AMD EPYC Zen 1
AMD EPYC 7601 32-Core testing with a TYAN B8026T70AE24HR (V1.02.B10 BIOS) and llvmpipe on Ubuntu 23.10 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2401081-NE-AMDEPYCZE16&grw.
Xmrig
Variant: Monero - Hash Count: 1M
Xmrig
Variant: Wownero - Hash Count: 1M
Xmrig
Variant: CryptoNight-Femto UPX2 - Hash Count: 1M
Xmrig
Variant: CryptoNight-Heavy - Hash Count: 1M
Quicksilver
Input: CORAL2 P2
Xmrig
Variant: KawPow - Hash Count: 1M
Xmrig
Variant: GhostRider - Hash Count: 1M
QuantLib
Configuration: Multi-Threaded
miniBUDE
Implementation: OpenMP - Input Deck: BM1
miniBUDE
Implementation: OpenMP - Input Deck: BM1
miniBUDE
Implementation: OpenMP - Input Deck: BM2
miniBUDE
Implementation: OpenMP - Input Deck: BM2
OpenRadioss
Model: Chrysler Neon 1M
Timed MrBayes Analysis
Primate Phylogeny Analysis
TensorFlow
Device: CPU - Batch Size: 16 - Model: ResNet-50
CloverLeaf
Input: clover_bm64_short
Y-Cruncher
Pi Digits To Calculate: 500M
Quicksilver
Input: CTS2
Y-Cruncher
Pi Digits To Calculate: 1B
CloverLeaf
Input: clover_bm16
Neural Magic DeepSparse
Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - 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: 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: Asynchronous Multi-Stream
Quicksilver
Input: CORAL2 P1
SPECFEM3D
Model: Layered Halfspace
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: 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, Sparse INT8 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Detection, YOLOv5s COCO, Sparse INT8 - 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: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream
easyWave
Input: e2Asean Grid + BengkuluSept2007 Source - Time: 1200
Neural Magic DeepSparse
Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream
easyWave
Input: e2Asean Grid + BengkuluSept2007 Source - Time: 2400
Neural Magic DeepSparse
Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream
PyTorch
Device: CPU - Batch Size: 1 - Model: ResNet-50
PyTorch
Device: CPU - Batch Size: 256 - Model: ResNet-50
GROMACS
Implementation: MPI CPU - Input: water_GMX50_bare
LAMMPS Molecular Dynamics Simulator
Model: 20k Atoms
NAMD
ATPase Simulation - 327,506 Atoms
OpenVINO
Model: Face Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Face Detection FP16-INT8 - Device: CPU
SPECFEM3D
Model: Homogeneous Halfspace
SPECFEM3D
Model: Mount St. Helens
SPECFEM3D
Model: Tomographic Model
OpenVINO
Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU
OpenVINO
Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU
OpenVINO
Model: Person Detection FP16 - Device: CPU
OpenVINO
Model: Person Detection FP16 - Device: CPU
SPECFEM3D
Model: Water-layered Halfspace
OpenVINO
Model: Weld Porosity Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Weld Porosity Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Vehicle Detection FP16-INT8 - Device: CPU
OpenVINO
Model: Vehicle 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: Machine Translation EN To DE FP16 - Device: CPU
OpenVINO
Model: Machine Translation EN To DE FP16 - Device: CPU
OpenVINO
Model: Face Detection Retail FP16-INT8 - Device: CPU
OpenVINO
Model: Face Detection Retail FP16-INT8 - Device: CPU
OpenVINO
Model: Handwritten English Recognition FP16-INT8 - Device: CPU
OpenVINO
Model: Handwritten English Recognition FP16-INT8 - Device: CPU
OpenVINO
Model: Road Segmentation ADAS FP16-INT8 - Device: CPU
OpenVINO
Model: Road Segmentation ADAS FP16-INT8 - Device: CPU
ACES DGEMM
Sustained Floating-Point Rate
Kripke
OpenFOAM
Input: drivaerFastback, Small Mesh Size - Mesh Time
OpenFOAM
Input: drivaerFastback, Small Mesh Size - Execution Time
OpenFOAM
Input: drivaerFastback, Medium Mesh Size - Mesh Time
OpenFOAM
Input: drivaerFastback, Medium Mesh Size - Execution Time
Xcompact3d Incompact3d
Input: input.i3d 193 Cells Per Direction
Xcompact3d Incompact3d
Input: X3D-benchmarking input.i3d
GPAW
Input: Carbon Nanotube
Timed FFmpeg Compilation
Time To Compile
7-Zip Compression
Test: Compression Rating
7-Zip Compression
Test: Decompression Rating
Timed LLVM Compilation
Build System: Ninja
Timed LLVM Compilation
Build System: Unix Makefiles
Timed Linux Kernel Compilation
Build: defconfig
Timed Linux Kernel Compilation
Build: allmodconfig
SVT-AV1
Encoder Mode: Preset 13 - Input: Bosphorus 4K
SVT-AV1
Encoder Mode: Preset 12 - Input: Bosphorus 4K
SVT-AV1
Encoder Mode: Preset 8 - Input: Bosphorus 4K
SVT-AV1
Encoder Mode: Preset 4 - Input: Bosphorus 4K
x265
Video Input: Bosphorus 4K
Chaos Group V-RAY
Mode: CPU
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: Pabellon Barcelona - Compute: CPU-Only
Blender
Blend File: Barbershop - Compute: CPU-Only
FFmpeg
Encoder: libx265 - Scenario: Live
FFmpeg
Encoder: libx265 - Scenario: Upload
FFmpeg
Encoder: libx265 - Scenario: Platform
FFmpeg
Encoder: libx265 - Scenario: Video On Demand
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
VVenC
Video Input: Bosphorus 4K - Video Preset: Fast
VVenC
Video Input: Bosphorus 4K - Video Preset: Faster
rav1e
Speed: 10
rav1e
Speed: 6
rav1e
Speed: 5
rav1e
Speed: 1
Embree
Binary: Pathtracer ISPC - Model: Asian Dragon
Embree
Binary: Pathtracer ISPC - Model: Crown
Intel Open Image Denoise
Run: RT.ldr_alb_nrm.3840x2160 - Device: CPU-Only
IndigoBench
Acceleration: CPU - Scene: Supercar
IndigoBench
Acceleration: CPU - Scene: Bedroom
OSPRay
Benchmark: gravity_spheres_volume/dim_512/ao/real_time
OSPRay
Benchmark: gravity_spheres_volume/dim_512/scivis/real_time
OSPRay
Benchmark: gravity_spheres_volume/dim_512/pathtracer/real_time
OSPRay
Benchmark: particle_volume/ao/real_time
OSPRay
Benchmark: particle_volume/scivis/real_time
OSPRay
Benchmark: particle_volume/pathtracer/real_time
OSPRay Studio
Camera: 1 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU
OSPRay Studio
Camera: 1 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU
OSPRay Studio
Camera: 1 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU
OSPRay Studio
Camera: 3 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU
OSPRay Studio
Camera: 3 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU
OSPRay Studio
Camera: 3 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU
Timed Gem5 Compilation
Time To Compile
Timed Node.js Compilation
Time To Compile
DuckDB
Benchmark: IMDB
DuckDB
Benchmark: TPC-H Parquet
Speedb
Test: Random Read
Speedb
Test: Read While Writing
Speedb
Test: Read Random Write Random
Speedb
Test: Update Random
nginx
Connections: 500
nginx
Connections: 1000
Apache HTTP Server
Concurrent Requests: 1000
OpenSSL
Algorithm: RSA4096
OpenSSL
Algorithm: RSA4096
OpenSSL
Algorithm: SHA256
OpenSSL
Algorithm: SHA512
OpenSSL
Algorithm: AES-128-GCM
OpenSSL
Algorithm: AES-256-GCM
OpenSSL
Algorithm: ChaCha20
OpenSSL
Algorithm: ChaCha20-Poly1305
Apache IoTDB
Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 200 - Client Number: 100
Apache IoTDB
Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 200 - Client Number: 100
Apache IoTDB
Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 200 - Client Number: 400
Apache IoTDB
Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 200 - Client Number: 400
Apache IoTDB
Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 500 - Client Number: 100
Apache IoTDB
Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 500 - Client Number: 100
Apache IoTDB
Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 500 - Client Number: 400
Apache IoTDB
Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 500 - Client Number: 400
Apache IoTDB
Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 800 - Client Number: 100
Apache IoTDB
Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 800 - Client Number: 100
Apache IoTDB
Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 800 - Client Number: 400
Apache IoTDB
Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 800 - Client Number: 400
Apache IoTDB
Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 200 - Client Number: 100
Apache IoTDB
Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 200 - Client Number: 100
Apache IoTDB
Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 200 - Client Number: 400
Apache IoTDB
Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 200 - Client Number: 400
Apache IoTDB
Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 500 - Client Number: 100
Apache IoTDB
Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 500 - Client Number: 100
Apache IoTDB
Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 500 - Client Number: 400
Apache IoTDB
Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 500 - Client Number: 400
Apache IoTDB
Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 800 - Client Number: 100
Apache IoTDB
Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 800 - Client Number: 100
Apache IoTDB
Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 800 - Client Number: 400
Apache IoTDB
Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 800 - Client Number: 400
Redis 7.0.12 + memtier_benchmark
Protocol: Redis - Clients: 100 - Set To Get Ratio: 1:10
Redis 7.0.12 + memtier_benchmark
Protocol: Redis - Clients: 100 - Set To Get Ratio: 1:5
RocksDB
Test: Random Read
RocksDB
Test: Read While Writing
RocksDB
Test: Read Random Write Random
RocksDB
Test: Update Random
Apache Cassandra
Test: Writes
nginx
Connections: 500
nginx
CPU Power Consumption Monitor
nginx
Connections: 1000
nginx
CPU Power Consumption Monitor
OpenSSL
Algorithm: RSA4096
OpenSSL
CPU Power Consumption Monitor
OpenSSL
Algorithm: SHA256
OpenSSL
CPU Power Consumption Monitor
OpenSSL
Algorithm: SHA512
OpenSSL
CPU Power Consumption Monitor
OpenSSL
Algorithm: AES-128-GCM
OpenSSL
CPU Power Consumption Monitor
OpenSSL
Algorithm: AES-256-GCM
OpenSSL
CPU Power Consumption Monitor
OpenSSL
Algorithm: ChaCha20
OpenSSL
CPU Power Consumption Monitor
OpenSSL
Algorithm: ChaCha20-Poly1305
OpenSSL
CPU Power Consumption Monitor
Apache HTTP Server
Concurrent Requests: 1000
Apache HTTP Server
CPU Power Consumption Monitor
Apache IoTDB
CPU Power Consumption Monitor
Apache IoTDB
CPU Power Consumption Monitor
Apache IoTDB
CPU Power Consumption Monitor
Apache IoTDB
CPU Power Consumption Monitor
Apache IoTDB
CPU Power Consumption Monitor
Apache IoTDB
CPU Power Consumption Monitor
Apache IoTDB
CPU Power Consumption Monitor
Apache IoTDB
CPU Power Consumption Monitor
Apache IoTDB
CPU Power Consumption Monitor
Apache IoTDB
CPU Power Consumption Monitor
Apache IoTDB
CPU Power Consumption Monitor
Apache IoTDB
CPU Power Consumption Monitor
DuckDB
CPU Power Consumption Monitor
DuckDB
CPU Power Consumption Monitor
Apache Cassandra
Test: Writes
Apache Cassandra
CPU Power Consumption Monitor
Speedb
Test: Random Read
Speedb
CPU Power Consumption Monitor
Speedb
Test: Read While Writing
Speedb
CPU Power Consumption Monitor
Speedb
Test: Read Random Write Random
Speedb
CPU Power Consumption Monitor
Speedb
Test: Update Random
Speedb
CPU Power Consumption Monitor
RocksDB
Test: Random Read
RocksDB
CPU Power Consumption Monitor
RocksDB
Test: Read While Writing
RocksDB
CPU Power Consumption Monitor
RocksDB
Test: Read Random Write Random
RocksDB
CPU Power Consumption Monitor
RocksDB
Test: Update Random
RocksDB
CPU Power Consumption Monitor
Redis 7.0.12 + memtier_benchmark
Protocol: Redis - Clients: 100 - Set To Get Ratio: 1:10
Redis 7.0.12 + memtier_benchmark
CPU Power Consumption Monitor
Redis 7.0.12 + memtier_benchmark
Protocol: Redis - Clients: 100 - Set To Get Ratio: 1:5
Redis 7.0.12 + memtier_benchmark
CPU Power Consumption Monitor
7-Zip Compression
Test: Decompression Rating
7-Zip Compression
CPU Power Consumption Monitor
Timed Linux Kernel Compilation
CPU Power Consumption Monitor
Timed Linux Kernel Compilation
CPU Power Consumption Monitor
Timed LLVM Compilation
CPU Power Consumption Monitor
Timed LLVM Compilation
CPU Power Consumption Monitor
Timed Node.js Compilation
CPU Power Consumption Monitor
Timed Gem5 Compilation
CPU Power Consumption Monitor
Timed FFmpeg Compilation
CPU Power Consumption Monitor
QuantLib
Configuration: Multi-Threaded
QuantLib
CPU Power Consumption Monitor
SPECFEM3D
CPU Power Consumption Monitor
SPECFEM3D
CPU Power Consumption Monitor
SPECFEM3D
CPU Power Consumption Monitor
SPECFEM3D
CPU Power Consumption Monitor
SPECFEM3D
CPU Power Consumption Monitor
OpenFOAM
CPU Power Consumption Monitor
OpenFOAM
CPU Power Consumption Monitor
OpenRadioss
CPU Power Consumption Monitor
miniBUDE
Implementation: OpenMP - Input Deck: BM1
miniBUDE
CPU Power Consumption Monitor
miniBUDE
Implementation: OpenMP - Input Deck: BM2
miniBUDE
CPU Power Consumption Monitor
easyWave
CPU Power Consumption Monitor
easyWave
CPU Power Consumption Monitor
GPAW
CPU Power Consumption Monitor
LAMMPS Molecular Dynamics Simulator
Model: 20k Atoms
LAMMPS Molecular Dynamics Simulator
CPU Power Consumption Monitor
CloverLeaf
CPU Power Consumption Monitor
CloverLeaf
CPU Power Consumption Monitor
Kripke
Kripke
CPU Power Consumption Monitor
Xcompact3d Incompact3d
CPU Power Consumption Monitor
Xcompact3d Incompact3d
CPU Power Consumption Monitor
NAMD
CPU Power Consumption Monitor
GROMACS
Implementation: MPI CPU - Input: water_GMX50_bare
GROMACS
CPU Power Consumption Monitor
Quicksilver
Input: CORAL2 P1
Quicksilver
CPU Power Consumption Monitor
Quicksilver
Input: CORAL2 P2