Comments (4)
jeejeelee
commented on July 30, 2024
FYI:https://github.com/triton-lang/triton/blob/main/python/triton/ops/matmul.py. SPLIT-K should be able to solve such problems.
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leiwen83
commented on July 30, 2024
SPLIT-K
Great! It seems that the tutorail itself don's support splitk, so we need to make it change to have it tested with 03 tutorial?
And after applying with splitk, how much performance you saw comparing with torch?
Thx~
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jeejeelee
commented on July 30, 2024
IMHO, I don't think we should change 03tutorial.
You can do benchmarking on your own.
because your M=1， it also applies to the problem domain of GEMV.
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sleepwalker2017
commented on July 30, 2024
FYI:https://github.com/triton-lang/triton/blob/main/python/triton/ops/matmul.py.
SPLIT-Kshould be able to solve such problems.
Hi, this file is deleted, why ？
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Related Issues (20)
- Introduce `tl.assume` or use `assert` expression in non-debug builds to guide optimization?
- run into dead loop when tuning the tma persistent kernel HOT 6
- [BUG] error load fp32 value from 2D tensor HOT 2
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- Incompatible type error with "torch.onnx.export()"
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- Segfault when using `tl.range(...,num_stages)` HOT 4
- os.environ["TRITON_INTERPRET"] = "1" may makes tl.load error. HOT 2
- tl.interleave crashes Python HOT 4
- 保存中间IR文件 HOT 2
- How can I use high-order function in triton jit kernel？
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