AMD EPYC 8534P 64-Core testing with a AMD Cinnabar (RCB1009C BIOS) and ASPEED on Ubuntu 23.10 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 2403160-NE-KDLKF039836
kdlkf
AMD EPYC 8534P 64-Core testing with a AMD Cinnabar (RCB1009C BIOS) and ASPEED on Ubuntu 23.10 via the Phoronix Test Suite.
a:
Processor: AMD EPYC 8534P 64-Core @ 2.30GHz (64 Cores / 128 Threads), Motherboard: AMD Cinnabar (RCB1009C BIOS), Chipset: AMD Device 14a4, Memory: 6 x 32GB DRAM-4800MT/s Samsung M321R4GA0BB0-CQKMG, Disk: 3201GB Micron_7450_MTFDKCB3T2TFS, Graphics: ASPEED, Network: 2 x Broadcom NetXtreme BCM5720 PCIe
OS: Ubuntu 23.10, Kernel: 6.5.0-15-generic (x86_64), Desktop: GNOME Shell, Display Server: X Server 1.21.1.7, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1200
b:
Processor: AMD EPYC 8534P 64-Core @ 2.30GHz (64 Cores / 128 Threads), Motherboard: AMD Cinnabar (RCB1009C BIOS), Chipset: AMD Device 14a4, Memory: 6 x 32GB DRAM-4800MT/s Samsung M321R4GA0BB0-CQKMG, Disk: 3201GB Micron_7450_MTFDKCB3T2TFS, Graphics: ASPEED, Network: 2 x Broadcom NetXtreme BCM5720 PCIe
OS: Ubuntu 23.10, Kernel: 6.5.0-15-generic (x86_64), Desktop: GNOME Shell, Display Server: X Server 1.21.1.7, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1200
c:
Processor: AMD EPYC 8534P 64-Core @ 2.30GHz (64 Cores / 128 Threads), Motherboard: AMD Cinnabar (RCB1009C BIOS), Chipset: AMD Device 14a4, Memory: 6 x 32GB DRAM-4800MT/s Samsung M321R4GA0BB0-CQKMG, Disk: 3201GB Micron_7450_MTFDKCB3T2TFS, Graphics: ASPEED, Network: 2 x Broadcom NetXtreme BCM5720 PCIe
OS: Ubuntu 23.10, Kernel: 6.5.0-15-generic (x86_64), Desktop: GNOME Shell, Display Server: X Server 1.21.1.7, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1200
WavPack Audio Encoding 5.7
WAV To WavPack
Seconds < Lower Is Better
a . 6.067 |====================================================================
b . 6.066 |====================================================================
c . 6.059 |====================================================================
Google Draco 1.5.6
Model: Lion
ms < Lower Is Better
a . 6301 |=====================================================================
b . 6258 |=====================================================================
c . 6255 |====================================================================
Google Draco 1.5.6
Model: Church Facade
ms < Lower Is Better
a . 8195 |=====================================================================
b . 8069 |====================================================================
c . 8162 |=====================================================================
JPEG-XL Decoding libjxl 0.10.1
CPU Threads: 1
MP/s > Higher Is Better
a . 49.66 |====================================================================
b . 49.68 |====================================================================
c . 49.75 |====================================================================
JPEG-XL Decoding libjxl 0.10.1
CPU Threads: All
MP/s > Higher Is Better
a . 551.29 |===================================================================
b . 546.96 |==================================================================
c . 536.44 |=================================================================
JPEG-XL libjxl 0.10.1
Input: PNG - Quality: 80
MP/s > Higher Is Better
a . 42.81 |=================================================================
b . 40.41 |=============================================================
c . 45.02 |====================================================================
JPEG-XL libjxl 0.10.1
Input: PNG - Quality: 90
MP/s > Higher Is Better
a . 36.94 |============================================================
b . 41.75 |====================================================================
c . 37.53 |=============================================================
JPEG-XL libjxl 0.10.1
Input: JPEG - Quality: 80
MP/s > Higher Is Better
a . 40.43 |===============================================================
b . 43.88 |====================================================================
c . 40.66 |===============================================================
JPEG-XL libjxl 0.10.1
Input: JPEG - Quality: 90
MP/s > Higher Is Better
a . 39.59 |====================================================================
b . 38.18 |==================================================================
c . 38.07 |=================================================================
JPEG-XL libjxl 0.10.1
Input: PNG - Quality: 100
MP/s > Higher Is Better
a . 29.42 |====================================================================
b . 29.50 |====================================================================
c . 29.55 |====================================================================
JPEG-XL libjxl 0.10.1
Input: JPEG - Quality: 100
MP/s > Higher Is Better
a . 30.19 |====================================================================
b . 30.03 |====================================================================
c . 29.92 |===================================================================
Neural Magic DeepSparse 1.7
Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream
items/sec > Higher Is Better
a . 35.62 |====================================================================
b . 35.74 |====================================================================
c . 35.62 |====================================================================
Neural Magic DeepSparse 1.7
Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream
ms/batch < Lower Is Better
a . 881.71 |===================================================================
b . 883.06 |===================================================================
c . 883.40 |===================================================================
Neural Magic DeepSparse 1.7
Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream
items/sec > Higher Is Better
a . 29.72 |====================================================================
b . 29.71 |====================================================================
c . 29.72 |====================================================================
Neural Magic DeepSparse 1.7
Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream
ms/batch < Lower Is Better
a . 33.64 |====================================================================
b . 33.64 |====================================================================
c . 33.63 |====================================================================
Neural Magic DeepSparse 1.7
Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream
items/sec > Higher Is Better
a . 1442.79 |==================================================================
b . 1439.29 |==================================================================
c . 1440.70 |==================================================================
Neural Magic DeepSparse 1.7
Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream
ms/batch < Lower Is Better
a . 22.15 |====================================================================
b . 22.20 |====================================================================
c . 22.18 |====================================================================
Neural Magic DeepSparse 1.7
Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Stream
items/sec > Higher Is Better
a . 202.10 |==================================================================
b . 203.93 |===================================================================
c . 201.04 |==================================================================
Neural Magic DeepSparse 1.7
Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Stream
ms/batch < Lower Is Better
a . 4.9422 |===================================================================
b . 4.8985 |==================================================================
c . 4.9685 |===================================================================
Neural Magic DeepSparse 1.7
Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream
items/sec > Higher Is Better
a . 476.83 |===================================================================
b . 476.81 |===================================================================
c . 476.88 |===================================================================
Neural Magic DeepSparse 1.7
Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream
ms/batch < Lower Is Better
a . 66.99 |====================================================================
b . 66.99 |====================================================================
c . 67.04 |====================================================================
Neural Magic DeepSparse 1.7
Model: ResNet-50, Baseline - Scenario: Synchronous Single-Stream
items/sec > Higher Is Better
a . 187.28 |===================================================================
b . 187.20 |===================================================================
c . 187.46 |===================================================================
Neural Magic DeepSparse 1.7
Model: ResNet-50, Baseline - Scenario: Synchronous Single-Stream
ms/batch < Lower Is Better
a . 5.3331 |===================================================================
b . 5.3354 |===================================================================
c . 5.3276 |===================================================================
Neural Magic DeepSparse 1.7
Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream
items/sec > Higher Is Better
a . 3769.72 |==================================================================
b . 3790.80 |==================================================================
c . 3797.24 |==================================================================
Neural Magic DeepSparse 1.7
Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream
ms/batch < Lower Is Better
a . 8.4671 |===================================================================
b . 8.4216 |===================================================================
c . 8.4068 |===================================================================
Neural Magic DeepSparse 1.7
Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream
items/sec > Higher Is Better
a . 823.78 |===================================================================
b . 820.60 |===================================================================
c . 796.35 |=================================================================
Neural Magic DeepSparse 1.7
Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream
ms/batch < Lower Is Better
a . 1.2101 |=================================================================
b . 1.2147 |=================================================================
c . 1.2517 |===================================================================
Neural Magic DeepSparse 1.7
Model: Llama2 Chat 7b Quantized - Scenario: Asynchronous Multi-Stream
items/sec > Higher Is Better
a . 2.8545 |===================================================================
b . 2.8315 |==================================================================
c . 2.8225 |==================================================================
Neural Magic DeepSparse 1.7
Model: Llama2 Chat 7b Quantized - Scenario: Asynchronous Multi-Stream
ms/batch < Lower Is Better
a . 9727.68 |=================================================================
b . 9786.06 |==================================================================
c . 9824.21 |==================================================================
Neural Magic DeepSparse 1.7
Model: Llama2 Chat 7b Quantized - Scenario: Synchronous Single-Stream
items/sec > Higher Is Better
a . 14.38 |====================================================================
b . 14.35 |====================================================================
c . 14.36 |====================================================================
Neural Magic DeepSparse 1.7
Model: Llama2 Chat 7b Quantized - Scenario: Synchronous Single-Stream
ms/batch < Lower Is Better
a . 69.50 |====================================================================
b . 69.64 |====================================================================
c . 69.62 |====================================================================
Neural Magic DeepSparse 1.7
Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream
items/sec > Higher Is Better
a . 477.05 |===================================================================
b . 476.53 |===================================================================
c . 476.82 |===================================================================
Neural Magic DeepSparse 1.7
Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream
ms/batch < Lower Is Better
a . 66.97 |====================================================================
b . 67.01 |====================================================================
c . 66.99 |====================================================================
Neural Magic DeepSparse 1.7
Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream
items/sec > Higher Is Better
a . 186.97 |===================================================================
b . 187.00 |===================================================================
c . 186.67 |===================================================================
Neural Magic DeepSparse 1.7
Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream
ms/batch < Lower Is Better
a . 5.3423 |===================================================================
b . 5.3412 |===================================================================
c . 5.3508 |===================================================================
Neural Magic DeepSparse 1.7
Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream
items/sec > Higher Is Better
a . 213.94 |===================================================================
b . 212.47 |===================================================================
c . 213.20 |===================================================================
Neural Magic DeepSparse 1.7
Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream
ms/batch < Lower Is Better
a . 149.25 |===================================================================
b . 150.07 |===================================================================
c . 149.61 |===================================================================
Neural Magic DeepSparse 1.7
Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Stream
items/sec > Higher Is Better
a . 154.50 |===================================================================
b . 154.04 |===================================================================
c . 154.41 |===================================================================
Neural Magic DeepSparse 1.7
Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Stream
ms/batch < Lower Is Better
a . 6.4656 |===================================================================
b . 6.4846 |===================================================================
c . 6.4692 |===================================================================
Neural Magic DeepSparse 1.7
Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream
items/sec > Higher Is Better
a . 314.47 |===================================================================
b . 315.29 |===================================================================
c . 314.48 |===================================================================
Neural Magic DeepSparse 1.7
Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream
ms/batch < Lower Is Better
a . 101.53 |===================================================================
b . 101.31 |===================================================================
c . 101.63 |===================================================================
Neural Magic DeepSparse 1.7
Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream
items/sec > Higher Is Better
a . 136.97 |==================================================================
b . 137.78 |===================================================================
c . 138.06 |===================================================================
Neural Magic DeepSparse 1.7
Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream
ms/batch < Lower Is Better
a . 7.2927 |===================================================================
b . 7.2496 |===================================================================
c . 7.2356 |==================================================================
Neural Magic DeepSparse 1.7
Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream
items/sec > Higher Is Better
a . 62.35 |====================================================================
b . 62.30 |====================================================================
c . 62.39 |====================================================================
Neural Magic DeepSparse 1.7
Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream
ms/batch < Lower Is Better
a . 509.31 |===================================================================
b . 508.60 |===================================================================
c . 507.72 |===================================================================
Neural Magic DeepSparse 1.7
Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream
items/sec > Higher Is Better
a . 44.11 |====================================================================
b . 44.07 |====================================================================
c . 44.06 |====================================================================
Neural Magic DeepSparse 1.7
Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream
ms/batch < Lower Is Better
a . 22.65 |====================================================================
b . 22.67 |====================================================================
c . 22.67 |====================================================================
Neural Magic DeepSparse 1.7
Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream
items/sec > Higher Is Better
a . 685.23 |===================================================================
b . 686.68 |===================================================================
c . 683.77 |===================================================================
Neural Magic DeepSparse 1.7
Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream
ms/batch < Lower Is Better
a . 46.62 |====================================================================
b . 46.53 |====================================================================
c . 46.72 |====================================================================
Neural Magic DeepSparse 1.7
Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream
items/sec > Higher Is Better
a . 64.49 |====================================================================
b . 64.42 |====================================================================
c . 64.01 |===================================================================
Neural Magic DeepSparse 1.7
Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream
ms/batch < Lower Is Better
a . 15.49 |===================================================================
b . 15.51 |====================================================================
c . 15.61 |====================================================================
Neural Magic DeepSparse 1.7
Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream
items/sec > Higher Is Better
a . 35.76 |====================================================================
b . 35.59 |====================================================================
c . 35.68 |====================================================================
Neural Magic DeepSparse 1.7
Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream
ms/batch < Lower Is Better
a . 882.34 |===================================================================
b . 883.11 |===================================================================
c . 882.87 |===================================================================
Neural Magic DeepSparse 1.7
Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream
items/sec > Higher Is Better
a . 29.75 |====================================================================
b . 29.74 |====================================================================
c . 29.76 |====================================================================
Neural Magic DeepSparse 1.7
Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream
ms/batch < Lower Is Better
a . 33.60 |====================================================================
b . 33.61 |====================================================================
c . 33.60 |====================================================================
oneDNN 3.4
Harness: IP Shapes 1D - Engine: CPU
ms < Lower Is Better
a . 0.796392 |=================================================================
b . 0.791773 |================================================================
c . 0.802263 |=================================================================
oneDNN 3.4
Harness: IP Shapes 3D - Engine: CPU
ms < Lower Is Better
a . 0.990182 |=================================================================
b . 0.992488 |=================================================================
c . 0.991900 |=================================================================
oneDNN 3.4
Harness: Convolution Batch Shapes Auto - Engine: CPU
ms < Lower Is Better
a . 1.18235 |==================================================================
b . 1.18126 |==================================================================
c . 1.17292 |=================================================================
oneDNN 3.4
Harness: Deconvolution Batch shapes_1d - Engine: CPU
ms < Lower Is Better
a . 8.73308 |==================================================================
b . 8.78255 |==================================================================
c . 8.75546 |==================================================================
oneDNN 3.4
Harness: Deconvolution Batch shapes_3d - Engine: CPU
ms < Lower Is Better
a . 1.45255 |==================================================================
b . 1.45945 |==================================================================
c . 1.45433 |==================================================================
oneDNN 3.4
Harness: Recurrent Neural Network Training - Engine: CPU
ms < Lower Is Better
a . 746.67 |==================================================================
b . 752.48 |===================================================================
c . 745.41 |==================================================================
oneDNN 3.4
Harness: Recurrent Neural Network Inference - Engine: CPU
ms < Lower Is Better
a . 455.02 |===================================================================
b . 457.83 |===================================================================
c . 457.71 |===================================================================
OpenVINO 2024.0
Model: Face Detection FP16 - Device: CPU
FPS > Higher Is Better
a . 29.64 |====================================================================
b . 29.59 |====================================================================
c . 29.60 |====================================================================
OpenVINO 2024.0
Model: Face Detection FP16 - Device: CPU
ms < Lower Is Better
a . 1077.23 |==================================================================
b . 1076.61 |==================================================================
c . 1076.35 |==================================================================
OpenVINO 2024.0
Model: Person Detection FP16 - Device: CPU
FPS > Higher Is Better
a . 217.12 |===================================================================
b . 216.75 |===================================================================
c . 216.84 |===================================================================
OpenVINO 2024.0
Model: Person Detection FP16 - Device: CPU
ms < Lower Is Better
a . 147.21 |===================================================================
b . 147.48 |===================================================================
c . 147.42 |===================================================================
OpenVINO 2024.0
Model: Person Detection FP32 - Device: CPU
FPS > Higher Is Better
a . 216.99 |===================================================================
b . 217.07 |===================================================================
c . 216.93 |===================================================================
OpenVINO 2024.0
Model: Person Detection FP32 - Device: CPU
ms < Lower Is Better
a . 147.33 |===================================================================
b . 147.26 |===================================================================
c . 147.35 |===================================================================
OpenVINO 2024.0
Model: Vehicle Detection FP16 - Device: CPU
FPS > Higher Is Better
a . 1332.49 |==================================================================
b . 1330.83 |==================================================================
c . 1332.74 |==================================================================
OpenVINO 2024.0
Model: Vehicle Detection FP16 - Device: CPU
ms < Lower Is Better
a . 23.96 |====================================================================
b . 23.99 |====================================================================
c . 23.96 |====================================================================
OpenVINO 2024.0
Model: Face Detection FP16-INT8 - Device: CPU
FPS > Higher Is Better
a . 56.39 |====================================================================
b . 56.45 |====================================================================
c . 56.51 |====================================================================
OpenVINO 2024.0
Model: Face Detection FP16-INT8 - Device: CPU
ms < Lower Is Better
a . 564.47 |===================================================================
b . 564.47 |===================================================================
c . 564.32 |===================================================================
OpenVINO 2024.0
Model: Face Detection Retail FP16 - Device: CPU
FPS > Higher Is Better
a . 6930.15 |==================================================================
b . 6920.51 |==================================================================
c . 6927.90 |==================================================================
OpenVINO 2024.0
Model: Face Detection Retail FP16 - Device: CPU
ms < Lower Is Better
a . 4.60 |=====================================================================
b . 4.61 |=====================================================================
c . 4.60 |=====================================================================
OpenVINO 2024.0
Model: Road Segmentation ADAS FP16 - Device: CPU
FPS > Higher Is Better
a . 556.51 |===================================================================
b . 546.67 |==================================================================
c . 545.93 |==================================================================
OpenVINO 2024.0
Model: Road Segmentation ADAS FP16 - Device: CPU
ms < Lower Is Better
a . 57.43 |===================================================================
b . 58.46 |====================================================================
c . 58.54 |====================================================================
OpenVINO 2024.0
Model: Vehicle Detection FP16-INT8 - Device: CPU
FPS > Higher Is Better
a . 3015.55 |==================================================================
b . 2988.49 |=================================================================
c . 3012.81 |==================================================================
OpenVINO 2024.0
Model: Vehicle Detection FP16-INT8 - Device: CPU
ms < Lower Is Better
a . 10.59 |===================================================================
b . 10.69 |====================================================================
c . 10.60 |===================================================================
OpenVINO 2024.0
Model: Weld Porosity Detection FP16 - Device: CPU
FPS > Higher Is Better
a . 2966.79 |==================================================================
b . 2968.32 |==================================================================
c . 2969.13 |==================================================================
OpenVINO 2024.0
Model: Weld Porosity Detection FP16 - Device: CPU
ms < Lower Is Better
a . 21.55 |====================================================================
b . 21.54 |====================================================================
c . 21.53 |====================================================================
OpenVINO 2024.0
Model: Face Detection Retail FP16-INT8 - Device: CPU
FPS > Higher Is Better
a . 9773.24 |==================================================================
b . 9793.26 |==================================================================
c . 9779.93 |==================================================================
OpenVINO 2024.0
Model: Face Detection Retail FP16-INT8 - Device: CPU
ms < Lower Is Better
a . 6.53 |=====================================================================
b . 6.52 |=====================================================================
c . 6.53 |=====================================================================
OpenVINO 2024.0
Model: Road Segmentation ADAS FP16-INT8 - Device: CPU
FPS > Higher Is Better
a . 1051.90 |==================================================================
b . 1054.53 |==================================================================
c . 1049.11 |==================================================================
OpenVINO 2024.0
Model: Road Segmentation ADAS FP16-INT8 - Device: CPU
ms < Lower Is Better
a . 30.38 |====================================================================
b . 30.30 |====================================================================
c . 30.46 |====================================================================
OpenVINO 2024.0
Model: Machine Translation EN To DE FP16 - Device: CPU
FPS > Higher Is Better
a . 331.17 |===================================================================
b . 331.65 |===================================================================
c . 331.63 |===================================================================
OpenVINO 2024.0
Model: Machine Translation EN To DE FP16 - Device: CPU
ms < Lower Is Better
a . 96.50 |====================================================================
b . 96.35 |====================================================================
c . 96.38 |====================================================================
OpenVINO 2024.0
Model: Weld Porosity Detection FP16-INT8 - Device: CPU
FPS > Higher Is Better
a . 5678.12 |==================================================================
b . 5685.06 |==================================================================
c . 5681.48 |==================================================================
OpenVINO 2024.0
Model: Weld Porosity Detection FP16-INT8 - Device: CPU
ms < Lower Is Better
a . 11.26 |====================================================================
b . 11.24 |====================================================================
c . 11.25 |====================================================================
OpenVINO 2024.0
Model: Person Vehicle Bike Detection FP16 - Device: CPU
FPS > Higher Is Better
a . 2974.20 |==================================================================
b . 2945.11 |=================================================================
c . 2934.13 |=================================================================
OpenVINO 2024.0
Model: Person Vehicle Bike Detection FP16 - Device: CPU
ms < Lower Is Better
a . 10.73 |===================================================================
b . 10.84 |====================================================================
c . 10.88 |====================================================================
OpenVINO 2024.0
Model: Noise Suppression Poconet-Like FP16 - Device: CPU
FPS > Higher Is Better
a . 3817.87 |==================================================================
b . 3825.64 |==================================================================
c . 3828.30 |==================================================================
OpenVINO 2024.0
Model: Noise Suppression Poconet-Like FP16 - Device: CPU
ms < Lower Is Better
a . 16.53 |====================================================================
b . 16.51 |====================================================================
c . 16.49 |====================================================================
OpenVINO 2024.0
Model: Handwritten English Recognition FP16 - Device: CPU
FPS > Higher Is Better
a . 1541.43 |==================================================================
b . 1540.00 |==================================================================
c . 1525.91 |=================================================================
OpenVINO 2024.0
Model: Handwritten English Recognition FP16 - Device: CPU
ms < Lower Is Better
a . 41.49 |===================================================================
b . 41.53 |===================================================================
c . 41.91 |====================================================================
OpenVINO 2024.0
Model: Person Re-Identification Retail FP16 - Device: CPU
FPS > Higher Is Better
a . 3927.60 |==================================================================
b . 3916.92 |==================================================================
c . 3921.98 |==================================================================
OpenVINO 2024.0
Model: Person Re-Identification Retail FP16 - Device: CPU
ms < Lower Is Better
a . 8.13 |=====================================================================
b . 8.15 |=====================================================================
c . 8.14 |=====================================================================
OpenVINO 2024.0
Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU
FPS > Higher Is Better
a . 68063.14 |=================================================================
b . 68303.49 |=================================================================
c . 68152.88 |=================================================================
OpenVINO 2024.0
Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU
ms < Lower Is Better
a . 0.77 |=====================================================================
b . 0.77 |=====================================================================
c . 0.77 |=====================================================================
OpenVINO 2024.0
Model: Handwritten English Recognition FP16-INT8 - Device: CPU
FPS > Higher Is Better
a . 1616.79 |==================================================================
b . 1621.11 |==================================================================
c . 1621.25 |==================================================================
OpenVINO 2024.0
Model: Handwritten English Recognition FP16-INT8 - Device: CPU
ms < Lower Is Better
a . 39.55 |====================================================================
b . 39.45 |====================================================================
c . 39.45 |====================================================================
OpenVINO 2024.0
Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU
FPS > Higher Is Better
a . 86126.49 |=================================================================
b . 86415.41 |=================================================================
c . 85841.12 |=================================================================
OpenVINO 2024.0
Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU
ms < Lower Is Better
a . 0.58 |=====================================================================
b . 0.58 |=====================================================================
c . 0.58 |=====================================================================
Primesieve 12.1
Length: 1e12
Seconds < Lower Is Better
a . 3.556 |====================================================================
b . 3.554 |====================================================================
c . 3.531 |====================================================================
Primesieve 12.1
Length: 1e13
Seconds < Lower Is Better
a . 42.90 |====================================================================
b . 42.76 |====================================================================
c . 42.84 |====================================================================
Stockfish 16.1
Chess Benchmark
Nodes Per Second > Higher Is Better
a . 98973914 |=========================================================
b . 110763828 |================================================================
c . 97292518 |========================================================
Parallel BZIP2 Compression 1.1.13
FreeBSD-13.0-RELEASE-amd64-memstick.img Compression
Seconds < Lower Is Better
a . 2.016558 |============================================================
b . 2.170377 |=================================================================
c . 2.057670 |==============================================================
Timed Linux Kernel Compilation 6.8
Build: defconfig
Seconds < Lower Is Better
a . 44.30 |====================================================================
b . 44.41 |====================================================================
c . 44.39 |====================================================================
Timed Linux Kernel Compilation 6.8
Build: allmodconfig
Seconds < Lower Is Better
a . 391.24 |===================================================================
b . 391.93 |===================================================================
c . 391.03 |===================================================================
SVT-AV1 2.0
Encoder Mode: Preset 4 - Input: Bosphorus 4K
Frames Per Second > Higher Is Better
a . 7.000 |====================================================================
b . 7.005 |====================================================================
c . 6.925 |===================================================================
SVT-AV1 2.0
Encoder Mode: Preset 8 - Input: Bosphorus 4K
Frames Per Second > Higher Is Better
a . 71.24 |====================================================================
b . 68.58 |=================================================================
c . 69.50 |==================================================================
SVT-AV1 2.0
Encoder Mode: Preset 12 - Input: Bosphorus 4K
Frames Per Second > Higher Is Better
a . 165.28 |===================================================================
b . 165.01 |===================================================================
c . 165.22 |===================================================================
SVT-AV1 2.0
Encoder Mode: Preset 13 - Input: Bosphorus 4K
Frames Per Second > Higher Is Better
a . 167.56 |===================================================================
b . 166.21 |==================================================================
c . 165.24 |==================================================================
SVT-AV1 2.0
Encoder Mode: Preset 4 - Input: Bosphorus 1080p
Frames Per Second > Higher Is Better
a . 18.75 |===================================================================
b . 18.76 |===================================================================
c . 19.07 |====================================================================
SVT-AV1 2.0
Encoder Mode: Preset 8 - Input: Bosphorus 1080p
Frames Per Second > Higher Is Better
a . 142.85 |==================================================================
b . 142.25 |==================================================================
c . 145.06 |===================================================================
SVT-AV1 2.0
Encoder Mode: Preset 12 - Input: Bosphorus 1080p
Frames Per Second > Higher Is Better
a . 507.36 |===================================================================
b . 499.83 |==================================================================
c . 509.75 |===================================================================
SVT-AV1 2.0
Encoder Mode: Preset 13 - Input: Bosphorus 1080p
Frames Per Second > Higher Is Better
a . 577.70 |==================================================================
b . 582.51 |===================================================================
c . 565.04 |=================================================================
Chaos Group V-RAY 6.0
Mode: CPU
vsamples > Higher Is Better
a . 92008 |====================================================================
b . 92099 |====================================================================
c . 91007 |===================================================================
srsRAN Project 23.10.1-20240219
Test: PDSCH Processor Benchmark, Throughput Total
Mbps > Higher Is Better
a . 21012.2 |==================================================================
b . 21055.5 |==================================================================
c . 20479.7 |================================================================
srsRAN Project 23.10.1-20240219
Test: PDSCH Processor Benchmark, Throughput Thread
Mbps > Higher Is Better
a . 545.7 |===========================================================
b . 628.9 |====================================================================
c . 630.9 |====================================================================