Upload Date | September 20 2024 07:25 AM |
Views | 1 |
System Information | |
---|---|
Operating System | Microsoft Windows 11 Pro (64-bit) |
Model | Micro-Star International Co., Ltd. MS-7D69 |
Motherboard | Micro-Star International Co., Ltd. MEG X670E ACE (MS-7D69) |
Power Plan | High performance |
CPU Information | |
---|---|
Name | AMD Ryzen 9 7950X |
Topology | 1 Processor, 16 Cores, 32 Threads |
Identifier | AuthenticAMD Family 25 Model 97 Stepping 2 |
Base Frequency | 4.50 GHz |
Cluster 1 | 16 Cores |
L1 Instruction Cache | 32.0 KB x 16 |
L1 Data Cache | 32.0 KB x 16 |
L2 Cache | 1.00 MB x 16 |
L3 Cache | 32.0 MB x 2 |
Memory Information | |
---|---|
Size | 64.00 GB |
Inference Information | |
---|---|
Framework | ONNX |
Backend | CPU |
Device | Default |
Workload | Accuracy | Score | |
---|---|---|---|
Image Classification (F32)
|
100% |
1887
353.1 IPS |
|
Image Classification (F16)
|
100% |
1924
360.0 IPS |
|
Image Classification (I8)
|
99% |
4726
884.4 IPS |
|
Image Segmentation (F32)
|
100% |
2418
40.4 IPS |
|
Image Segmentation (F16)
|
100% |
2514
42.0 IPS |
|
Image Segmentation (I8)
|
98% |
3381
56.5 IPS |
|
Pose Estimation (F32)
|
100% |
15880
19.2 IPS |
|
Pose Estimation (F16)
|
100% |
15916
19.3 IPS |
|
Pose Estimation (I8)
|
100% |
45060
54.6 IPS |
|
Object Detection (F32)
|
100% |
2187
163.3 IPS |
|
Object Detection (F16)
|
100% |
2168
161.9 IPS |
|
Object Detection (I8)
|
62% |
2180
162.7 IPS |
|
Face Detection (F32)
|
100% |
4140
49.2 IPS |
|
Face Detection (F16)
|
100% |
3753
44.6 IPS |
|
Face Detection (I8)
|
89% |
5763
68.5 IPS |
|
Depth Estimation (F32)
|
100% |
10446
81.0 IPS |
|
Depth Estimation (F16)
|
100% |
10231
79.3 IPS |
|
Depth Estimation (I8)
|
96% |
22008
170.7 IPS |
|
Style Transfer (F32)
|
100% |
30629
40.3 IPS |
|
Style Transfer (F16)
|
100% |
30521
40.1 IPS |
|
Style Transfer (I8)
|
98% |
40971
53.9 IPS |
|
Image Super-Resolution (F32)
|
100% |
4203
150.1 IPS |
|
Image Super-Resolution (F16)
|
100% |
3979
142.1 IPS |
|
Image Super-Resolution (I8)
|
99% |
5045
180.2 IPS |
|
Text Classification (F32)
|
100% |
1654
2.38 KIPS |
|
Text Classification (F16)
|
100% |
1667
2.40 KIPS |
|
Text Classification (I8)
|
98% |
395
567.5 IPS |
|
Machine Translation (F32)
|
100% |
3168
58.3 IPS |
|
Machine Translation (F16)
|
100% |
3331
61.3 IPS |
|
Machine Translation (I8)
|
67% |
4031
74.2 IPS |