Supermicro Super Server
Geekbench ML Score
1254
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | July 15 2024 01:23 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 Enterprise LTSC (64-bit) |
| Model | Supermicro Super Server |
| Motherboard | Supermicro X13SAV-LVDS |
| Power Plan | Ultimate Performance |
| CPU Information | |
|---|---|
| Name | Intel Core i7-13700E |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | GenuineIntel Family 6 Model 183 Stepping 1 |
| Base Frequency | 1.88 GHz |
| Cluster 1 | 8 Cores |
| L1 Instruction Cache | 32.0 KB x 8 |
| L1 Data Cache | 48.0 KB x 8 |
| L2 Cache | 2.00 MB x 2 |
| L3 Cache | 30.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | Intel(R) UHD Graphics 770 |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
535
100.1 IPS |
|
|
Image Classification (F16)
|
100% |
535
100.1 IPS |
|
|
Image Classification (I8)
|
100% |
459
85.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
1052
17.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
1050
17.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
797
13.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
3179
3.85 IPS |
|
|
Pose Estimation (F16)
|
100% |
3216
3.89 IPS |
|
|
Pose Estimation (I8)
|
100% |
2990
3.62 IPS |
|
|
Object Detection (F32)
|
100% |
537
40.1 IPS |
|
|
Object Detection (F16)
|
100% |
572
42.7 IPS |
|
|
Object Detection (I8)
|
54% |
497
37.1 IPS |
|
|
Face Detection (F32)
|
100% |
1466
17.4 IPS |
|
|
Face Detection (F16)
|
100% |
1468
17.5 IPS |
|
|
Face Detection (I8)
|
89% |
1084
12.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
2186
17.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
2189
17.0 IPS |
|
|
Depth Estimation (I8)
|
94% |
1903
14.8 IPS |
|
|
Style Transfer (F32)
|
100% |
9191
12.1 IPS |
|
|
Style Transfer (F16)
|
100% |
9188
12.1 IPS |
|
|
Style Transfer (I8)
|
98% |
7958
10.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1650
58.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1655
59.1 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
1300
46.4 IPS |
|
|
Text Classification (F32)
|
100% |
856
1.23 KIPS |
|
|
Text Classification (F16)
|
100% |
857
1.23 KIPS |
|
|
Text Classification (I8)
|
98% |
408
586.4 IPS |
|
|
Machine Translation (F32)
|
100% |
555
10.2 IPS |
|
|
Machine Translation (F16)
|
100% |
554
10.2 IPS |
|
|
Machine Translation (I8)
|
70% |
358
6.58 IPS |
