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Hi,
Deep learning algorithms run very slowly on DSP(TDA2xx)
image size is 512x256.
### CPU [ DSP1], LinkID [ 49],
[IPU1-0] 831.681815 s:
[IPU1-0] 831.681845 s: [ ALG_TIDL ] Link Statistics,
[IPU1-0] 831.681937 s: ******************************
[IPU1-0] 831.681998 s:
[IPU1-0] 831.682028 s: Elapsed time = 633812 msec
[IPU1-0] 831.682120 s:
[IPU1-0] 831.682272 s: New data Recv = 0.2 fps
[IPU1-0] 831.682364 s:
[IPU1-0] 831.682394 s: Input Statistics,
[IPU1-0] 831.682455 s:
[IPU1-0] 831.682516 s: CH | In Recv | In Drop | In User Drop | In Process
[IPU1-0] 831.682577 s: | FPS | FPS | FPS | FPS
[IPU1-0] 831.682669 s: --------------------------------------------------
[IPU1-0] 831.682760 s: 0 | 0. 1 0. 0 0. 0 0. 1
Computational complexity:
thanks!
Hi,
deploy_512x256.rarAbout
eep_top_k: 20
confidence_threshold: 0.15
1. I don't have these two variables in my file (deploy.prototxt) .
2. I want to run four networks on tda2x at the same time.
1camera (video input)---------->first network on DSP_1
2camera(video input)---------->the second network on DSP_2
3camera(video input)----------->the third network on EVE_1
4camera(video input)---------->the fourth network on EVE_2 EVE_3 EVE_4
The network is running slowly on the DSP.
Is there any way to improve it?
Thanks!