Supermicro Super Server
Geekbench ML Score
4435
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | July 15 2024 01:19 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
2579
482.7 IPS |
|
|
Image Classification (F16)
|
100% |
2574
481.7 IPS |
|
|
Image Classification (I8)
|
99% |
4352
814.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
1959
32.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
1959
32.7 IPS |
|
|
Image Segmentation (I8)
|
98% |
2808
46.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
7786
9.43 IPS |
|
|
Pose Estimation (F16)
|
100% |
7787
9.43 IPS |
|
|
Pose Estimation (I8)
|
100% |
25270
30.6 IPS |
|
|
Object Detection (F32)
|
100% |
2391
178.5 IPS |
|
|
Object Detection (F16)
|
100% |
2387
178.2 IPS |
|
|
Object Detection (I8)
|
62% |
1981
147.9 IPS |
|
|
Face Detection (F32)
|
100% |
4167
49.5 IPS |
|
|
Face Detection (F16)
|
100% |
4213
50.1 IPS |
|
|
Face Detection (I8)
|
89% |
4682
55.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
9016
69.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
9004
69.8 IPS |
|
|
Depth Estimation (I8)
|
96% |
16104
124.9 IPS |
|
|
Style Transfer (F32)
|
100% |
18136
23.9 IPS |
|
|
Style Transfer (F16)
|
100% |
18068
23.8 IPS |
|
|
Style Transfer (I8)
|
98% |
21614
28.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
4010
143.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4011
143.2 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
5736
204.9 IPS |
|
|
Text Classification (F32)
|
100% |
1920
2.76 KIPS |
|
|
Text Classification (F16)
|
100% |
1918
2.76 KIPS |
|
|
Text Classification (I8)
|
98% |
573
823.6 IPS |
|
|
Machine Translation (F32)
|
100% |
2908
53.5 IPS |
|
|
Machine Translation (F16)
|
100% |
2916
53.7 IPS |
|
|
Machine Translation (I8)
|
67% |
3785
69.6 IPS |
