RuggON SOL7
Geekbench ML Score
1281
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | August 27 2024 06:59 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 IoT Enterprise (64-bit) |
| Model | RuggON SOL7 |
| Motherboard | RuggON SOL7 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 5 125U |
| Topology | 1 Processor, 10 Cores, 12 Threads |
| Identifier | GenuineIntel Family 6 Model 170 Stepping 4 |
| Base Frequency | 3.60 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 8 Cores |
| L1 Instruction Cache | 64.0 KB x 6 |
| L1 Data Cache | 48.0 KB x 6 |
| L2 Cache | 2.00 MB x 1 |
| L3 Cache | 12.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | Intel(R) Graphics |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
531
99.3 IPS |
|
|
Image Classification (F16)
|
100% |
525
98.2 IPS |
|
|
Image Classification (I8)
|
100% |
485
90.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
588
9.83 IPS |
|
|
Image Segmentation (F16)
|
100% |
594
9.92 IPS |
|
|
Image Segmentation (I8)
|
98% |
517
8.64 IPS |
|
|
Pose Estimation (F32)
|
100% |
5463
6.62 IPS |
|
|
Pose Estimation (F16)
|
100% |
5453
6.60 IPS |
|
|
Pose Estimation (I8)
|
100% |
4695
5.69 IPS |
|
|
Object Detection (F32)
|
100% |
498
37.2 IPS |
|
|
Object Detection (F16)
|
100% |
505
37.7 IPS |
|
|
Object Detection (I8)
|
54% |
464
34.6 IPS |
|
|
Face Detection (F32)
|
100% |
523
6.21 IPS |
|
|
Face Detection (F16)
|
100% |
522
6.21 IPS |
|
|
Face Detection (I8)
|
89% |
466
5.54 IPS |
|
|
Depth Estimation (F32)
|
100% |
3045
23.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
3096
24.0 IPS |
|
|
Depth Estimation (I8)
|
95% |
2590
20.1 IPS |
|
|
Style Transfer (F32)
|
100% |
16596
21.8 IPS |
|
|
Style Transfer (F16)
|
100% |
16031
21.1 IPS |
|
|
Style Transfer (I8)
|
98% |
12350
16.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2933
104.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2950
105.4 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
2000
71.4 IPS |
|
|
Text Classification (F32)
|
90% |
509
731.5 IPS |
|
|
Text Classification (F16)
|
90% |
518
744.4 IPS |
|
|
Text Classification (I8)
|
90% |
355
510.4 IPS |
|
|
Machine Translation (F32)
|
100% |
760
14.0 IPS |
|
|
Machine Translation (F16)
|
100% |
762
14.0 IPS |
|
|
Machine Translation (I8)
|
70% |
443
8.15 IPS |
