Profile Job Results
Jobs
j5qe6w275
Results Ready
Name
unet_segmentation
Target Device
- SA7255P ADP
- Android 14
- Qualcomm® SA7255P
Creator
ai-hub-support@qti.qualcomm.com
Target Model
Input Specs
image: float32[1, 640, 1280, 3]Completion Time
4/8/2025, 1:16:06 PM
Versions
- TensorFlow Lite: 2.17.0
- QAIRT: v2.32.0.250228225014_116386-auto
- QNN TfLite Delegate: v2.32.0.250228225014_116386-auto
- Android: 14 (UQ1A.240205.002)
- Build ID: Snapdragon_Auto.HQX.4.5.6.0.r2-00012-STD.PROD-5
- AI Hub: aihub-2025.03.24.0
Estimated Inference Time
122 min
Estimated Peak Memory Usage
468 ‑ 86,683 GB
Compute Units
NPU
32
| Stage | Time | Memory |
|---|---|---|
First App Load | 502 min | 546,032‑555,776 GB |
Subsequent App Load | 512 min | 534,616‑633,800 GB |
Inference | 122 min | 468‑86,683 GB |
| TensorFlow Lite | Value |
|---|---|
| number_of_threads | 4 |
| QNN Delegate | Value |
|---|---|
| backend_type | kHtpBackend |
| log_level | kLogLevelWarn |
| htp_options.precision | kHtpFp16 |
| htp_options.useConvHmx | true |
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