How to use CUDA stream in Pytorch?

Question

I wanna use CUDA stream in Pytorch to parallel some computations, but I don’t know how to do it.
For instance, if there’s 2 tasks, A and B, need to be parallelized, I wanna do the following things:

stream0 = torch.get_stream()
stream1 = torch.get_stream()
with torch.now_stream(stream0):
    // task A
with torch.now_stream(stream1):
    // task B
torch.synchronize()
// get A and B's answer

How can I achieve the goal in real python code?

Asked By: gasoon

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Source

Answer 1

s1 = torch.cuda.Stream()
s2 = torch.cuda.Stream()
# Initialise cuda tensors here. E.g.:
A = torch.rand(1000, 1000, device = 'cuda')
B = torch.rand(1000, 1000, device = 'cuda')
# Wait for the above tensors to initialise.
torch.cuda.synchronize()
with torch.cuda.stream(s1):
    C = torch.mm(A, A)
with torch.cuda.stream(s2):
    D = torch.mm(B, B)
# Wait for C and D to be computed.
torch.cuda.synchronize()
# Do stuff with C and D.

Answered By: Tomas

How to use CUDA stream in Pytorch?

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