower Is Better MBP M1 Max Machine Learning . 43.16 |========================================== ML Tests .................... 25.17 |======================== NCNN 20210720 Target: CPU - Model: efficientnet-b0 ms < Lower Is Better MBP M1 Max Machine Learning . 8.69 |=========================================== ML Tests .................... 5.22 |========================== NCNN 20210720 Target: CPU - Model: mnasnet ms < Lower Is Better MBP M1 Max Machine Learning . 5.40 |=========================================== ML Tests .................... 3.25 |========================== NCNN 20210720 Target: Vulkan GPU - Model: yolov4-tiny ms < Lower Is Better MBP M1 Max Machine Learning . 30.33 |========================================== ML Tests .................... 18.82 |========================== NCNN 20210720 Target: Vulkan GPU - Model: vgg16 ms < Lower Is Better MBP M1 Max Machine Learning . 70.89 |========================================== ML Tests .................... 43.99 |========================== NCNN 20210720 Target: Vulkan GPU - Model: mnasnet ms < Lower Is Better MBP M1 Max Machine Learning . 5.37 |=========================================== ML Tests .................... 3.89 |=============================== NCNN 20210720 Target: CPU - Model: blazeface ms < Lower Is Better MBP M1 Max Machine Learning . 1.65 |=========================================== ML Tests .................... 1.20 |=============================== NCNN 20210720 Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2 ms < Lower Is Better MBP M1 Max Machine Learning . 5.30 |=========================================== ML Tests .................... 3.88 |=============================== NCNN 20210720 Target: Vulkan GPU - Model: regnety_400m ms < Lower Is Better MBP M1 Max Machine Learning . 7.19 |=========================================== ML Tests .................... 5.28 |================================ NCNN 20210720 Target: Vulkan GPU - Model: squeezenet_ssd ms < Lower Is Better MBP M1 Max Machine Learning . 20.55 |========================================== ML Tests .................... 15.36 |=============================== NCNN 20210720 Target: CPU-v2-v2 - Model: mobilenet-v2 ms < Lower Is Better MBP M1 Max Machine Learning . 5.33 |=========================================== ML Tests .................... 3.99 |================================ NCNN 20210720 Target: CPU-v3-v3 - Model: mobilenet-v3 ms < Lower Is Better MBP M1 Max Machine Learning . 4.36 |=========================================== ML Tests .................... 3.41 |================================== NCNN 20210720 Target: CPU - Model: mobilenet ms < Lower Is Better MBP M1 Max Machine Learning . 20.32 |========================================== ML Tests .................... 15.95 |================================= NCNN 20210720 Target: CPU - Model: shufflenet-v2 ms < Lower Is Better MBP M1 Max Machine Learning . 3.47 |=========================================== ML Tests .................... 2.75 |================================== NCNN 20210720 Target: Vulkan GPU - Model: blazeface ms < Lower Is Better MBP M1 Max Machine Learning . 1.64 |=========================================== ML Tests .................... 1.35 |=================================== NCNN 20210720 Target: CPU - Model: yolov4-tiny ms < Lower Is Better MBP M1 Max Machine Learning . 30.24 |========================================== ML Tests .................... 24.97 |=================================== NCNN 20210720 Target: Vulkan GPU - Model: efficientnet-b0 ms < Lower Is Better MBP M1 Max Machine Learning . 8.71 |==================================== ML Tests .................... 10.07 |========================================== NCNN 20210720 Target: Vulkan GPU - Model: shufflenet-v2 ms < Lower Is Better MBP M1 Max Machine Learning . 3.46 |=========================================== ML Tests .................... 3.02 |====================================== NCNN 20210720 Target: CPU - Model: squeezenet_ssd ms < Lower Is Better MBP M1 Max Machine Learning . 20.53 |========================================== ML Tests .................... 18.56 |====================================== NCNN 20210720 Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3 ms < Lower Is Better MBP M1 Max Machine Learning . 4.35 |======================================== ML Tests .................... 4.69 |=========================================== NCNN 20210720 Target: CPU - Model: resnet18 ms < Lower Is Better MBP M1 Max Machine Learning . 16.82 |========================================== ML Tests .................... 15.78 |======================================= NCNN 20210720 Target: CPU - Model: regnety_400m ms < Lower Is Better MBP M1 Max Machine Learning . 7.18 |=========================================== ML Tests .................... 6.90 |========================================= NCNN 20210720 Target: CPU - Model: vgg16 ms < Lower Is Better MBP M1 Max Machine Learning . 71.01 |========================================= ML Tests .................... 71.97 |========================================== Mlpack Benchmark Benchmark: scikit_linearridgeregression Seconds < Lower Is Better ML Tests . 2.10 |============================================================== Mlpack Benchmark Benchmark: scikit_svm Seconds < Lower Is Better ML Tests . 17.60 |============================================================= Mlpack Benchmark Benchmark: scikit_qda Seconds < Lower Is Better ML Tests . 65.69 |============================================================= Mlpack Benchmark Benchmark: scikit_ica Seconds < Lower Is Better ML Tests . 48.40 |============================================================= ECP-CANDLE 0.4 Benchmark: P3B2 Seconds < Lower Is Better ML Tests . 730.74 |============================================================ ECP-CANDLE 0.4 Benchmark: P3B1 Seconds < Lower Is Better ML Tests . 1463.72 |=========================================================== ECP-CANDLE 0.4 Benchmark: P1B2 Seconds < Lower Is Better ML Tests . 37.51 |============================================================= PlaidML FP16: No - Mode: Inference - Network: ResNet 50 - Device: CPU FPS > Higher Is Better ML Tests . 6.88 |============================================================== PlaidML FP16: No - Mode: Inference - Network: VGG16 - Device: CPU FPS > Higher Is Better ML Tests . 12.47 |============================================================= TNN 0.3 Target: CPU - Model: SqueezeNet v1.1 ms < Lower Is Better ML Tests . 222.33 |============================================================ TNN 0.3 Target: CPU - Model: SqueezeNet v2 ms < Lower Is Better ML Tests . 55.43 |============================================================= TNN 0.3 Target: CPU - Model: MobileNet v2 ms < Lower Is Better ML Tests . 249.48 |============================================================ TNN 0.3 Target: CPU - Model: DenseNet ms < Lower Is Better ML Tests . 2736.17 |=========================================================== Caffe 2020-02-13 Model: GoogleNet - Acceleration: CPU - Iterations: 1000 Milli-Seconds < Lower Is Better ML Tests . 868758 |============================================================ Caffe 2020-02-13 Model: GoogleNet - Acceleration: CPU - Iterations: 200 Milli-Seconds < Lower Is Better ML Tests . 173671 |============================================================ Caffe 2020-02-13 Model: GoogleNet - Acceleration: CPU - Iterations: 100 Milli-Seconds < Lower Is Better ML Tests . 86567 |============================================================= Caffe 2020-02-13 Model: AlexNet - Acceleration: CPU - Iterations: 1000 Milli-Seconds < Lower Is Better ML Tests . 325884 |============================================================ Caffe 2020-02-13 Model: AlexNet - Acceleration: CPU - Iterations: 200 Milli-Seconds < Lower Is Better ML Tests . 65986 |============================================================= Caffe 2020-02-13 Model: AlexNet - Acceleration: CPU - Iterations: 100 Milli-Seconds < Lower Is Better ML Tests . 33496 |============================================================= TensorFlow Lite 2020-08-23 Model: Inception ResNet V2 Microseconds < Lower Is Better ML Tests . 2479080 |=========================================================== TensorFlow Lite 2020-08-23 Model: Mobilenet Quant Microseconds < Lower Is Better ML Tests . 141174 |============================================================ TensorFlow Lite 2020-08-23 Model: Mobilenet Float Microseconds < Lower Is Better ML Tests . 127818 |============================================================ TensorFlow Lite 2020-08-23 Model: NASNet Mobile Microseconds < Lower Is Better ML Tests . 152186 |============================================================ TensorFlow Lite 2020-08-23 Model: Inception V4 Microseconds < Lower Is Better ML Tests . 2749623 |=========================================================== TensorFlow Lite 2020-08-23 Model: SqueezeNet Microseconds < Lower Is Better ML Tests . 189764 |============================================================ RNNoise 2020-06-28 Seconds < Lower Is Better ML Tests . 16.14 |============================================================= R Benchmark Seconds < Lower Is Better ML Tests . 0.1293 |============================================================ LeelaChessZero 0.28 Backend: BLAS Nodes Per Second > Higher Is Better ML Tests . 563 |=============================================================== DeepSpeech 0.6 Acceleration: CPU Seconds < Lower Is Better ML Tests .................... 74.44 |========================================== Numpy Benchmark Score > Higher Is Better ML Tests .................... 422.45 |========================================= oneDNN 2.1.2 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better ML Tests .................... 2.98659 |======================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better ML Tests .................... 2237.65 |======================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better ML Tests .................... 3577.00 |======================================== oneDNN 2.1.2 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU ms < Lower Is Better ML Tests .................... 4.59343 |======================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better ML Tests .................... 2228.17 |======================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better ML Tests .................... 3587.17 |======================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU ms < Lower Is Better ML Tests .................... 2219.13 |======================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU ms < Lower Is Better ML Tests .................... 3579.00 |======================================== oneDNN 2.1.2 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better ML Tests .................... 3.24784 |======================================== oneDNN 2.1.2 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better ML Tests .................... 2.11771 |======================================== oneDNN 2.1.2 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better ML Tests .................... 23.77 |========================================== oneDNN 2.1.2 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU ms < Lower Is Better ML Tests .................... 6.74559 |======================================== oneDNN 2.1.2 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU ms < Lower Is Better ML Tests .................... 8.34789 |======================================== oneDNN 2.1.2 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU ms < Lower Is Better ML Tests .................... 22.79 |========================================== oneDNN 2.1.2 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better ML Tests .................... 2.69210 |======================================== oneDNN 2.1.2 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better ML Tests .................... 1.62985 |======================================== oneDNN 2.1.2 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU ms < Lower Is Better ML Tests .................... 12.09 |========================================== oneDNN 2.1.2 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU ms < Lower Is Better ML Tests .................... 4.25855 |======================================== OpenCV 4.5.4 Test: DNN - Deep Neural Network ms < Lower Is Better ML Tests . 13787 |============================================================= ONNX Runtime 1.10 Model: super-resolution-10 - Device: CPU Inferences Per Minute > Higher Is Better ONNX Runtime 1.10 Model: shufflenet-v2-10 - Device: CPU Inferences Per Minute > Higher Is Better ONNX Runtime 1.10 Model: fcn-resnet101-11 - Device: CPU Inferences Per Minute > Higher Is Better ONNX Runtime 1.10 Model: yolov4 - Device: CPU Inferences Per Minute > Higher Is Better OpenVINO 2021.1 Model: Age Gender Recognition Retail 0013 FP32 - Device: Intel GPU FPS > Higher Is Better OpenVINO 2021.1 Model: Age Gender Recognition Retail 0013 FP16 - Device: Intel GPU FPS > Higher Is Better OpenVINO 2021.1 Model: Age Gender Recognition Retail 0013 FP32 - Device: CPU FPS > Higher Is Better OpenVINO 2021.1 Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU FPS > Higher Is Better OpenVINO 2021.1 Model: Person Detection 0106 FP32 - Device: Intel GPU FPS > Higher Is Better OpenVINO 2021.1 Model: Person Detection 0106 FP16 - Device: Intel GPU FPS > Higher Is Better OpenVINO 2021.1 Model: Face Detection 0106 FP32 - Device: Intel GPU FPS > Higher Is Better OpenVINO 2021.1 Model: Face Detection 0106 FP16 - Device: Intel GPU FPS > Higher Is Better OpenVINO 2021.1 Model: Person Detection 0106 FP32 - Device: CPU FPS > Higher Is Better OpenVINO 2021.1 Model: Person Detection 0106 FP16 - Device: CPU FPS > Higher Is Better OpenVINO 2021.1 Model: Face Detection 0106 FP32 - Device: CPU FPS > Higher Is Better OpenVINO 2021.1 Model: Face Detection 0106 FP16 - Device: CPU FPS > Higher Is Better Tensorflow Build: Cifar10 Seconds < Lower Is Better AI Benchmark Alpha 0.1.2 Score > Higher Is Better Numenta Anomaly Benchmark 1.1 Detector: Bayesian Changepoint Seconds < Lower Is Better Numenta Anomaly Benchmark 1.1 Detector: Earthgecko Skyline Seconds < Lower Is Better Numenta Anomaly Benchmark 1.1 Detector: Windowed Gaussian Seconds < Lower Is Better Numenta Anomaly Benchmark 1.1 Detector: Relative Entropy Seconds < Lower Is Better Numenta Anomaly Benchmark 1.1 Detector: EXPoSE Seconds < Lower Is Better Mobile Neural Network 1.2 Model: inception-v3 ms < Lower Is Better MBP M1 Max Machine Learning . 58.25 |========================================== ML Tests .................... 31.58 |======================= Mobile Neural Network 1.2 Model: mobilenet-v1-1.0 ms < Lower Is Better MBP M1 Max Machine Learning . 8.205 |========================================== ML Tests .................... 2.440 |============ Mobile Neural Network 1.2 Model: SqueezeNetV1.0 ms < Lower Is Better MBP M1 Max Machine Learning . 9.967 |========================================== ML Tests .................... 4.546 |=================== Mobile Neural Network 1.2 Model: resnet-v2-50 ms < Lower Is Better MBP M1 Max Machine Learning . 42.43 |========================================== ML Tests .................... 22.44 |====================== Mobile Neural Network 1.2 Model: squeezenetv1.1 ms < Lower Is Better MBP M1 Max Machine Learning . 7.274 |========================================== ML Tests .................... 2.803 |================ Mobile Neural Network 1.2 Model: mobilenetV3 ms < Lower Is Better MBP M1 Max Machine Learning . 9.152 |========================================== ML Tests .................... 1.202 |====== oneDNN 2.1.2 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better oneDNN 2.1.2 Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better oneDNN 2.1.2 Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better oneDNN 2.1.2 Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better oneDNN 2.1.2 Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better oneDNN 2.1.2 Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better