2107171-PTS-ML
AMD Ryzen 5 3600 6-Core testing with a Gigabyte X570 AORUS PRO (F34 BIOS) and AMD Radeon VII 16GB on ManjaroLinux 21.1.0 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2107171-IB-2107171PT13.
SHOC Scalable HeterOgeneous Computing
Target: OpenCL - Benchmark: S3D
SHOC Scalable HeterOgeneous Computing
Target: OpenCL - Benchmark: Triad
SHOC Scalable HeterOgeneous Computing
Target: OpenCL - Benchmark: FFT SP
SHOC Scalable HeterOgeneous Computing
Target: OpenCL - Benchmark: MD5 Hash
SHOC Scalable HeterOgeneous Computing
Target: OpenCL - Benchmark: Reduction
SHOC Scalable HeterOgeneous Computing
Target: OpenCL - Benchmark: GEMM SGEMM_N
SHOC Scalable HeterOgeneous Computing
Target: OpenCL - Benchmark: Max SP Flops
SHOC Scalable HeterOgeneous Computing
Target: OpenCL - Benchmark: Bus Speed Download
SHOC Scalable HeterOgeneous Computing
Target: OpenCL - Benchmark: Bus Speed Readback
SHOC Scalable HeterOgeneous Computing
Target: OpenCL - Benchmark: Texture Read Bandwidth
oneDNN
Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU
oneDNN
Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU
oneDNN
Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU
oneDNN
Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU
oneDNN
Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU
oneDNN
Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU
oneDNN
Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU
oneDNN
Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU
oneDNN
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU
oneDNN
Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU
oneDNN
Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU
oneDNN
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU
Numpy Benchmark
DeepSpeech
Acceleration: CPU
R Benchmark
RNNoise
TensorFlow Lite
Model: SqueezeNet
TensorFlow Lite
Model: Inception V4
TensorFlow Lite
Model: NASNet Mobile
TensorFlow Lite
Model: Mobilenet Float
TensorFlow Lite
Model: Mobilenet Quant
TensorFlow Lite
Model: Inception ResNet V2
Mobile Neural Network
Model: mobilenetV3
Mobile Neural Network
Model: squeezenetv1.1
Mobile Neural Network
Model: resnet-v2-50
Mobile Neural Network
Model: SqueezeNetV1.0
Mobile Neural Network
Model: MobileNetV2_224
Mobile Neural Network
Model: mobilenet-v1-1.0
Mobile Neural Network
Model: inception-v3
NCNN
Target: CPU - Model: mobilenet
NCNN
Target: CPU-v2-v2 - Model: mobilenet-v2
NCNN
Target: CPU-v3-v3 - Model: mobilenet-v3
NCNN
Target: CPU - Model: shufflenet-v2
NCNN
Target: CPU - Model: mnasnet
NCNN
Target: CPU - Model: efficientnet-b0
NCNN
Target: CPU - Model: blazeface
NCNN
Target: CPU - Model: googlenet
NCNN
Target: CPU - Model: vgg16
NCNN
Target: CPU - Model: resnet18
NCNN
Target: CPU - Model: alexnet
NCNN
Target: CPU - Model: resnet50
NCNN
Target: CPU - Model: yolov4-tiny
NCNN
Target: CPU - Model: squeezenet_ssd
NCNN
Target: CPU - Model: regnety_400m
NCNN
Target: Vulkan GPU - Model: mobilenet
NCNN
Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2
NCNN
Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3
NCNN
Target: Vulkan GPU - Model: shufflenet-v2
NCNN
Target: Vulkan GPU - Model: mnasnet
NCNN
Target: Vulkan GPU - Model: efficientnet-b0
NCNN
Target: Vulkan GPU - Model: blazeface
NCNN
Target: Vulkan GPU - Model: googlenet
NCNN
Target: Vulkan GPU - Model: vgg16
NCNN
Target: Vulkan GPU - Model: resnet18
NCNN
Target: Vulkan GPU - Model: alexnet
NCNN
Target: Vulkan GPU - Model: resnet50
NCNN
Target: Vulkan GPU - Model: yolov4-tiny
NCNN
Target: Vulkan GPU - Model: squeezenet_ssd
NCNN
Target: Vulkan GPU - Model: regnety_400m
TNN
Target: CPU - Model: DenseNet
TNN
Target: CPU - Model: MobileNet v2
TNN
Target: CPU - Model: SqueezeNet v2
TNN
Target: CPU - Model: SqueezeNet v1.1
PlaidML
FP16: No - Mode: Inference - Network: VGG16 - Device: CPU
PlaidML
FP16: No - Mode: Inference - Network: ResNet 50 - Device: CPU
ONNX Runtime
Model: yolov4 - Device: OpenMP CPU
ONNX Runtime
Model: fcn-resnet101-11 - Device: OpenMP CPU
ONNX Runtime
Model: shufflenet-v2-10 - Device: OpenMP CPU
ONNX Runtime
Model: super-resolution-10 - Device: OpenMP CPU
Mlpack Benchmark
Benchmark: scikit_svm
Mlpack Benchmark
Benchmark: scikit_linearridgeregression
Scikit-Learn
Phoronix Test Suite v10.8.4