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AMD Ryzen 7 4800U testing with a ASRock 4X4-4000 (P1.30Q BIOS) and AMD Renoir 512MB on Ubuntu 22.04 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2210101-NE-FDSDF056044&gru.
srsRAN
Test: 4G PHY_DL_Test 100 PRB MIMO 64-QAM
srsRAN
Test: 4G PHY_DL_Test 100 PRB SISO 64-QAM
srsRAN
Test: 4G PHY_DL_Test 100 PRB MIMO 256-QAM
srsRAN
Test: 4G PHY_DL_Test 100 PRB SISO 256-QAM
srsRAN
Test: 5G PHY_DL_NR Test 52 PRB SISO 64-QAM
QuadRay
Scene: 1 - Resolution: 4K
QuadRay
Scene: 2 - Resolution: 4K
QuadRay
Scene: 3 - Resolution: 4K
QuadRay
Scene: 5 - Resolution: 4K
QuadRay
Scene: 1 - Resolution: 1080p
QuadRay
Scene: 2 - Resolution: 1080p
QuadRay
Scene: 3 - Resolution: 1080p
QuadRay
Scene: 5 - Resolution: 1080p
OpenVINO
Model: Face Detection FP16 - Device: CPU
OpenVINO
Model: Person Detection FP16 - Device: CPU
OpenVINO
Model: Person Detection FP32 - Device: CPU
OpenVINO
Model: Vehicle Detection FP16 - Device: CPU
OpenVINO
Model: Face Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Vehicle Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Weld Porosity Detection FP16 - Device: CPU
OpenVINO
Model: Machine Translation EN To DE FP16 - Device: CPU
OpenVINO
Model: Weld Porosity Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Person Vehicle Bike Detection FP16 - Device: CPU
OpenVINO
Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU
OpenVINO
Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU
Unvanquished
Resolution: 1920 x 1080 - Effects Quality: High
Unvanquished
Resolution: 1920 x 1200 - Effects Quality: High
Unvanquished
Resolution: 2560 x 1440 - Effects Quality: High
Unvanquished
Resolution: 3840 x 2160 - Effects Quality: High
Unvanquished
Resolution: 1920 x 1080 - Effects Quality: Ultra
Unvanquished
Resolution: 1920 x 1200 - Effects Quality: Ultra
Unvanquished
Resolution: 2560 x 1440 - Effects Quality: Ultra
Unvanquished
Resolution: 3840 x 2160 - Effects Quality: Ultra
Unvanquished
Resolution: 1920 x 1080 - Effects Quality: Medium
Unvanquished
Resolution: 1920 x 1200 - Effects Quality: Medium
Unvanquished
Resolution: 2560 x 1440 - Effects Quality: Medium
Unvanquished
Resolution: 3840 x 2160 - Effects Quality: Medium
AOM AV1
Encoder Mode: Speed 0 Two-Pass - Input: Bosphorus 4K
AOM AV1
Encoder Mode: Speed 4 Two-Pass - Input: Bosphorus 4K
AOM AV1
Encoder Mode: Speed 6 Realtime - Input: Bosphorus 4K
AOM AV1
Encoder Mode: Speed 6 Two-Pass - Input: Bosphorus 4K
AOM AV1
Encoder Mode: Speed 8 Realtime - Input: Bosphorus 4K
AOM AV1
Encoder Mode: Speed 9 Realtime - Input: Bosphorus 4K
AOM AV1
Encoder Mode: Speed 10 Realtime - Input: Bosphorus 4K
AOM AV1
Encoder Mode: Speed 0 Two-Pass - Input: Bosphorus 1080p
AOM AV1
Encoder Mode: Speed 4 Two-Pass - Input: Bosphorus 1080p
AOM AV1
Encoder Mode: Speed 6 Realtime - Input: Bosphorus 1080p
AOM AV1
Encoder Mode: Speed 6 Two-Pass - Input: Bosphorus 1080p
AOM AV1
Encoder Mode: Speed 8 Realtime - Input: Bosphorus 1080p
AOM AV1
Encoder Mode: Speed 9 Realtime - Input: Bosphorus 1080p
AOM AV1
Encoder Mode: Speed 10 Realtime - Input: Bosphorus 1080p
SVT-AV1
Encoder Mode: Preset 4 - Input: Bosphorus 4K
SVT-AV1
Encoder Mode: Preset 8 - Input: Bosphorus 4K
SVT-AV1
Encoder Mode: Preset 10 - Input: Bosphorus 4K
SVT-AV1
Encoder Mode: Preset 12 - Input: Bosphorus 4K
SVT-AV1
Encoder Mode: Preset 4 - Input: Bosphorus 1080p
SVT-AV1
Encoder Mode: Preset 8 - Input: Bosphorus 1080p
SVT-AV1
Encoder Mode: Preset 10 - Input: Bosphorus 1080p
SVT-AV1
Encoder Mode: Preset 12 - Input: Bosphorus 1080p
TensorFlow
Device: CPU - Batch Size: 16 - Model: AlexNet
TensorFlow
Device: CPU - Batch Size: 32 - Model: AlexNet
TensorFlow
Device: CPU - Batch Size: 16 - Model: GoogLeNet
TensorFlow
Device: CPU - Batch Size: 16 - Model: ResNet-50
TensorFlow
Device: CPU - Batch Size: 32 - Model: GoogLeNet
TensorFlow
Device: CPU - Batch Size: 32 - Model: ResNet-50
GraphicsMagick
Operation: Swirl
GraphicsMagick
Operation: Rotate
GraphicsMagick
Operation: Sharpen
GraphicsMagick
Operation: Enhanced
GraphicsMagick
Operation: Resizing
GraphicsMagick
Operation: Noise-Gaussian
GraphicsMagick
Operation: HWB Color Space
C-Blosc
Test: blosclz shuffle
C-Blosc
Test: blosclz bitshuffle
SMHasher
Hash: wyhash
SMHasher
Hash: SHA3-256
SMHasher
Hash: Spooky32
SMHasher
Hash: fasthash32
SMHasher
Hash: FarmHash128
SMHasher
Hash: t1ha2_atonce
SMHasher
Hash: FarmHash32 x86_64 AVX
SMHasher
Hash: t1ha0_aes_avx2 x86_64
SMHasher
Hash: MeowHash x86_64 AES-NI
7-Zip Compression
Test: Compression Rating
7-Zip Compression
Test: Decompression Rating
WebP Image Encode
Encode Settings: Default
WebP Image Encode
Encode Settings: Quality 100
WebP Image Encode
Encode Settings: Quality 100, Lossless
WebP Image Encode
Encode Settings: Quality 100, Highest Compression
WebP2 Image Encode
Encode Settings: Default
WebP2 Image Encode
Encode Settings: Quality 75, Compression Effort 7
WebP2 Image Encode
Encode Settings: Quality 95, Compression Effort 7
WebP2 Image Encode
Encode Settings: Quality 100, Compression Effort 5
Facebook RocksDB
Test: Random Fill
Facebook RocksDB
Test: Random Read
Facebook RocksDB
Test: Update Random
Facebook RocksDB
Test: Sequential Fill
Facebook RocksDB
Test: Random Fill Sync
Facebook RocksDB
Test: Read While Writing
Facebook RocksDB
Test: Read Random Write Random
ClickHouse
100M Rows Web Analytics Dataset, First Run / Cold Cache
ClickHouse
100M Rows Web Analytics Dataset, Second Run
ClickHouse
100M Rows Web Analytics Dataset, Third Run
srsRAN
Test: OFDM_Test
spaCy
Model: en_core_web_lg
spaCy
Model: en_core_web_trf
srsRAN
Test: 4G PHY_DL_Test 100 PRB MIMO 64-QAM
srsRAN
Test: 4G PHY_DL_Test 100 PRB SISO 64-QAM
srsRAN
Test: 4G PHY_DL_Test 100 PRB MIMO 256-QAM
srsRAN
Test: 4G PHY_DL_Test 100 PRB SISO 256-QAM
srsRAN
Test: 5G PHY_DL_NR Test 52 PRB SISO 64-QAM
BRL-CAD
VGR Performance Metric
SMHasher
Hash: wyhash
SMHasher
Hash: SHA3-256
SMHasher
Hash: Spooky32
SMHasher
Hash: fasthash32
SMHasher
Hash: FarmHash128
SMHasher
Hash: t1ha2_atonce
SMHasher
Hash: FarmHash32 x86_64 AVX
SMHasher
Hash: t1ha0_aes_avx2 x86_64
SMHasher
Hash: MeowHash x86_64 AES-NI
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
Mobile Neural Network
Model: nasnet
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: CPU - Model: vision_transformer
NCNN
Target: CPU - Model: FastestDet
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
NCNN
Target: Vulkan GPU - Model: vision_transformer
NCNN
Target: Vulkan GPU - Model: FastestDet
OpenVINO
Model: Face Detection FP16 - Device: CPU
OpenVINO
Model: Person Detection FP16 - Device: CPU
OpenVINO
Model: Person Detection FP32 - Device: CPU
OpenVINO
Model: Vehicle Detection FP16 - Device: CPU
OpenVINO
Model: Face Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Vehicle Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Weld Porosity Detection FP16 - Device: CPU
OpenVINO
Model: Machine Translation EN To DE FP16 - Device: CPU
OpenVINO
Model: Weld Porosity Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Person Vehicle Bike Detection FP16 - Device: CPU
OpenVINO
Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU
OpenVINO
Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU
OpenFOAM
Input: motorBike - Mesh Time
OpenFOAM
Input: motorBike - Execution Time
OpenFOAM
Input: drivaerFastback, Small Mesh Size - Mesh Time
OpenFOAM
Input: drivaerFastback, Small Mesh Size - Execution Time
Timed Node.js Compilation
Time To Compile
Timed PHP Compilation
Time To Compile
Timed CPython Compilation
Build Configuration: Default
Timed CPython Compilation
Build Configuration: Released Build, PGO + LTO Optimized
Y-Cruncher
Pi Digits To Calculate: 1B
Y-Cruncher
Pi Digits To Calculate: 500M
Timed Erlang/OTP Compilation
Time To Compile
Timed Wasmer Compilation
Time To Compile
FLAC Audio Encoding
WAV To FLAC
Blender
Blend File: BMW27 - Compute: CPU-Only
Phoronix Test Suite v10.8.5