Upload Date | August 15 2024 02:54 PM |
Views | 2 |
System Information | |
---|---|
Operating System | Microsoft Windows 11 Pro (64-bit) |
Model | HP HP EliteBook 645 14 inch G11 Notebook PC |
Motherboard | HP 8C7A |
Power Plan | HP Optimized (Modern Standby) |
CPU Information | |
---|---|
Name | AMD Ryzen 7 Pro 7735U with Radeon Graphics |
Topology | 1 Processor, 8 Cores, 16 Threads |
Identifier | AuthenticAMD Family 25 Model 68 Stepping 1 |
Base Frequency | 2.70 GHz |
Cluster 1 | 8 Cores |
L1 Instruction Cache | 32.0 KB x 8 |
L1 Data Cache | 32.0 KB x 8 |
L2 Cache | 512 KB x 8 |
L3 Cache | 16.0 MB x 1 |
Memory Information | |
---|---|
Size | 16.00 GB |
Inference Information | |
---|---|
Framework | ONNX |
Backend | DirectML |
Device | AMD Radeon(TM) Graphics |
Workload | Accuracy | Score | |
---|---|---|---|
Image Classification (F32)
|
100% |
1675
313.5 IPS |
|
Image Classification (F16)
|
100% |
1716
321.1 IPS |
|
Image Classification (I8)
|
100% |
1485
277.9 IPS |
|
Image Segmentation (F32)
|
100% |
2756
46.0 IPS |
|
Image Segmentation (F16)
|
100% |
2749
45.9 IPS |
|
Image Segmentation (I8)
|
98% |
2217
37.0 IPS |
|
Pose Estimation (F32)
|
100% |
23556
28.5 IPS |
|
Pose Estimation (F16)
|
100% |
24304
29.4 IPS |
|
Pose Estimation (I8)
|
100% |
19056
23.1 IPS |
|
Object Detection (F32)
|
100% |
1400
104.5 IPS |
|
Object Detection (F16)
|
100% |
1430
106.7 IPS |
|
Object Detection (I8)
|
62% |
1289
96.3 IPS |
|
Face Detection (F32)
|
100% |
4053
48.2 IPS |
|
Face Detection (F16)
|
100% |
4001
47.6 IPS |
|
Face Detection (I8)
|
89% |
3129
37.2 IPS |
|
Depth Estimation (F32)
|
100% |
11253
87.3 IPS |
|
Depth Estimation (F16)
|
100% |
11181
86.7 IPS |
|
Depth Estimation (I8)
|
94% |
9111
70.7 IPS |
|
Style Transfer (F32)
|
100% |
34606
45.5 IPS |
|
Style Transfer (F16)
|
100% |
34860
45.9 IPS |
|
Style Transfer (I8)
|
98% |
32790
43.1 IPS |
|
Image Super-Resolution (F32)
|
100% |
6228
222.4 IPS |
|
Image Super-Resolution (F16)
|
100% |
8466
302.3 IPS |
|
Image Super-Resolution (I8)
|
99% |
5398
192.8 IPS |
|
Text Classification (F32)
|
100% |
1334
1.92 KIPS |
|
Text Classification (F16)
|
100% |
1341
1.93 KIPS |
|
Text Classification (I8)
|
98% |
1009
1.45 KIPS |
|
Machine Translation (F32)
|
100% |
2078
38.2 IPS |
|
Machine Translation (F16)
|
100% |
2134
39.3 IPS |
|
Machine Translation (I8)
|
70% |
1202
22.1 IPS |