Supermicro Super Server
Geekbench ML Score
1416
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | July 15 2024 01:04 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Supermicro Super Server |
| Motherboard | Supermicro X13SAV-LVDS |
| Power Plan | High 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 | 1.90 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 | 32.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | Intel(R) UHD Graphics 770 |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
675
126.3 IPS |
|
|
Image Classification (F16)
|
100% |
678
126.9 IPS |
|
|
Image Classification (I8)
|
100% |
552
103.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
970
16.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
972
16.2 IPS |
|
|
Image Segmentation (I8)
|
98% |
741
12.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
5063
6.13 IPS |
|
|
Pose Estimation (F16)
|
100% |
5099
6.17 IPS |
|
|
Pose Estimation (I8)
|
100% |
3450
4.18 IPS |
|
|
Object Detection (F32)
|
100% |
779
58.2 IPS |
|
|
Object Detection (F16)
|
100% |
778
58.1 IPS |
|
|
Object Detection (I8)
|
54% |
646
48.3 IPS |
|
|
Face Detection (F32)
|
100% |
1371
16.3 IPS |
|
|
Face Detection (F16)
|
100% |
1364
16.2 IPS |
|
|
Face Detection (I8)
|
89% |
945
11.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
2962
23.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
2977
23.1 IPS |
|
|
Depth Estimation (I8)
|
95% |
2280
17.7 IPS |
|
|
Style Transfer (F32)
|
100% |
10644
14.0 IPS |
|
|
Style Transfer (F16)
|
100% |
10646
14.0 IPS |
|
|
Style Transfer (I8)
|
98% |
7948
10.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1744
62.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1767
63.1 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
960
34.3 IPS |
|
|
Text Classification (F32)
|
100% |
845
1.21 KIPS |
|
|
Text Classification (F16)
|
100% |
841
1.21 KIPS |
|
|
Text Classification (I8)
|
98% |
411
590.5 IPS |
|
|
Machine Translation (F32)
|
100% |
704
12.9 IPS |
|
|
Machine Translation (F16)
|
100% |
707
13.0 IPS |
|
|
Machine Translation (I8)
|
70% |
409
7.53 IPS |
