Intel Optimized Power Mode Xeon Platinum Benchmarks

2 x INTEL XEON PLATINUM 8592 testing by Michael Larabel for a future article.

HTML result view exported from: https://openbenchmarking.org/result/2312153-NE-XEONEMRPO30&rdt&grr.

PyTorch

Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l

PyTorch

Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_l

Timed GCC Compilation

Time To Compile

PostgreSQL

Scaling Factor: 100 - Clients: 1000 - Mode: Read Only - Average Latency

PostgreSQL

Scaling Factor: 100 - Clients: 1000 - Mode: Read Only

Apache Spark TPC-H

Scale Factor: 10 - Q22

Apache Spark TPC-H

Scale Factor: 10 - Q21

Apache Spark TPC-H

Scale Factor: 10 - Q20

Apache Spark TPC-H

Scale Factor: 10 - Q19

Apache Spark TPC-H

Scale Factor: 10 - Q18

Apache Spark TPC-H

Scale Factor: 10 - Q17

Apache Spark TPC-H

Scale Factor: 10 - Q16

Apache Spark TPC-H

Scale Factor: 10 - Q15

Apache Spark TPC-H

Scale Factor: 10 - Q14

Apache Spark TPC-H

Scale Factor: 10 - Q13

Apache Spark TPC-H

Scale Factor: 10 - Q12

Apache Spark TPC-H

Scale Factor: 10 - Q11

Apache Spark TPC-H

Scale Factor: 10 - Q10

Apache Spark TPC-H

Scale Factor: 10 - Q09

Apache Spark TPC-H

Scale Factor: 10 - Q08

Apache Spark TPC-H

Scale Factor: 10 - Q07

Apache Spark TPC-H

Scale Factor: 10 - Q06

Apache Spark TPC-H

Scale Factor: 10 - Q05

Apache Spark TPC-H

Scale Factor: 10 - Q04

Apache Spark TPC-H

Scale Factor: 10 - Q03

Apache Spark TPC-H

Scale Factor: 10 - Q02

Apache Spark TPC-H

Scale Factor: 10 - Q01

Apache Spark TPC-H

Scale Factor: 10 - Geometric Mean Of All Queries

PyTorch

Device: CPU - Batch Size: 64 - Model: ResNet-152

Memcached

Set To Get Ratio: 1:10

PyTorch

Device: CPU - Batch Size: 256 - Model: ResNet-152

Blender

Blend File: Barbershop - Compute: CPU-Only

easyWave

Input: e2Asean Grid + BengkuluSept2007 Source - Time: 2400

DuckDB

Benchmark: TPC-H Parquet

DuckDB

Benchmark: IMDB

Timed LLVM Compilation

Build System: Unix Makefiles

FFmpeg

Encoder: libx265 - Scenario: Upload

FFmpeg

Encoder: libx265 - Scenario: Video On Demand

FFmpeg

Encoder: libx265 - Scenario: Platform

Timed Linux Kernel Compilation

Build: allmodconfig

PostgreSQL

Scaling Factor: 100 - Clients: 1000 - Mode: Read Write - Average Latency

PostgreSQL

Scaling Factor: 100 - Clients: 1000 - Mode: Read Write

QMCPACK

Input: Li2_STO_ae

easyWave

Input: e2Asean Grid + BengkuluSept2007 Source - Time: 1200

OpenRadioss

Model: Chrysler Neon 1M

OpenRadioss

Model: Bird Strike on Windshield

OpenRadioss

Model: INIVOL and Fluid Structure Interaction Drop Container

Timed LLVM Compilation

Build System: Ninja

VVenC

Video Input: Bosphorus 4K - Video Preset: Fast

nginx

Connections: 500

Apache HTTP Server

Concurrent Requests: 500

OpenRadioss

Model: Rubber O-Ring Seal Installation

Liquid-DSP

Threads: 64 - Buffer Length: 256 - Filter Length: 57

OpenRadioss

Model: Bumper Beam

Zstd Compression

Compression Level: 12 - Decompression Speed

Zstd Compression

Compression Level: 12 - Compression Speed

Redis

Test: SET - Parallel Connections: 500

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

Zstd Compression

Compression Level: 19, Long Mode - Decompression Speed

Zstd Compression

Compression Level: 19, Long Mode - Compression Speed

Timed Linux Kernel Compilation

Build: defconfig

nginx

Connections: 1000

Zstd Compression

Compression Level: 19 - Decompression Speed

Zstd Compression

Compression Level: 19 - Compression Speed

Xmrig

Variant: GhostRider - Hash Count: 1M

PyTorch

Device: CPU - Batch Size: 64 - Model: ResNet-50

PyTorch

Device: CPU - Batch Size: 256 - Model: ResNet-50

OpenVINO

Model: Face Detection FP16-INT8 - Device: CPU

OpenVINO

Model: Face Detection FP16-INT8 - Device: CPU

Memcached

Set To Get Ratio: 1:100

VVenC

Video Input: Bosphorus 4K - Video Preset: Faster

OpenVINO

Model: Person Vehicle Bike Detection FP16 - Device: CPU

OpenVINO

Model: Person Vehicle Bike Detection FP16 - Device: CPU

OpenVINO

Model: Road Segmentation ADAS FP16-INT8 - Device: CPU

OpenVINO

Model: Road Segmentation ADAS FP16-INT8 - Device: CPU

OpenVINO

Model: Person Detection FP16 - Device: CPU

OpenVINO

Model: Person Detection FP16 - Device: CPU

OpenVINO

Model: Vehicle Detection FP16-INT8 - Device: CPU

OpenVINO

Model: Vehicle Detection FP16-INT8 - 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

QuantLib

Configuration: Multi-Threaded

OpenVINO

Model: Handwritten English Recognition FP16-INT8 - Device: CPU

OpenVINO

Model: Handwritten English Recognition FP16-INT8 - Device: CPU

OpenVINO

Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU

OpenVINO

Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU

OpenVINO

Model: Weld Porosity Detection FP16-INT8 - Device: CPU

OpenVINO

Model: Weld Porosity Detection FP16-INT8 - Device: CPU

FFmpeg

Encoder: libx265 - Scenario: Live

Apache Hadoop

Operation: Create - Threads: 100 - Files: 100000

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: 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

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 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

Liquid-DSP

Threads: 32 - Buffer Length: 256 - Filter Length: 512

Liquid-DSP

Threads: 256 - Buffer Length: 256 - Filter Length: 32

7-Zip Compression

Test: Decompression Rating

7-Zip Compression

Test: Compression Rating

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: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream

Neural Magic DeepSparse

Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream

uvg266

Video Input: Bosphorus 4K - Video Preset: Very Fast

Neural Magic DeepSparse

Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream

Neural Magic DeepSparse

Model: ResNet-50, Sparse INT8 - 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

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 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 Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream

Neural Magic DeepSparse

Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream

VVenC

Video Input: Bosphorus 1080p - Video Preset: Fast

OpenRadioss

Model: Cell Phone Drop Test

Blender

Blend File: Classroom - Compute: CPU-Only

Liquid-DSP

Threads: 256 - Buffer Length: 256 - Filter Length: 512

Apache HTTP Server

Concurrent Requests: 1000

Liquid-DSP

Threads: 128 - Buffer Length: 256 - Filter Length: 512

Liquid-DSP

Threads: 64 - Buffer Length: 256 - Filter Length: 512

Liquid-DSP

Threads: 256 - Buffer Length: 256 - Filter Length: 57

Liquid-DSP

Threads: 128 - Buffer Length: 256 - Filter Length: 57

Liquid-DSP

Threads: 128 - Buffer Length: 256 - Filter Length: 32

Liquid-DSP

Threads: 64 - Buffer Length: 256 - Filter Length: 32

Liquid-DSP

Threads: 32 - Buffer Length: 256 - Filter Length: 32

Liquid-DSP

Threads: 32 - Buffer Length: 256 - Filter Length: 57

VVenC

Video Input: Bosphorus 1080p - Video Preset: Faster

SVT-AV1

Encoder Mode: Preset 4 - Input: Bosphorus 4K

Redis

Test: SET - Parallel Connections: 50

uvg266

Video Input: Bosphorus 4K - Video Preset: Slow

Redis

Test: GET - Parallel Connections: 500

QuantLib

Configuration: Single-Threaded

Xmrig

Variant: Wownero - Hash Count: 1M

Redis

Test: GET - Parallel Connections: 50

OpenFOAM

Input: drivaerFastback, Small Mesh Size - Execution Time

OpenFOAM

Input: drivaerFastback, Small Mesh Size - Mesh Time

SVT-AV1

Encoder Mode: Preset 13 - Input: Bosphorus 4K

uvg266

Video Input: Bosphorus 4K - Video Preset: Medium

uvg266

Video Input: Bosphorus 1080p - Video Preset: Super Fast

Xmrig

Variant: CryptoNight-Femto UPX2 - Hash Count: 1M

Kvazaar

Video Input: Bosphorus 4K - Video Preset: Slow

Xmrig

Variant: KawPow - Hash Count: 1M

Xmrig

Variant: Monero - Hash Count: 1M