AMD EPYC 7F32 8-Core testing with a ASRockRack EPYCD8 (P2.40 BIOS) and ASPEED on Debian 11 via the Phoronix Test Suite.
Compare your own system(s) to this result file with the
Phoronix Test Suite by running the command:
phoronix-test-suite benchmark 2302171-NE-7F32FEB4497
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.
a:
Processor: AMD EPYC 7F32 8-Core @ 3.70GHz (8 Cores / 16 Threads), Motherboard: ASRockRack EPYCD8 (P2.40 BIOS), Chipset: AMD Starship/Matisse, Memory: 28GB, Disk: Samsung SSD 970 EVO Plus 250GB, Graphics: ASPEED, Network: 2 x Intel I350
OS: Debian 11, Kernel: 5.10.0-10-amd64 (x86_64), Desktop: GNOME Shell 3.38.6, Display Server: X Server, Compiler: GCC 10.2.1 20210110, File-System: ext4, Screen Resolution: 1024x768
b:
Processor: AMD EPYC 7F32 8-Core @ 3.70GHz (8 Cores / 16 Threads), Motherboard: ASRockRack EPYCD8 (P2.40 BIOS), Chipset: AMD Starship/Matisse, Memory: 28GB, Disk: Samsung SSD 970 EVO Plus 250GB, Graphics: ASPEED, Network: 2 x Intel I350
OS: Debian 11, Kernel: 5.10.0-10-amd64 (x86_64), Desktop: GNOME Shell 3.38.6, Display Server: X Server, Compiler: GCC 10.2.1 20210110, File-System: ext4, Screen Resolution: 1024x768
OpenEMS 0.0.35-86
Test: pyEMS Coupler
MCells/s > Higher Is Better
a . 20.99 |====================================================================
b . 20.97 |====================================================================
OpenEMS 0.0.35-86
Test: openEMS MSL_NotchFilter
MCells/s > Higher Is Better
a . 43.28 |==================================================================
b . 44.47 |====================================================================
Neural Magic DeepSparse 1.3.2
Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream
items/sec > Higher Is Better
a . 6.3968 |===================================================================
b . 6.3828 |===================================================================
Neural Magic DeepSparse 1.3.2
Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream
ms/batch < Lower Is Better
a . 618.83 |===================================================================
b . 619.46 |===================================================================
Neural Magic DeepSparse 1.3.2
Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream
items/sec > Higher Is Better
a . 5.4210 |===================================================================
b . 5.3209 |==================================================================
Neural Magic DeepSparse 1.3.2
Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream
ms/batch < Lower Is Better
a . 184.46 |==================================================================
b . 187.93 |===================================================================
Neural Magic DeepSparse 1.3.2
Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream
items/sec > Higher Is Better
a . 59.38 |====================================================================
b . 59.57 |====================================================================
Neural Magic DeepSparse 1.3.2
Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream
ms/batch < Lower Is Better
a . 67.30 |====================================================================
b . 67.04 |====================================================================
Neural Magic DeepSparse 1.3.2
Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Synchronous Single-Stream
items/sec > Higher Is Better
a . 33.53 |================================================================
b . 35.64 |====================================================================
Neural Magic DeepSparse 1.3.2
Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Synchronous Single-Stream
ms/batch < Lower Is Better
a . 29.81 |====================================================================
b . 28.05 |================================================================
Neural Magic DeepSparse 1.3.2
Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream
items/sec > Higher Is Better
a . 22.42 |===================================================================
b . 22.59 |====================================================================
Neural Magic DeepSparse 1.3.2
Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream
ms/batch < Lower Is Better
a . 177.91 |===================================================================
b . 176.59 |===================================================================
Neural Magic DeepSparse 1.3.2
Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream
items/sec > Higher Is Better
a . 12.09 |================================================================
b . 12.91 |====================================================================
Neural Magic DeepSparse 1.3.2
Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream
ms/batch < Lower Is Better
a . 82.73 |====================================================================
b . 77.42 |================================================================
Neural Magic DeepSparse 1.3.2
Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream
items/sec > Higher Is Better
a . 36.49 |====================================================================
b . 36.22 |===================================================================
Neural Magic DeepSparse 1.3.2
Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream
ms/batch < Lower Is Better
a . 109.45 |==================================================================
b . 110.31 |===================================================================
Neural Magic DeepSparse 1.3.2
Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream
items/sec > Higher Is Better
a . 26.15 |===================================================================
b . 26.37 |====================================================================
Neural Magic DeepSparse 1.3.2
Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream
ms/batch < Lower Is Better
a . 38.22 |====================================================================
b . 37.91 |===================================================================
Neural Magic DeepSparse 1.3.2
Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream
items/sec > Higher Is Better
a . 72.28 |====================================================================
b . 71.54 |===================================================================
Neural Magic DeepSparse 1.3.2
Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream
ms/batch < Lower Is Better
a . 55.27 |===================================================================
b . 55.85 |====================================================================
Neural Magic DeepSparse 1.3.2
Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream
items/sec > Higher Is Better
a . 52.31 |====================================================================
b . 50.75 |==================================================================
Neural Magic DeepSparse 1.3.2
Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream
ms/batch < Lower Is Better
a . 19.11 |==================================================================
b . 19.70 |====================================================================
Neural Magic DeepSparse 1.3.2
Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream
items/sec > Higher Is Better
a . 50.37 |====================================================================
b . 50.16 |====================================================================
Neural Magic DeepSparse 1.3.2
Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream
ms/batch < Lower Is Better
a . 79.29 |====================================================================
b . 79.62 |====================================================================
Neural Magic DeepSparse 1.3.2
Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream
items/sec > Higher Is Better
a . 36.57 |====================================================================
b . 36.07 |===================================================================
Neural Magic DeepSparse 1.3.2
Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream
ms/batch < Lower Is Better
a . 27.34 |===================================================================
b . 27.72 |====================================================================
Neural Magic DeepSparse 1.3.2
Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream
items/sec > Higher Is Better
a . 8.0865 |==================================================================
b . 8.1627 |===================================================================
Neural Magic DeepSparse 1.3.2
Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream
ms/batch < Lower Is Better
a . 492.13 |===================================================================
b . 487.20 |==================================================================
Neural Magic DeepSparse 1.3.2
Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream
items/sec > Higher Is Better
a . 6.8129 |===================================================================
b . 6.8210 |===================================================================
Neural Magic DeepSparse 1.3.2
Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream
ms/batch < Lower Is Better
a . 146.76 |===================================================================
b . 146.59 |===================================================================
Neural Magic DeepSparse 1.3.2
Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream
items/sec > Higher Is Better
a . 25.55 |====================================================================
b . 25.27 |===================================================================
Neural Magic DeepSparse 1.3.2
Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream
ms/batch < Lower Is Better
a . 156.34 |==================================================================
b . 157.89 |===================================================================
Neural Magic DeepSparse 1.3.2
Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Stream
items/sec > Higher Is Better
a . 18.53 |====================================================================
b . 18.47 |====================================================================
Neural Magic DeepSparse 1.3.2
Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Stream
ms/batch < Lower Is Better
a . 53.96 |====================================================================
b . 54.12 |====================================================================
Neural Magic DeepSparse 1.3.2
Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream
items/sec > Higher Is Better
a . 6.4027 |===================================================================
b . 6.3771 |===================================================================
Neural Magic DeepSparse 1.3.2
Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream
ms/batch < Lower Is Better
a . 618.22 |===================================================================
b . 618.84 |===================================================================
Neural Magic DeepSparse 1.3.2
Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream
items/sec > Higher Is Better
a . 5.3727 |===================================================================
b . 5.3372 |===================================================================
Neural Magic DeepSparse 1.3.2
Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream
ms/batch < Lower Is Better
a . 186.12 |===================================================================
b . 187.36 |===================================================================
GROMACS 2023
Implementation: MPI CPU - Input: water_GMX50_bare
Ns Per Day > Higher Is Better
a . 1.244 |==================================================================
b . 1.283 |====================================================================
AOM AV1 3.6
Encoder Mode: Speed 0 Two-Pass - Input: Bosphorus 4K
Frames Per Second > Higher Is Better
a . 0.19 |=====================================================================
b . 0.19 |=====================================================================
AOM AV1 3.6
Encoder Mode: Speed 4 Two-Pass - Input: Bosphorus 4K
Frames Per Second > Higher Is Better
a . 5.64 |=====================================================================
b . 5.65 |=====================================================================
AOM AV1 3.6
Encoder Mode: Speed 6 Realtime - Input: Bosphorus 4K
Frames Per Second > Higher Is Better
a . 45.97 |===================================================================
b . 46.60 |====================================================================
AOM AV1 3.6
Encoder Mode: Speed 6 Two-Pass - Input: Bosphorus 4K
Frames Per Second > Higher Is Better
a . 9.56 |=====================================================================
b . 9.53 |=====================================================================
AOM AV1 3.6
Encoder Mode: Speed 8 Realtime - Input: Bosphorus 4K
Frames Per Second > Higher Is Better
a . 37.74 |===================================================================
b . 38.13 |====================================================================
AOM AV1 3.6
Encoder Mode: Speed 9 Realtime - Input: Bosphorus 4K
Frames Per Second > Higher Is Better
a . 45.36 |================================================================
b . 48.38 |====================================================================
AOM AV1 3.6
Encoder Mode: Speed 10 Realtime - Input: Bosphorus 4K
Frames Per Second > Higher Is Better
a . 44.60 |==================================================================
b . 46.21 |====================================================================
AOM AV1 3.6
Encoder Mode: Speed 0 Two-Pass - Input: Bosphorus 1080p
Frames Per Second > Higher Is Better
a . 0.54 |=====================================================================
b . 0.54 |=====================================================================
AOM AV1 3.6
Encoder Mode: Speed 4 Two-Pass - Input: Bosphorus 1080p
Frames Per Second > Higher Is Better
a . 12.30 |====================================================================
b . 12.35 |====================================================================
AOM AV1 3.6
Encoder Mode: Speed 6 Realtime - Input: Bosphorus 1080p
Frames Per Second > Higher Is Better
a . 107.42 |===================================================================
b . 100.54 |===============================================================
AOM AV1 3.6
Encoder Mode: Speed 6 Two-Pass - Input: Bosphorus 1080p
Frames Per Second > Higher Is Better
a . 28.80 |====================================================================
b . 28.22 |===================================================================
AOM AV1 3.6
Encoder Mode: Speed 8 Realtime - Input: Bosphorus 1080p
Frames Per Second > Higher Is Better
a . 101.40 |===================================================================
b . 95.22 |===============================================================
AOM AV1 3.6
Encoder Mode: Speed 9 Realtime - Input: Bosphorus 1080p
Frames Per Second > Higher Is Better
a . 114.06 |==================================================================
b . 115.24 |===================================================================
AOM AV1 3.6
Encoder Mode: Speed 10 Realtime - Input: Bosphorus 1080p
Frames Per Second > Higher Is Better
a . 125.49 |==================================================================
b . 126.50 |===================================================================
VP9 libvpx Encoding 1.13
Speed: Speed 0 - Input: Bosphorus 4K
Frames Per Second > Higher Is Better
a . 5.42 |=====================================================================
b . 5.44 |=====================================================================
VP9 libvpx Encoding 1.13
Speed: Speed 5 - Input: Bosphorus 4K
Frames Per Second > Higher Is Better
a . 9.80 |=====================================================================
b . 9.61 |====================================================================
VP9 libvpx Encoding 1.13
Speed: Speed 0 - Input: Bosphorus 1080p
Frames Per Second > Higher Is Better
a . 11.26 |====================================================================
b . 11.01 |==================================================================
VP9 libvpx Encoding 1.13
Speed: Speed 5 - Input: Bosphorus 1080p
Frames Per Second > Higher Is Better
a . 23.93 |====================================================================
b . 23.25 |==================================================================
dav1d 1.1
Video Input: Chimera 1080p
FPS > Higher Is Better
a . 390.36 |===================================================================
b . 390.37 |===================================================================
dav1d 1.1
Video Input: Summer Nature 4K
FPS > Higher Is Better
a . 170.85 |================================================================
b . 178.99 |===================================================================
dav1d 1.1
Video Input: Summer Nature 1080p
FPS > Higher Is Better
a . 612.98 |===================================================================
b . 616.71 |===================================================================
dav1d 1.1
Video Input: Chimera 1080p 10-bit
FPS > Higher Is Better
a . 366.43 |==================================================================
b . 369.21 |===================================================================
VVenC 1.7
Video Input: Bosphorus 4K - Video Preset: Fast
Frames Per Second > Higher Is Better
a . 2.72 |=====================================================================
b . 2.71 |=====================================================================
VVenC 1.7
Video Input: Bosphorus 4K - Video Preset: Faster
Frames Per Second > Higher Is Better
a . 6.274 |====================================================================
b . 6.085 |==================================================================
VVenC 1.7
Video Input: Bosphorus 1080p - Video Preset: Fast
Frames Per Second > Higher Is Better
a . 7.229 |====================================================================
b . 7.257 |====================================================================
VVenC 1.7
Video Input: Bosphorus 1080p - Video Preset: Faster
Frames Per Second > Higher Is Better
a . 17.60 |====================================================================
b . 17.60 |====================================================================
Embree 4.0
Binary: Pathtracer - Model: Crown
Frames Per Second > Higher Is Better
a . 9.5705 |=================================================================
b . 9.8828 |===================================================================
Embree 4.0
Binary: Pathtracer ISPC - Model: Crown
Frames Per Second > Higher Is Better
a . 9.3491 |===================================================================
b . 9.3296 |===================================================================
Embree 4.0
Binary: Pathtracer - Model: Asian Dragon
Frames Per Second > Higher Is Better
a . 10.54 |==================================================================
b . 10.81 |====================================================================
Embree 4.0
Binary: Pathtracer - Model: Asian Dragon Obj
Frames Per Second > Higher Is Better
a . 9.7218 |===================================================================
b . 9.7600 |===================================================================
Embree 4.0
Binary: Pathtracer ISPC - Model: Asian Dragon
Frames Per Second > Higher Is Better
a . 10.88 |====================================================================
b . 10.79 |===================================================================
Embree 4.0
Binary: Pathtracer ISPC - Model: Asian Dragon Obj
Frames Per Second > Higher Is Better
a . 9.3827 |===================================================================
b . 9.3503 |===================================================================
Apache Spark 3.3
Row Count: 1000000 - Partitions: 100 - SHA-512 Benchmark Time
Seconds < Lower Is Better
a . 4.03 |=====================================================================
b . 4.04 |=====================================================================
Apache Spark 3.3
Row Count: 1000000 - Partitions: 100 - Calculate Pi Benchmark
Seconds < Lower Is Better
a . 188.34 |===================================================================
b . 187.45 |===================================================================
Apache Spark 3.3
Row Count: 1000000 - Partitions: 100 - Calculate Pi Benchmark Using Dataframe
Seconds < Lower Is Better
a . 11.49 |====================================================================
b . 11.52 |====================================================================
Apache Spark 3.3
Row Count: 1000000 - Partitions: 100 - Group By Test Time
Seconds < Lower Is Better
a . 4.64 |=====================================================================
b . 4.59 |====================================================================
Apache Spark 3.3
Row Count: 1000000 - Partitions: 100 - Repartition Test Time
Seconds < Lower Is Better
a . 2.00 |====================================================================
b . 2.02 |=====================================================================
Apache Spark 3.3
Row Count: 1000000 - Partitions: 100 - Inner Join Test Time
Seconds < Lower Is Better
a . 2.13 |=====================================================================
b . 2.05 |==================================================================
Apache Spark 3.3
Row Count: 1000000 - Partitions: 100 - Broadcast Inner Join Test Time
Seconds < Lower Is Better
a . 1.93 |=====================================================================
b . 1.80 |================================================================
Apache Spark 3.3
Row Count: 1000000 - Partitions: 500 - SHA-512 Benchmark Time
Seconds < Lower Is Better
a . 4.15 |=====================================================================
b . 4.13 |=====================================================================
Apache Spark 3.3
Row Count: 1000000 - Partitions: 500 - Calculate Pi Benchmark
Seconds < Lower Is Better
a . 189.28 |===================================================================
b . 189.00 |===================================================================
Apache Spark 3.3
Row Count: 1000000 - Partitions: 500 - Calculate Pi Benchmark Using Dataframe
Seconds < Lower Is Better
a . 11.39 |==================================================================
b . 11.69 |====================================================================
Apache Spark 3.3
Row Count: 1000000 - Partitions: 500 - Group By Test Time
Seconds < Lower Is Better
a . 5.05 |=====================================================================
b . 5.02 |=====================================================================
Apache Spark 3.3
Row Count: 1000000 - Partitions: 500 - Repartition Test Time
Seconds < Lower Is Better
a . 1.96 |=============================================================
b . 2.23 |=====================================================================
Apache Spark 3.3
Row Count: 1000000 - Partitions: 500 - Inner Join Test Time
Seconds < Lower Is Better
a . 2.30 |================================================================
b . 2.49 |=====================================================================
Apache Spark 3.3
Row Count: 1000000 - Partitions: 500 - Broadcast Inner Join Test Time
Seconds < Lower Is Better
a . 2.07 |=====================================================================
b . 1.91 |================================================================
Apache Spark 3.3
Row Count: 1000000 - Partitions: 1000 - SHA-512 Benchmark Time
Seconds < Lower Is Better
a . 4.32 |=====================================================================
b . 4.29 |=====================================================================
Apache Spark 3.3
Row Count: 1000000 - Partitions: 1000 - Calculate Pi Benchmark
Seconds < Lower Is Better
a . 186.61 |===================================================================
b . 185.93 |===================================================================
Apache Spark 3.3
Row Count: 1000000 - Partitions: 1000 - Calculate Pi Benchmark Using Dataframe
Seconds < Lower Is Better
a . 11.43 |===================================================================
b . 11.54 |====================================================================
Apache Spark 3.3
Row Count: 1000000 - Partitions: 1000 - Group By Test Time
Seconds < Lower Is Better
a . 5.59 |=====================================================================
b . 5.31 |==================================================================
Apache Spark 3.3
Row Count: 1000000 - Partitions: 1000 - Repartition Test Time
Seconds < Lower Is Better
a . 2.25 |=====================================================================
b . 2.22 |====================================================================
Apache Spark 3.3
Row Count: 1000000 - Partitions: 1000 - Inner Join Test Time
Seconds < Lower Is Better
a . 2.77 |=====================================================================
b . 2.43 |=============================================================
Apache Spark 3.3
Row Count: 1000000 - Partitions: 1000 - Broadcast Inner Join Test Time
Seconds < Lower Is Better
a . 2.17651277 |==========================================================
b . 2.38000000 |===============================================================
Apache Spark 3.3
Row Count: 1000000 - Partitions: 2000 - SHA-512 Benchmark Time
Seconds < Lower Is Better
a . 4.74 |====================================================================
b . 4.78 |=====================================================================
Apache Spark 3.3
Row Count: 1000000 - Partitions: 2000 - Calculate Pi Benchmark
Seconds < Lower Is Better
a . 186.58 |===================================================================
b . 186.16 |===================================================================
Apache Spark 3.3
Row Count: 1000000 - Partitions: 2000 - Calculate Pi Benchmark Using Dataframe
Seconds < Lower Is Better
a . 11.51 |====================================================================
b . 11.40 |===================================================================
Apache Spark 3.3
Row Count: 1000000 - Partitions: 2000 - Group By Test Time
Seconds < Lower Is Better
a . 5.79 |=====================================================================
b . 5.77 |=====================================================================
Apache Spark 3.3
Row Count: 1000000 - Partitions: 2000 - Repartition Test Time
Seconds < Lower Is Better
a . 2.753324538 |==============================================================
b . 2.690000000 |=============================================================
Apache Spark 3.3
Row Count: 1000000 - Partitions: 2000 - Inner Join Test Time
Seconds < Lower Is Better
a . 3.18 |=====================================================================
b . 3.01 |=================================================================
Apache Spark 3.3
Row Count: 1000000 - Partitions: 2000 - Broadcast Inner Join Test Time
Seconds < Lower Is Better
a . 2.39 |=============================================================
b . 2.72 |=====================================================================
ClickHouse 22.12.3.5
Queries Per Minute, Geo Mean > Higher Is Better
RocksDB 7.9.2
Test: Random Fill
Op/s > Higher Is Better
a . 530099 |===================================================================
b . 528550 |===================================================================
RocksDB 7.9.2
Test: Random Read
Op/s > Higher Is Better
a . 35559141 |================================================================
b . 36110424 |=================================================================
RocksDB 7.9.2
Test: Update Random
Op/s > Higher Is Better
a . 346409 |===================================================================
b . 347469 |===================================================================
RocksDB 7.9.2
Test: Sequential Fill
Op/s > Higher Is Better
a . 589310 |==================================================================
b . 595266 |===================================================================
RocksDB 7.9.2
Test: Random Fill Sync
Op/s > Higher Is Better
a . 2852 |=====================================================================
b . 2857 |=====================================================================
RocksDB 7.9.2
Test: Read While Writing
Op/s > Higher Is Better
a . 1490922 |==================================================================
b . 1401161 |==============================================================
RocksDB 7.9.2
Test: Read Random Write Random
Op/s > Higher Is Better
a . 1146165 |==================================================================
b . 1152478 |==================================================================
PostgreSQL 15
Scaling Factor: 1 - Clients: 1 - Mode: Read Only
TPS > Higher Is Better
a . 61593 |=================================================================
b . 64239 |====================================================================
PostgreSQL 15
Scaling Factor: 1 - Clients: 1 - Mode: Read Only - Average Latency
ms < Lower Is Better
a . 0.016 |====================================================================
b . 0.016 |====================================================================
PostgreSQL 15
Scaling Factor: 1 - Clients: 1 - Mode: Read Write
TPS > Higher Is Better
a . 708 |======================================================================
b . 703 |======================================================================
PostgreSQL 15
Scaling Factor: 1 - Clients: 1 - Mode: Read Write - Average Latency
ms < Lower Is Better
a . 1.413 |====================================================================
b . 1.423 |====================================================================
PostgreSQL 15
Scaling Factor: 1 - Clients: 50 - Mode: Read Only
TPS > Higher Is Better
a . 620983 |===================================================================
b . 618290 |===================================================================
PostgreSQL 15
Scaling Factor: 1 - Clients: 50 - Mode: Read Only - Average Latency
ms < Lower Is Better
a . 0.081 |====================================================================
b . 0.081 |====================================================================
PostgreSQL 15
Scaling Factor: 1 - Clients: 100 - Mode: Read Only
TPS > Higher Is Better
a . 627441 |=================================================================
b . 645705 |===================================================================
PostgreSQL 15
Scaling Factor: 1 - Clients: 100 - Mode: Read Only - Average Latency
ms < Lower Is Better
a . 0.159 |====================================================================
b . 0.155 |==================================================================
PostgreSQL 15
Scaling Factor: 1 - Clients: 250 - Mode: Read Only
TPS > Higher Is Better
a . 606075 |==================================================================
b . 617509 |===================================================================
PostgreSQL 15
Scaling Factor: 1 - Clients: 250 - Mode: Read Only - Average Latency
ms < Lower Is Better
a . 0.412 |====================================================================
b . 0.405 |===================================================================
PostgreSQL 15
Scaling Factor: 1 - Clients: 50 - Mode: Read Write
TPS > Higher Is Better
a . 678 |======================================================================
b . 675 |======================================================================
PostgreSQL 15
Scaling Factor: 1 - Clients: 50 - Mode: Read Write - Average Latency
ms < Lower Is Better
a . 73.72 |====================================================================
b . 74.05 |====================================================================
PostgreSQL 15
Scaling Factor: 1 - Clients: 500 - Mode: Read Only
TPS > Higher Is Better
a . 522138 |=============================================================
b . 571774 |===================================================================
PostgreSQL 15
Scaling Factor: 1 - Clients: 500 - Mode: Read Only - Average Latency
ms < Lower Is Better
a . 0.958 |====================================================================
b . 0.874 |==============================================================
PostgreSQL 15
Scaling Factor: 1 - Clients: 800 - Mode: Read Only
TPS > Higher Is Better
a . 499392 |===================================================================
b . 479473 |================================================================
PostgreSQL 15
Scaling Factor: 1 - Clients: 800 - Mode: Read Only - Average Latency
ms < Lower Is Better
a . 1.602 |=================================================================
b . 1.668 |====================================================================
PostgreSQL 15
Scaling Factor: 100 - Clients: 1 - Mode: Read Only
TPS > Higher Is Better
a . 54842 |===================================================================
b . 55389 |====================================================================
PostgreSQL 15
Scaling Factor: 100 - Clients: 1 - Mode: Read Only - Average Latency
ms < Lower Is Better
a . 0.018 |====================================================================
b . 0.018 |====================================================================
PostgreSQL 15
Scaling Factor: 1 - Clients: 100 - Mode: Read Write
TPS > Higher Is Better
a . 658 |======================================================================
b . 654 |======================================================================
PostgreSQL 15
Scaling Factor: 1 - Clients: 100 - Mode: Read Write - Average Latency
ms < Lower Is Better
a . 152.08 |===================================================================
b . 152.86 |===================================================================
PostgreSQL 15
Scaling Factor: 1 - Clients: 1000 - Mode: Read Only
TPS > Higher Is Better
a . 466800 |===================================================================
b . 450620 |=================================================================
PostgreSQL 15
Scaling Factor: 1 - Clients: 1000 - Mode: Read Only - Average Latency
ms < Lower Is Better
a . 2.142 |==================================================================
b . 2.219 |====================================================================
PostgreSQL 15
Scaling Factor: 1 - Clients: 250 - Mode: Read Write
TPS > Higher Is Better
a . 598 |====================================================================
b . 614 |======================================================================
PostgreSQL 15
Scaling Factor: 1 - Clients: 250 - Mode: Read Write - Average Latency
ms < Lower Is Better
a . 417.72 |===================================================================
b . 407.38 |=================================================================
PostgreSQL 15
Scaling Factor: 1 - Clients: 500 - Mode: Read Write
TPS > Higher Is Better
a . 509 |======================================================================
b . 488 |===================================================================
PostgreSQL 15
Scaling Factor: 1 - Clients: 500 - Mode: Read Write - Average Latency
ms < Lower Is Better
a . 982.95 |===============================================================
b . 1025.32 |==================================================================
PostgreSQL 15
Scaling Factor: 1 - Clients: 800 - Mode: Read Write
TPS > Higher Is Better
a . 326 |=====================================================================
b . 329 |======================================================================
PostgreSQL 15
Scaling Factor: 1 - Clients: 800 - Mode: Read Write - Average Latency
ms < Lower Is Better
a . 2457.45 |==================================================================
b . 2428.66 |=================================================================
PostgreSQL 15
Scaling Factor: 100 - Clients: 1 - Mode: Read Write
TPS > Higher Is Better
a . 425 |======================================================================
b . 424 |======================================================================
PostgreSQL 15
Scaling Factor: 100 - Clients: 1 - Mode: Read Write - Average Latency
ms < Lower Is Better
a . 2.355 |====================================================================
b . 2.360 |====================================================================
PostgreSQL 15
Scaling Factor: 100 - Clients: 50 - Mode: Read Only
TPS > Higher Is Better
a . 545224 |===================================================================
b . 531797 |=================================================================
PostgreSQL 15
Scaling Factor: 100 - Clients: 50 - Mode: Read Only - Average Latency
ms < Lower Is Better
a . 0.092 |===================================================================
b . 0.094 |====================================================================
PostgreSQL 15
Scaling Factor: 1 - Clients: 1000 - Mode: Read Write
TPS > Higher Is Better
a . 270 |======================================================================
b . 258 |===================================================================
PostgreSQL 15
Scaling Factor: 1 - Clients: 1000 - Mode: Read Write - Average Latency
ms < Lower Is Better
a . 3707.47 |===============================================================
b . 3876.57 |==================================================================
PostgreSQL 15
Scaling Factor: 100 - Clients: 100 - Mode: Read Only
TPS > Higher Is Better
a . 561050 |===================================================================
b . 563522 |===================================================================
PostgreSQL 15
Scaling Factor: 100 - Clients: 100 - Mode: Read Only - Average Latency
ms < Lower Is Better
a . 0.178 |====================================================================
b . 0.177 |====================================================================
PostgreSQL 15
Scaling Factor: 100 - Clients: 250 - Mode: Read Only
TPS > Higher Is Better
a . 550537 |===================================================================
b . 543855 |==================================================================
PostgreSQL 15
Scaling Factor: 100 - Clients: 250 - Mode: Read Only - Average Latency
ms < Lower Is Better
a . 0.454 |===================================================================
b . 0.460 |====================================================================
PostgreSQL 15
Scaling Factor: 100 - Clients: 50 - Mode: Read Write
TPS > Higher Is Better
a . 4856 |=====================================================================
b . 4516 |================================================================
PostgreSQL 15
Scaling Factor: 100 - Clients: 50 - Mode: Read Write - Average Latency
ms < Lower Is Better
a . 10.30 |===============================================================
b . 11.07 |====================================================================
PostgreSQL 15
Scaling Factor: 100 - Clients: 500 - Mode: Read Only
TPS > Higher Is Better
a . 491975 |===================================================================
b . 470230 |================================================================
PostgreSQL 15
Scaling Factor: 100 - Clients: 500 - Mode: Read Only - Average Latency
ms < Lower Is Better
a . 1.016 |=================================================================
b . 1.063 |====================================================================
PostgreSQL 15
Scaling Factor: 100 - Clients: 800 - Mode: Read Only
TPS > Higher Is Better
a . 446689 |=============================================================
b . 486710 |===================================================================
PostgreSQL 15
Scaling Factor: 100 - Clients: 800 - Mode: Read Only - Average Latency
ms < Lower Is Better
a . 1.791 |====================================================================
b . 1.644 |==============================================================
PostgreSQL 15
Scaling Factor: 100 - Clients: 100 - Mode: Read Write
TPS > Higher Is Better
a . 6893 |=====================================================================
b . 6055 |=============================================================
PostgreSQL 15
Scaling Factor: 100 - Clients: 100 - Mode: Read Write - Average Latency
ms < Lower Is Better
a . 14.51 |============================================================
b . 16.52 |====================================================================
PostgreSQL 15
Scaling Factor: 100 - Clients: 1000 - Mode: Read Only
TPS > Higher Is Better
a . 410670 |======================================================
b . 508680 |===================================================================
PostgreSQL 15
Scaling Factor: 100 - Clients: 1000 - Mode: Read Only - Average Latency
ms < Lower Is Better
a . 2.435 |====================================================================
b . 1.966 |=======================================================
PostgreSQL 15
Scaling Factor: 100 - Clients: 250 - Mode: Read Write
TPS > Higher Is Better
a . 8126 |=====================================================================
b . 7069 |============================================================
PostgreSQL 15
Scaling Factor: 100 - Clients: 250 - Mode: Read Write - Average Latency
ms < Lower Is Better
a . 30.77 |===========================================================
b . 35.37 |====================================================================
PostgreSQL 15
Scaling Factor: 100 - Clients: 500 - Mode: Read Write
TPS > Higher Is Better
a . 8425 |=====================================================================
b . 6839 |========================================================
PostgreSQL 15
Scaling Factor: 100 - Clients: 500 - Mode: Read Write - Average Latency
ms < Lower Is Better
a . 59.35 |=======================================================
b . 73.11 |====================================================================
PostgreSQL 15
Scaling Factor: 100 - Clients: 800 - Mode: Read Write
TPS > Higher Is Better
a . 8166 |=====================================================================
b . 7173 |=============================================================
PostgreSQL 15
Scaling Factor: 100 - Clients: 800 - Mode: Read Write - Average Latency
ms < Lower Is Better
a . 97.97 |===========================================================
b . 111.52 |===================================================================
PostgreSQL 15
Scaling Factor: 100 - Clients: 1000 - Mode: Read Write
TPS > Higher Is Better
a . 7792 |=====================================================================
b . 6889 |=============================================================
PostgreSQL 15
Scaling Factor: 100 - Clients: 1000 - Mode: Read Write - Average Latency
ms < Lower Is Better
a . 128.35 |===========================================================
b . 145.16 |===================================================================