Open k-okada opened 3 years ago
@k-okada Yes, but your P51s's NVIDIA Quadro M520 is maxwell architecture, which does not support unified memory. we need Pascal architecture Nvidia GPU at least. https://developer.nvidia.com/blog/beyond-gpu-memory-limits-unified-memory-pascal/#:~:text=New%20Pascal%20Unified%20Memory%20Features&text=Unified%20Memory%20was%20introduced%20in,6%20and%20the%20Kepler%20architecture.&text=The%20Page%20Migration%20engine%20allows,on%2Ddemand%20for%20efficient%20processing.
@k-okada It was my misunderstandings, but unified memory is introduced in Keplar architecture. However, cupy's unified memory is enabled from Pascal architecture. https://developer.nvidia.com/blog/unified-memory-cuda-beginners/ https://github.com/cupy/cupy/pull/447#issue-137859218
if we add
pool = cp.cuda.MemoryPool(cp.cuda.malloc_managed) cp.cuda.set_allocator(pool.malloc)
then, it works on my p51s, so question is; Should we put this code on fcn_object_segmentation.py ?
-- ◉ Kei Okada
2021年7月12日(月) 0:01 Shingo Kitagawa @.***>:
@k-okada https://github.com/k-okada It was my misunderstandings, but unified memory is introduced in Keplar architecture. However, cupy's unified memory is enabled from Pascal architecture. https://developer.nvidia.com/blog/unified-memory-cuda-beginners/
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in my P50, the code does not work, so it doesnot change my situation. but yes. it does not have bad effect.
I tried to run FCN example on my P51s
and have following error. This error can be avoid by adding following code and I'd like to add this code on source tree instead of adding the code every time.
Is there any why to know if the model fits in current memory before we send to hardware? Or
is enough?