AMD Ryzen Non-X vs. Intel Alder Lake/Raptor Lake benchmarks new cpus
Benchmarks for a future article on Phoronix.
HTML result view exported from: https://openbenchmarking.org/result/2301151-PTS-EO2022BE21&rdt.
miniBUDE
Implementation: OpenMP - Input Deck: BM1
miniBUDE
Implementation: OpenMP - Input Deck: BM1
nekRS
Input: TurboPipe Periodic
OpenFOAM
Input: drivaerFastback, Small Mesh Size - Mesh Time
OpenFOAM
Input: drivaerFastback, Small Mesh Size - Execution Time
OpenRadioss
Model: Bumper Beam
OpenRadioss
Model: Cell Phone Drop Test
OpenRadioss
Model: Bird Strike on Windshield
OpenRadioss
Model: Rubber O-Ring Seal Installation
OpenRadioss
Model: INIVOL and Fluid Structure Interaction Drop Container
Xmrig
Variant: Monero - Hash Count: 1M
Xmrig
Variant: Wownero - Hash Count: 1M
JPEG XL libjxl
Input: PNG - Quality: 80
JPEG XL libjxl
Input: PNG - Quality: 90
JPEG XL libjxl
Input: JPEG - Quality: 80
JPEG XL libjxl
Input: JPEG - Quality: 90
JPEG XL libjxl
Input: PNG - Quality: 100
JPEG XL libjxl
Input: JPEG - Quality: 100
JPEG XL Decoding libjxl
CPU Threads: 1
JPEG XL Decoding libjxl
CPU Threads: All
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
SVT-AV1
Encoder Mode: Preset 4 - Input: Bosphorus 4K
SVT-AV1
Encoder Mode: Preset 8 - Input: Bosphorus 4K
SVT-AV1
Encoder Mode: Preset 12 - Input: Bosphorus 4K
SVT-AV1
Encoder Mode: Preset 13 - 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 12 - Input: Bosphorus 1080p
SVT-AV1
Encoder Mode: Preset 13 - Input: Bosphorus 1080p
OpenVKL
Benchmark: vklBenchmark ISPC
OpenVKL
Benchmark: vklBenchmark Scalar
Stargate Digital Audio Workstation
Sample Rate: 44100 - Buffer Size: 512
Stargate Digital Audio Workstation
Sample Rate: 96000 - Buffer Size: 512
Stargate Digital Audio Workstation
Sample Rate: 192000 - Buffer Size: 512
Stargate Digital Audio Workstation
Sample Rate: 44100 - Buffer Size: 1024
Stargate Digital Audio Workstation
Sample Rate: 480000 - Buffer Size: 512
Stargate Digital Audio Workstation
Sample Rate: 96000 - Buffer Size: 1024
Stargate Digital Audio Workstation
Sample Rate: 192000 - Buffer Size: 1024
Stargate Digital Audio Workstation
Sample Rate: 480000 - Buffer Size: 1024
libavif avifenc
Encoder Speed: 0
libavif avifenc
Encoder Speed: 2
libavif avifenc
Encoder Speed: 6
libavif avifenc
Encoder Speed: 6, Lossless
libavif avifenc
Encoder Speed: 10, Lossless
Timed Linux Kernel Compilation
Build: defconfig
Timed Linux Kernel Compilation
Build: allmodconfig
Y-Cruncher
Pi Digits To Calculate: 1B
Y-Cruncher
Pi Digits To Calculate: 500M
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: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU
oneDNN
Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - 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: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU
oneDNN
Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU
oneDNN
Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - 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
oneDNN
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: bf16bf16bf16 - Engine: CPU
CockroachDB
Workload: MoVR - Concurrency: 128
CockroachDB
Workload: MoVR - Concurrency: 256
CockroachDB
Workload: MoVR - Concurrency: 512
CockroachDB
Workload: MoVR - Concurrency: 1024
CockroachDB
Workload: KV, 10% Reads - Concurrency: 128
CockroachDB
Workload: KV, 10% Reads - Concurrency: 256
CockroachDB
Workload: KV, 10% Reads - Concurrency: 512
CockroachDB
Workload: KV, 50% Reads - Concurrency: 128
CockroachDB
Workload: KV, 50% Reads - Concurrency: 256
CockroachDB
Workload: KV, 50% Reads - Concurrency: 512
CockroachDB
Workload: KV, 60% Reads - Concurrency: 128
CockroachDB
Workload: KV, 60% Reads - Concurrency: 256
CockroachDB
Workload: KV, 60% Reads - Concurrency: 512
CockroachDB
Workload: KV, 95% Reads - Concurrency: 128
CockroachDB
Workload: KV, 95% Reads - Concurrency: 256
CockroachDB
Workload: KV, 95% Reads - Concurrency: 512
CockroachDB
Workload: KV, 10% Reads - Concurrency: 1024
CockroachDB
Workload: KV, 50% Reads - Concurrency: 1024
CockroachDB
Workload: KV, 60% Reads - Concurrency: 1024
CockroachDB
Workload: KV, 95% Reads - Concurrency: 1024
TensorFlow
Device: CPU - Batch Size: 16 - Model: AlexNet
TensorFlow
Device: CPU - Batch Size: 32 - Model: AlexNet
TensorFlow
Device: CPU - Batch Size: 64 - 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
TensorFlow
Device: CPU - Batch Size: 64 - Model: GoogLeNet
TensorFlow
Device: CPU - Batch Size: 64 - Model: ResNet-50
Neural Magic DeepSparse
Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: CV Detection,YOLOv5s COCO - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Detection,YOLOv5s COCO - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Detection,YOLOv5s COCO - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: CV Detection,YOLOv5s COCO - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream
Neural Magic DeepSparse
Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream
spaCy
Model: en_core_web_lg
spaCy
Model: en_core_web_trf
Blender
Blend File: BMW27 - Compute: CPU-Only
Blender
Blend File: Classroom - Compute: CPU-Only
Blender
Blend File: Fishy Cat - Compute: CPU-Only
Blender
Blend File: Barbershop - Compute: CPU-Only
Blender
Blend File: Pabellon Barcelona - Compute: CPU-Only
OpenVINO
Model: Face Detection FP16 - Device: CPU
OpenVINO
Model: Face Detection FP16 - Device: CPU
OpenVINO
Model: Person Detection FP16 - Device: CPU
OpenVINO
Model: Person Detection FP16 - Device: CPU
OpenVINO
Model: Person Detection FP32 - Device: CPU
OpenVINO
Model: Person Detection FP32 - Device: CPU
OpenVINO
Model: Vehicle Detection FP16 - Device: CPU
OpenVINO
Model: Vehicle Detection FP16 - Device: CPU
OpenVINO
Model: Face Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Face Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Vehicle Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Vehicle Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Weld Porosity Detection FP16 - Device: CPU
OpenVINO
Model: Weld Porosity Detection FP16 - Device: CPU
OpenVINO
Model: Machine Translation EN To DE FP16 - Device: CPU
OpenVINO
Model: Machine Translation EN To DE FP16 - Device: CPU
OpenVINO
Model: Weld Porosity Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Weld Porosity Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Person Vehicle Bike Detection FP16 - 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 - Device: CPU
OpenVINO
Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU
OpenVINO
Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU
nginx
Connections: 20
nginx
Connections: 100
nginx
Connections: 200
nginx
Connections: 500
nginx
Connections: 1000
nginx
Connections: 4000
EnCodec
Target Bandwidth: 3 kbps
EnCodec
Target Bandwidth: 6 kbps
EnCodec
Target Bandwidth: 24 kbps
EnCodec
Target Bandwidth: 1.5 kbps
BRL-CAD
VGR Performance Metric
uvg266
Video Input: Bosphorus 1080p - Video Preset: Slow
uvg266
Video Input: Bosphorus 1080p - Video Preset: Medium
uvg266
Video Input: Bosphorus 1080p - Video Preset: Very Fast
uvg266
Video Input: Bosphorus 1080p - Video Preset: Super Fast
uvg266
Video Input: Bosphorus 1080p - Video Preset: Ultra Fast
uvg266
Video Input: Bosphorus 4K - Video Preset: Slow
uvg266
Video Input: Bosphorus 4K - Video Preset: Medium
uvg266
Video Input: Bosphorus 4K - Video Preset: Very Fast
uvg266
Video Input: Bosphorus 4K - Video Preset: Super Fast
uvg266
Video Input: Bosphorus 4K - Video Preset: Ultra Fast
Kvazaar
Video Input: Bosphorus 1080p - Video Preset: Slow
Kvazaar
Video Input: Bosphorus 1080p - Video Preset: Medium
Kvazaar
Video Input: Bosphorus 1080p - Video Preset: Very Fast
Kvazaar
Video Input: Bosphorus 1080p - Video Preset: Super Fast
Kvazaar
Video Input: Bosphorus 1080p - Video Preset: Ultra Fast
Kvazaar
Video Input: Bosphorus 4K - Video Preset: Slow
Kvazaar
Video Input: Bosphorus 4K - Video Preset: Medium
Kvazaar
Video Input: Bosphorus 4K - Video Preset: Very Fast
Kvazaar
Video Input: Bosphorus 4K - Video Preset: Super Fast
Kvazaar
Video Input: Bosphorus 4K - Video Preset: Ultra Fast
ClickHouse
100M Rows Hits Dataset, First Run / Cold Cache
ClickHouse
100M Rows Hits Dataset, Second Run
ClickHouse
100M Rows Hits Dataset, Third Run
Phoronix Test Suite v10.8.5