| Upload Date | September 03 2024 06:09 AM | 
| Views | 59 | 
| AI Information | |
|---|---|
| Framework | OpenVINO | 
| Backend | CPU | 
| Device | AMD Ryzen AI 9 365 w/ Radeon 880M | 
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) | 
| Model | AMD BirmanPlus-STX | 
| Motherboard | STX Beluga_SKF | 
| Power Plan | AVT powerscheme | 
| CPU Information | |
|---|---|
| Name | AMD Ryzen AI 9 365 w/ Radeon 880M | 
| Topology | 1 Processor, 10 Cores, 20 Threads | 
| Identifier | AuthenticAMD Family 26 Model 36 Stepping 0 | 
| Base Frequency | 2.00 GHz | 
| Cluster 1 | 4 Cores | 
| Cluster 2 | 6 Cores | 
| Memory Information | |
|---|---|
| Size | 32.00 GB | 
| Workload | Accuracy | Score | |
|---|---|---|---|
| Image Classification (SP) | 100% | 2651 492.9 IPS | |
| Image Classification (HP) | 100% | 2622 487.7 IPS | |
| Image Classification (Q) | 100% | 7199 1.34 KIPS | |
| Image Segmentation (SP) | 100% | 2377 38.5 IPS | |
| Image Segmentation (HP) | 100% | 2295 37.2 IPS | |
| Image Segmentation (Q) | 99% | 6722 109.0 IPS | |
| Pose Estimation (SP) | 100% | 7083 8.27 IPS | |
| Pose Estimation (HP) | 100% | 7063 8.24 IPS | |
| Pose Estimation (Q) | 98% | 27452 32.1 IPS | |
| Object Detection (SP) | 100% | 2684 212.9 IPS | |
| Object Detection (HP) | 100% | 2733 216.8 IPS | |
| Object Detection (Q) | 88% | 7642 612.6 IPS | |
| Face Detection (SP) | 100% | 8252 98.0 IPS | |
| Face Detection (HP) | 100% | 8361 99.3 IPS | |
| Face Detection (Q) | 100% | 20300 241.2 IPS | |
| Depth Estimation (SP) | 100% | 8038 61.9 IPS | |
| Depth Estimation (HP) | 100% | 7917 61.0 IPS | |
| Depth Estimation (Q) | 80% | 19510 154.6 IPS | |
| Style Transfer (SP) | 100% | 18170 23.4 IPS | |
| Style Transfer (HP) | 100% | 18261 23.5 IPS | |
| Style Transfer (Q) | 98% | 66795 86.1 IPS | |
| Image Super-Resolution (SP) | 100% | 3638 134.3 IPS | |
| Image Super-Resolution (HP) | 100% | 3667 135.4 IPS | |
| Image Super-Resolution (Q) | 99% | 12189 451.4 IPS | |
| Text Classification (SP) | 100% | 2376 3.17 KIPS | |
| Text Classification (HP) | 100% | 2464 3.29 KIPS | |
| Text Classification (Q) | 92% | 3207 4.31 KIPS | |
| Machine Translation (SP) | 100% | 3662 63.1 IPS | |
| Machine Translation (HP) | 100% | 3435 59.2 IPS | |
| Machine Translation (Q) | 85% | 4465 78.0 IPS |