ROMED8-2T
Geekbench AI Score
2640
Single Precision Score
946
Half Precision Score
2625
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| User | xilvar |
| Upload Date | December 21 2024 08:53 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | AMD EPYC 7F52 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 Pro (64-bit) |
| Model | ROMED8-2T |
| Motherboard | ASRockRack ROMED8-2T |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | AMD EPYC 7F52 |
| Topology | 1 Processor, 16 Cores, 32 Threads |
| Identifier | AuthenticAMD Family 23 Model 49 Stepping 0 |
| Base Frequency | 3.50 GHz |
| Cluster 1 | 16 Cores |
| Memory Information | |
|---|---|
| Size | 256.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1942
361.1 IPS |
|
|
Image Classification (HP)
|
100% |
309
57.5 IPS |
|
|
Image Classification (Q)
|
96% |
2621
489.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
755
12.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
383
6.21 IPS |
|
|
Image Segmentation (Q)
|
97% |
1394
22.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
11000
12.8 IPS |
|
|
Pose Estimation (HP)
|
100% |
6760
7.89 IPS |
|
|
Pose Estimation (Q)
|
86% |
9449
11.2 IPS |
|
|
Object Detection (SP)
|
100% |
2186
173.4 IPS |
|
|
Object Detection (HP)
|
100% |
389
30.8 IPS |
|
|
Object Detection (Q)
|
58% |
1923
210.1 IPS |
|
|
Face Detection (SP)
|
100% |
4988
59.3 IPS |
|
|
Face Detection (HP)
|
100% |
899
10.7 IPS |
|
|
Face Detection (Q)
|
96% |
5193
61.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
8266
63.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
1611
12.4 IPS |
|
|
Depth Estimation (Q)
|
78% |
6737
53.8 IPS |
|
|
Style Transfer (SP)
|
100% |
16203
20.8 IPS |
|
|
Style Transfer (HP)
|
100% |
13951
17.9 IPS |
|
|
Style Transfer (Q)
|
87% |
15064
19.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1325
48.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1033
38.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1201
44.5 IPS |
|
|
Text Classification (SP)
|
100% |
565
754.6 IPS |
|
|
Text Classification (HP)
|
100% |
275
366.4 IPS |
|
|
Text Classification (Q)
|
97% |
269
360.8 IPS |
|
|
Machine Translation (SP)
|
100% |
933
16.1 IPS |
|
|
Machine Translation (HP)
|
100% |
324
5.57 IPS |
|
|
Machine Translation (Q)
|
68% |
1378
26.6 IPS |
