pts-hpc

Apple M2 Pro testing with a Apple Mac mini and Apple M2 Pro on macOS 13.5 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 2312093-REIN-PTSHPC077
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Result
Identifier
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Performance Per
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Date
Run
  Test
  Duration
pts-hpc
December 09 2023
  18 Hours, 30 Minutes
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pts-hpc Apple M2 Pro testing with a Apple Mac mini and Apple M2 Pro on macOS 13.5 via the Phoronix Test Suite. ,,"pts-hpc" Processor,,Apple M2 Pro (10 Cores) Motherboard,,Apple Mac mini Memory,,16GB Disk,,461GB Graphics,,Apple M2 Pro Monitor,,Apple M2 Pro OS,,macOS 13.5 Kernel,,22.6.0 (arm64) Compiler,,GCC 14.0.3 + Clang 17.0.6 + LLVM 17.0.6 + Xcode 14.3.1 File-System,,APFS Screen Resolution,,x ,,"pts-hpc" "NAMD - ATPase Simulation - 327,506 Atoms (days/ns)",LIB,2.37121 "Nebular Empirical Analysis Tool - (sec)",LIB, "Timed MrBayes Analysis - (sec)",LIB, "Timed HMMer Search - (sec)",LIB, "Timed MAFFT Alignment - Multiple Sequence Alignment - LSU RNA (sec)",LIB,8.315 "LAMMPS Molecular Dynamics Simulator - Model: 20k Atoms (ns/day)",HIB, "LAMMPS Molecular Dynamics Simulator - Model: Rhodopsin Protein (ns/day)",HIB, "ACES DGEMM - (GFLOP/s)",HIB, "Himeno Benchmark - (MFLOPS)",HIB, "oneDNN - Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU (ms)",LIB,198.544 "oneDNN - Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU (ms)",LIB,127.933 "oneDNN - Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,266.297 "oneDNN - Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,341.080 "oneDNN - Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB, "oneDNN - Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB, "oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU (ms)",LIB,349.577 "oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU (ms)",LIB,888.776 "oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU (ms)",LIB,348.905 "oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,771.373 "oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,612.431 "oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,375.870 "oneDNN - Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU (ms)",LIB,216031 "oneDNN - Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU (ms)",LIB,132806 "oneDNN - Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,215461 "oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB, "oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB, "oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB, "oneDNN - Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,132819 "oneDNN - Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,215425 "oneDNN - Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,132815 "Numpy Benchmark - (Score)",HIB, "DeepSpeech - Acceleration: CPU (sec)",LIB, "GROMACS - Implementation: MPI CPU - Input: water_GMX50_bare (Ns/Day)",HIB, "GNU Octave Benchmark - (sec)",LIB, "Mobile Neural Network - Model: nasnet (ms)",LIB,11.523 "Mobile Neural Network - Model: mobilenetV3 (ms)",LIB,1.825 "Mobile Neural Network - Model: squeezenetv1.1 (ms)",LIB,3.199 "Mobile Neural Network - Model: resnet-v2-50 (ms)",LIB,25.079 "Mobile Neural Network - Model: SqueezeNetV1.0 (ms)",LIB,5.527 "Mobile Neural Network - Model: MobileNetV2_224 (ms)",LIB,3.629 "Mobile Neural Network - Model: mobilenet-v1-1.0 (ms)",LIB,4.664 "Mobile Neural Network - Model: inception-v3 (ms)",LIB,35.277 "NCNN - Target: CPU - Model: mobilenet (ms)",LIB,18.07 "NCNN - Target: CPU-v2-v2 - Model: mobilenet-v2 (ms)",LIB,4.64 "NCNN - Target: CPU-v3-v3 - Model: mobilenet-v3 (ms)",LIB,3.77 "NCNN - Target: CPU - Model: shufflenet-v2 (ms)",LIB,2.69 "NCNN - Target: CPU - Model: mnasnet (ms)",LIB,4.73 "NCNN - Target: CPU - Model: efficientnet-b0 (ms)",LIB,7.59 "NCNN - Target: CPU - Model: blazeface (ms)",LIB,0.88 "NCNN - Target: CPU - Model: googlenet (ms)",LIB,22.11 "NCNN - Target: CPU - Model: vgg16 (ms)",LIB,66.25 "NCNN - Target: CPU - Model: resnet18 (ms)",LIB,14.85 "NCNN - Target: CPU - Model: alexnet (ms)",LIB,16.75 "NCNN - Target: CPU - Model: resnet50 (ms)",LIB,40.62 "NCNN - Target: CPU - Model: yolov4-tiny (ms)",LIB,26.77 "NCNN - Target: CPU - Model: squeezenet_ssd (ms)",LIB,13.80 "NCNN - Target: CPU - Model: regnety_400m (ms)",LIB,6.44 "NCNN - Target: CPU - Model: vision_transformer (ms)",LIB,1187.73 "NCNN - Target: CPU - Model: FastestDet (ms)",LIB,2.11 "NCNN - Target: Vulkan GPU - Model: mobilenet (ms)",LIB,18.01 "NCNN - Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2 (ms)",LIB,4.59 "NCNN - Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3 (ms)",LIB,3.73 "NCNN - Target: Vulkan GPU - Model: shufflenet-v2 (ms)",LIB,2.66 "NCNN - Target: Vulkan GPU - Model: mnasnet (ms)",LIB,4.69 "NCNN - Target: Vulkan GPU - Model: efficientnet-b0 (ms)",LIB,7.51 "NCNN - Target: Vulkan GPU - Model: blazeface (ms)",LIB,0.87 "NCNN - Target: Vulkan GPU - Model: googlenet (ms)",LIB,21.91 "NCNN - Target: Vulkan GPU - Model: vgg16 (ms)",LIB,65.60 "NCNN - Target: Vulkan GPU - Model: resnet18 (ms)",LIB,14.72 "NCNN - Target: Vulkan GPU - Model: alexnet (ms)",LIB,16.59 "NCNN - Target: Vulkan GPU - Model: resnet50 (ms)",LIB,40.27 "NCNN - Target: Vulkan GPU - Model: yolov4-tiny (ms)",LIB,26.71 "NCNN - Target: Vulkan GPU - Model: squeezenet_ssd (ms)",LIB,13.69 "NCNN - Target: Vulkan GPU - Model: regnety_400m (ms)",LIB,6.38 "NCNN - Target: Vulkan GPU - Model: vision_transformer (ms)",LIB,1187.42 "NCNN - Target: Vulkan GPU - Model: FastestDet (ms)",LIB,2.11 "PlaidML - FP16: No - Mode: Inference - Network: VGG16 - Device: CPU (Examples/sec)",HIB, "PlaidML - FP16: No - Mode: Inference - Network: ResNet 50 - Device: CPU (Examples/sec)",HIB, "Numenta Anomaly Benchmark - Detector: KNN CAD (sec)",LIB, "Numenta Anomaly Benchmark - Detector: Relative Entropy (sec)",LIB, "Numenta Anomaly Benchmark - Detector: Windowed Gaussian (sec)",LIB, "Numenta Anomaly Benchmark - Detector: Earthgecko Skyline (sec)",LIB, "Numenta Anomaly Benchmark - Detector: Bayesian Changepoint (sec)",LIB, "Numenta Anomaly Benchmark - Detector: Contextual Anomaly Detector OSE (sec)",LIB, "AI Benchmark Alpha - (Score)",HIB, "PyHPC Benchmarks - Device: CPU - Backend: JAX - Project Size: 16384 - Benchmark: Equation of State (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: JAX - Project Size: 16384 - Benchmark: Isoneutral Mixing (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: JAX - Project Size: 65536 - Benchmark: Equation of State (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: JAX - Project Size: 65536 - Benchmark: Isoneutral Mixing (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: JAX - Project Size: 262144 - Benchmark: Equation of State (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: JAX - Project Size: 262144 - Benchmark: Isoneutral Mixing (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: JAX - Project Size: 1048576 - Benchmark: Equation of State (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: JAX - Project Size: 1048576 - Benchmark: Isoneutral Mixing (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: JAX - Project Size: 4194304 - Benchmark: Equation of State (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: JAX - Project Size: 4194304 - Benchmark: Isoneutral Mixing (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: Numba - Project Size: 16384 - Benchmark: Equation of State (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: Numba - Project Size: 16384 - Benchmark: Isoneutral Mixing (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: Numba - Project Size: 65536 - Benchmark: Equation of State (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: Numba - Project Size: 65536 - Benchmark: Isoneutral Mixing (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: Numpy - Project Size: 16384 - Benchmark: Equation of State (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: Numpy - Project Size: 16384 - Benchmark: Isoneutral Mixing (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: Numpy - Project Size: 65536 - Benchmark: Equation of State (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: Numpy - Project Size: 65536 - Benchmark: Isoneutral Mixing (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: Aesara - Project Size: 16384 - Benchmark: Equation of State (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: Aesara - Project Size: 16384 - Benchmark: Isoneutral Mixing (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: Aesara - Project Size: 65536 - Benchmark: Equation of State (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: Aesara - Project Size: 65536 - Benchmark: Isoneutral Mixing (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: Numba - Project Size: 262144 - Benchmark: Equation of State (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: Numba - Project Size: 262144 - Benchmark: Isoneutral Mixing (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: Numpy - Project Size: 262144 - Benchmark: Equation of State (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: Numpy - Project Size: 262144 - Benchmark: Isoneutral Mixing (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: Aesara - Project Size: 262144 - Benchmark: Equation of State (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: Aesara - Project Size: 262144 - Benchmark: Isoneutral Mixing (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: Numba - Project Size: 1048576 - Benchmark: Equation of State (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: Numba - Project Size: 1048576 - Benchmark: Isoneutral Mixing (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: Numba - Project Size: 4194304 - Benchmark: Equation of State (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: Numba - Project Size: 4194304 - Benchmark: Isoneutral Mixing (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: Numpy - Project Size: 1048576 - Benchmark: Equation of State (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: Numpy - Project Size: 1048576 - Benchmark: Isoneutral Mixing (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: Numpy - Project Size: 4194304 - Benchmark: Equation of State (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: Numpy - Project Size: 4194304 - Benchmark: Isoneutral Mixing (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: PyTorch - Project Size: 16384 - Benchmark: Equation of State (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: PyTorch - Project Size: 16384 - Benchmark: Isoneutral Mixing (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: PyTorch - Project Size: 65536 - Benchmark: Equation of State (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: PyTorch - Project Size: 65536 - Benchmark: Isoneutral Mixing (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: Aesara - Project Size: 1048576 - Benchmark: Equation of State (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: Aesara - Project Size: 1048576 - Benchmark: Isoneutral Mixing (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: Aesara - Project Size: 4194304 - Benchmark: Equation of State (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: Aesara - Project Size: 4194304 - Benchmark: Isoneutral Mixing (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: PyTorch - Project Size: 262144 - Benchmark: Equation of State (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: PyTorch - Project Size: 262144 - Benchmark: Isoneutral Mixing (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: PyTorch - Project Size: 1048576 - Benchmark: Equation of State (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: PyTorch - Project Size: 1048576 - Benchmark: Isoneutral Mixing (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: PyTorch - Project Size: 4194304 - Benchmark: Equation of State (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: PyTorch - Project Size: 4194304 - Benchmark: Isoneutral Mixing (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: TensorFlow - Project Size: 16384 - Benchmark: Equation of State (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: TensorFlow - Project Size: 16384 - Benchmark: Isoneutral Mixing (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: TensorFlow - Project Size: 65536 - Benchmark: Equation of State (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: TensorFlow - Project Size: 65536 - Benchmark: Isoneutral Mixing (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: TensorFlow - Project Size: 262144 - Benchmark: Equation of State (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: TensorFlow - Project Size: 262144 - Benchmark: Isoneutral Mixing (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: TensorFlow - Project Size: 1048576 - Benchmark: Equation of State (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: TensorFlow - Project Size: 1048576 - Benchmark: Isoneutral Mixing (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: TensorFlow - Project Size: 4194304 - Benchmark: Equation of State (sec)",LIB, "PyHPC Benchmarks - Device: CPU - Backend: TensorFlow - Project Size: 4194304 - Benchmark: Isoneutral Mixing (sec)",LIB,