[TOPI][OP] cuda for argwhere #6868
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@zhiics I have a branch with the changes you'd need, but I haven't opened a PR because I've been fighting that memory corruption issue with topk. Would you like me to submit a PR to enable the other dynamic tests and include my refactors to strided slice? |
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@mbrookhart Thanks. That would be cool. |
| max_threads = int(tvm.target.Target.current(allow_none=False).max_num_threads) | ||
| nthread_tx = max_threads | ||
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| # Limit threads to a single block to make sure atomic_add works normally. |
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Cuda does have a kernel level atomic add (https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#atomic-functions). It is just slower or do we not have access to it from TIR?
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We use atomicAdd. However, if number of blocks is larger than a threshold(like 18), it will return incorrect result.
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I'm surprised. I'd expect atomicAdd to work with any number of blocks. Could you maybe expand this comment with why and when atomicAdd fails?
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The observation is that if input data size is large( > 300 * 300 for example), previous we don't limit the number of blocks and the output of IR routine would be incorrect. I didn't dig deeper into it at this time.
In addition we need to use thrust otherwise tvm implemetation of topk can also generate incorrect result.
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Thanks @zhiics @mbrookhart @tkonolige |
* argwhere * cuda schedule * sort argwhere result * Use single block and thrust to fix flaky behavior * format * used dynamic strided_slice * Fix dynamic strided_slice * try new strided_slice * Improve dynamic strided slice to bind data depedent shape var. * all tests pass * remove print * use new strided_slice * clean Co-authored-by: Yao Wang <[email protected]>
* argwhere * cuda schedule * sort argwhere result * Use single block and thrust to fix flaky behavior * format * used dynamic strided_slice * Fix dynamic strided_slice * try new strided_slice * Improve dynamic strided slice to bind data depedent shape var. * all tests pass * remove print * use new strided_slice * clean Co-authored-by: Yao Wang <[email protected]>
* argwhere * cuda schedule * sort argwhere result * Use single block and thrust to fix flaky behavior * format * used dynamic strided_slice * Fix dynamic strided_slice * try new strided_slice * Improve dynamic strided slice to bind data depedent shape var. * all tests pass * remove print * use new strided_slice * clean Co-authored-by: Yao Wang <[email protected]>
This PR adds cuda schedule for argwhere.
Will ping reviews when we can run argwhere relay tests.