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I have a question regarding the prefetch implementation in your framework.
As I understand it, prefetching and inference should ideally run concurrently in separate CUDA streams. I noticed that there are some codes about Cuda Stream in your framework.
I use pytorch profiler to profile the readme_example.py, and I found that there is just one stream (stream7), and cudaMemcpy operations are blocking.
Could you please clarify how prefetching is implemented in your framework? (Apologies if I haven't fully grasped the code yet.) Additionally, could it be that I'm misunderstanding some basic concepts?
Thanks a lot!
The text was updated successfully, but these errors were encountered:
Thanks for pointing this out, there's some miss-alignment in using torch stream API and cuda stream API. By the end of the day, everything should be using stream pool. Will update shortly.
Hi.
I have a question regarding the prefetch implementation in your framework.
As I understand it, prefetching and inference should ideally run concurrently in separate CUDA streams. I noticed that there are some codes about Cuda Stream in your framework.
I use pytorch profiler to profile the readme_example.py, and I found that there is just one stream (stream7), and cudaMemcpy operations are blocking.
Could you please clarify how prefetching is implemented in your framework? (Apologies if I haven't fully grasped the code yet.) Additionally, could it be that I'm misunderstanding some basic concepts?
Thanks a lot!
The text was updated successfully, but these errors were encountered: