| User | grinceur |
| Upload Date | August 18 2024 04:34 PM |
| Views | 18 |
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Microsoft SQ1 @ 3.0 GHz |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Professionnel (64-bit) |
| Model | Microsoft Corporation Surface Pro X |
| Motherboard | Microsoft Corporation Surface Pro X |
| Power Plan | Utilisation normale |
| CPU Information | |
|---|---|
| Name | Microsoft SQ1 @ 3.0 GHz |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARMv8 (64-bit) Family 8 Model 805 Revision D0E |
| Base Frequency | 3.00 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 8.00 GB |
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
212
39.4 IPS |
|
|
Image Classification (HP)
|
100% |
219
40.8 IPS |
|
|
Image Classification (Q)
|
99% |
800
149.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
256
4.16 IPS |
|
|
Image Segmentation (HP)
|
100% |
789
12.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
774
12.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
834
0.97 IPS |
|
|
Pose Estimation (HP)
|
100% |
808
0.94 IPS |
|
|
Pose Estimation (Q)
|
95% |
3788
4.44 IPS |
|
|
Object Detection (SP)
|
100% |
225
17.9 IPS |
|
|
Object Detection (HP)
|
99% |
224
17.8 IPS |
|
|
Object Detection (Q)
|
88% |
876
70.2 IPS |
|
|
Face Detection (SP)
|
100% |
612
7.27 IPS |
|
|
Face Detection (HP)
|
100% |
519
6.17 IPS |
|
|
Face Detection (Q)
|
97% |
1846
22.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
636
4.90 IPS |
|
|
Depth Estimation (HP)
|
98% |
756
5.84 IPS |
|
|
Depth Estimation (Q)
|
76% |
2476
19.9 IPS |
|
|
Style Transfer (SP)
|
100% |
2162
2.78 IPS |
|
|
Style Transfer (HP)
|
100% |
3375
4.34 IPS |
|
|
Style Transfer (Q)
|
98% |
7854
10.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
406
15.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
231
8.54 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
1013
37.5 IPS |
|
|
Text Classification (SP)
|
100% |
389
519.5 IPS |
|
|
Text Classification (HP)
|
100% |
136
180.9 IPS |
|
|
Text Classification (Q)
|
97% |
198
264.8 IPS |
|
|
Machine Translation (SP)
|
100% |
480
8.27 IPS |
|
|
Machine Translation (HP)
|
99% |
456
7.87 IPS |
|
|
Machine Translation (Q)
|
60% |
491
11.0 IPS |