Supermicro Super Server
Geekbench ML Score
1232
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | July 15 2024 03:54 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 i9-13900E |
| Topology | 1 Processor, 24 Cores, 32 Threads |
| Identifier | GenuineIntel Family 6 Model 183 Stepping 1 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 16 Cores |
| L1 Instruction Cache | 64.0 KB x 16 |
| L1 Data Cache | 32.0 KB x 16 |
| L2 Cache | 4.00 MB x 4 |
| L3 Cache | 36.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | Intel(R) UHD Graphics 770 |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
541
101.2 IPS |
|
|
Image Classification (F16)
|
100% |
543
101.6 IPS |
|
|
Image Classification (I8)
|
100% |
459
85.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
1010
16.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
1008
16.8 IPS |
|
|
Image Segmentation (I8)
|
98% |
777
13.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
3265
3.95 IPS |
|
|
Pose Estimation (F16)
|
100% |
3264
3.95 IPS |
|
|
Pose Estimation (I8)
|
100% |
2991
3.62 IPS |
|
|
Object Detection (F32)
|
100% |
547
40.8 IPS |
|
|
Object Detection (F16)
|
100% |
543
40.5 IPS |
|
|
Object Detection (I8)
|
54% |
478
35.7 IPS |
|
|
Face Detection (F32)
|
100% |
1402
16.7 IPS |
|
|
Face Detection (F16)
|
100% |
1405
16.7 IPS |
|
|
Face Detection (I8)
|
89% |
1029
12.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
2132
16.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
2129
16.5 IPS |
|
|
Depth Estimation (I8)
|
94% |
1848
14.3 IPS |
|
|
Style Transfer (F32)
|
100% |
9204
12.1 IPS |
|
|
Style Transfer (F16)
|
100% |
9257
12.2 IPS |
|
|
Style Transfer (I8)
|
98% |
8123
10.7 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1675
59.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1662
59.4 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
1308
46.7 IPS |
|
|
Text Classification (F32)
|
100% |
840
1.21 KIPS |
|
|
Text Classification (F16)
|
100% |
846
1.22 KIPS |
|
|
Text Classification (I8)
|
98% |
410
589.7 IPS |
|
|
Machine Translation (F32)
|
100% |
500
9.21 IPS |
|
|
Machine Translation (F16)
|
100% |
519
9.55 IPS |
|
|
Machine Translation (I8)
|
70% |
336
6.18 IPS |
