7f32 feb
AMD EPYC 7F32 8-Core testing with a ASRockRack EPYCD8 (P2.40 BIOS) and ASPEED on Debian 11 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2302171-NE-7F32FEB4497&gru.
dav1d
Video Input: Chimera 1080p
dav1d
Video Input: Summer Nature 4K
dav1d
Video Input: Summer Nature 1080p
dav1d
Video Input: Chimera 1080p 10-bit
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
Embree
Binary: Pathtracer - Model: Crown
Embree
Binary: Pathtracer ISPC - Model: Crown
Embree
Binary: Pathtracer - Model: Asian Dragon
Embree
Binary: Pathtracer - Model: Asian Dragon Obj
Embree
Binary: Pathtracer ISPC - Model: Asian Dragon
Embree
Binary: Pathtracer ISPC - Model: Asian Dragon Obj
VP9 libvpx Encoding
Speed: Speed 0 - Input: Bosphorus 4K
VP9 libvpx Encoding
Speed: Speed 5 - Input: Bosphorus 4K
VP9 libvpx Encoding
Speed: Speed 0 - Input: Bosphorus 1080p
VP9 libvpx Encoding
Speed: Speed 5 - Input: Bosphorus 1080p
VVenC
Video Input: Bosphorus 4K - Video Preset: Fast
VVenC
Video Input: Bosphorus 4K - Video Preset: Faster
VVenC
Video Input: Bosphorus 1080p - Video Preset: Fast
VVenC
Video Input: Bosphorus 1080p - Video Preset: Faster
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 Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - 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: Synchronous Single-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 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: 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: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Segmentation, 90% Pruned YOLACT Pruned - 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: 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: Synchronous Single-Stream
OpenEMS
Test: pyEMS Coupler
OpenEMS
Test: openEMS MSL_NotchFilter
GROMACS
Implementation: MPI CPU - Input: water_GMX50_bare
RocksDB
Test: Random Fill
RocksDB
Test: Random Read
RocksDB
Test: Update Random
RocksDB
Test: Sequential Fill
RocksDB
Test: Random Fill Sync
RocksDB
Test: Read While Writing
RocksDB
Test: Read Random Write Random
PostgreSQL
Scaling Factor: 1 - Clients: 1 - Mode: Read Only
PostgreSQL
Scaling Factor: 1 - Clients: 1 - Mode: Read Write
PostgreSQL
Scaling Factor: 1 - Clients: 50 - Mode: Read Only
PostgreSQL
Scaling Factor: 1 - Clients: 100 - Mode: Read Only
PostgreSQL
Scaling Factor: 1 - Clients: 250 - Mode: Read Only
PostgreSQL
Scaling Factor: 1 - Clients: 50 - Mode: Read Write
PostgreSQL
Scaling Factor: 1 - Clients: 500 - Mode: Read Only
PostgreSQL
Scaling Factor: 1 - Clients: 800 - Mode: Read Only
PostgreSQL
Scaling Factor: 100 - Clients: 1 - Mode: Read Only
PostgreSQL
Scaling Factor: 1 - Clients: 100 - Mode: Read Write
PostgreSQL
Scaling Factor: 1 - Clients: 1000 - Mode: Read Only
PostgreSQL
Scaling Factor: 1 - Clients: 250 - Mode: Read Write
PostgreSQL
Scaling Factor: 1 - Clients: 500 - Mode: Read Write
PostgreSQL
Scaling Factor: 1 - Clients: 800 - Mode: Read Write
PostgreSQL
Scaling Factor: 100 - Clients: 1 - Mode: Read Write
PostgreSQL
Scaling Factor: 100 - Clients: 50 - Mode: Read Only
PostgreSQL
Scaling Factor: 1 - Clients: 1000 - Mode: Read Write
PostgreSQL
Scaling Factor: 100 - Clients: 100 - Mode: Read Only
PostgreSQL
Scaling Factor: 100 - Clients: 250 - Mode: Read Only
PostgreSQL
Scaling Factor: 100 - Clients: 50 - Mode: Read Write
PostgreSQL
Scaling Factor: 100 - Clients: 500 - Mode: Read Only
PostgreSQL
Scaling Factor: 100 - Clients: 800 - Mode: Read Only
PostgreSQL
Scaling Factor: 100 - Clients: 100 - Mode: Read Write
PostgreSQL
Scaling Factor: 100 - Clients: 1000 - Mode: Read Only
PostgreSQL
Scaling Factor: 100 - Clients: 250 - Mode: Read Write
PostgreSQL
Scaling Factor: 100 - Clients: 500 - Mode: Read Write
PostgreSQL
Scaling Factor: 100 - Clients: 800 - Mode: Read Write
PostgreSQL
Scaling Factor: 100 - Clients: 1000 - Mode: Read Write
PostgreSQL
Scaling Factor: 1 - Clients: 1 - Mode: Read Only - Average Latency
PostgreSQL
Scaling Factor: 1 - Clients: 1 - Mode: Read Write - Average Latency
PostgreSQL
Scaling Factor: 1 - Clients: 50 - Mode: Read Only - Average Latency
PostgreSQL
Scaling Factor: 1 - Clients: 100 - Mode: Read Only - Average Latency
PostgreSQL
Scaling Factor: 1 - Clients: 250 - Mode: Read Only - Average Latency
PostgreSQL
Scaling Factor: 1 - Clients: 50 - Mode: Read Write - Average Latency
PostgreSQL
Scaling Factor: 1 - Clients: 500 - Mode: Read Only - Average Latency
PostgreSQL
Scaling Factor: 1 - Clients: 800 - Mode: Read Only - Average Latency
PostgreSQL
Scaling Factor: 100 - Clients: 1 - Mode: Read Only - Average Latency
PostgreSQL
Scaling Factor: 1 - Clients: 100 - Mode: Read Write - Average Latency
PostgreSQL
Scaling Factor: 1 - Clients: 1000 - Mode: Read Only - Average Latency
PostgreSQL
Scaling Factor: 1 - Clients: 250 - Mode: Read Write - Average Latency
PostgreSQL
Scaling Factor: 1 - Clients: 500 - Mode: Read Write - Average Latency
PostgreSQL
Scaling Factor: 1 - Clients: 800 - Mode: Read Write - Average Latency
PostgreSQL
Scaling Factor: 100 - Clients: 1 - Mode: Read Write - Average Latency
PostgreSQL
Scaling Factor: 100 - Clients: 50 - Mode: Read Only - Average Latency
PostgreSQL
Scaling Factor: 1 - Clients: 1000 - Mode: Read Write - Average Latency
PostgreSQL
Scaling Factor: 100 - Clients: 100 - Mode: Read Only - Average Latency
PostgreSQL
Scaling Factor: 100 - Clients: 250 - Mode: Read Only - Average Latency
PostgreSQL
Scaling Factor: 100 - Clients: 50 - Mode: Read Write - Average Latency
PostgreSQL
Scaling Factor: 100 - Clients: 500 - Mode: Read Only - Average Latency
PostgreSQL
Scaling Factor: 100 - Clients: 800 - Mode: Read Only - Average Latency
PostgreSQL
Scaling Factor: 100 - Clients: 100 - Mode: Read Write - Average Latency
PostgreSQL
Scaling Factor: 100 - Clients: 1000 - Mode: Read Only - Average Latency
PostgreSQL
Scaling Factor: 100 - Clients: 250 - Mode: Read Write - Average Latency
PostgreSQL
Scaling Factor: 100 - Clients: 500 - Mode: Read Write - Average Latency
PostgreSQL
Scaling Factor: 100 - Clients: 800 - Mode: Read Write - Average Latency
PostgreSQL
Scaling Factor: 100 - Clients: 1000 - Mode: Read Write - Average Latency
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 Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - 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: Synchronous Single-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 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: 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: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream
Neural Magic DeepSparse
Model: CV Segmentation, 90% Pruned YOLACT Pruned - 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: 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: Synchronous Single-Stream
Apache Spark
Row Count: 1000000 - Partitions: 100 - SHA-512 Benchmark Time
Apache Spark
Row Count: 1000000 - Partitions: 100 - Calculate Pi Benchmark
Apache Spark
Row Count: 1000000 - Partitions: 100 - Calculate Pi Benchmark Using Dataframe
Apache Spark
Row Count: 1000000 - Partitions: 100 - Group By Test Time
Apache Spark
Row Count: 1000000 - Partitions: 100 - Repartition Test Time
Apache Spark
Row Count: 1000000 - Partitions: 100 - Inner Join Test Time
Apache Spark
Row Count: 1000000 - Partitions: 100 - Broadcast Inner Join Test Time
Apache Spark
Row Count: 1000000 - Partitions: 500 - SHA-512 Benchmark Time
Apache Spark
Row Count: 1000000 - Partitions: 500 - Calculate Pi Benchmark
Apache Spark
Row Count: 1000000 - Partitions: 500 - Calculate Pi Benchmark Using Dataframe
Apache Spark
Row Count: 1000000 - Partitions: 500 - Group By Test Time
Apache Spark
Row Count: 1000000 - Partitions: 500 - Repartition Test Time
Apache Spark
Row Count: 1000000 - Partitions: 500 - Inner Join Test Time
Apache Spark
Row Count: 1000000 - Partitions: 500 - Broadcast Inner Join Test Time
Apache Spark
Row Count: 1000000 - Partitions: 1000 - SHA-512 Benchmark Time
Apache Spark
Row Count: 1000000 - Partitions: 1000 - Calculate Pi Benchmark
Apache Spark
Row Count: 1000000 - Partitions: 1000 - Calculate Pi Benchmark Using Dataframe
Apache Spark
Row Count: 1000000 - Partitions: 1000 - Group By Test Time
Apache Spark
Row Count: 1000000 - Partitions: 1000 - Repartition Test Time
Apache Spark
Row Count: 1000000 - Partitions: 1000 - Inner Join Test Time
Apache Spark
Row Count: 1000000 - Partitions: 1000 - Broadcast Inner Join Test Time
Apache Spark
Row Count: 1000000 - Partitions: 2000 - SHA-512 Benchmark Time
Apache Spark
Row Count: 1000000 - Partitions: 2000 - Calculate Pi Benchmark
Apache Spark
Row Count: 1000000 - Partitions: 2000 - Calculate Pi Benchmark Using Dataframe
Apache Spark
Row Count: 1000000 - Partitions: 2000 - Group By Test Time
Apache Spark
Row Count: 1000000 - Partitions: 2000 - Repartition Test Time
Apache Spark
Row Count: 1000000 - Partitions: 2000 - Inner Join Test Time
Apache Spark
Row Count: 1000000 - Partitions: 2000 - Broadcast Inner Join Test Time
Phoronix Test Suite v10.8.5