| 文件 | 最后提交记录 | 最后更新时间 |
|---|---|---|
[MLIR][SparseTensor] Dense Outer Loop Ordering Strategy (#160168) This PR builds upon the infrastructure set up for Sparse Tensor Loop Ordering Heuristics (#154656) by adding a preference to have dense loops outer and sparse loops inner. As always I'd love to get feedback and know if there's any other direction to go with this work that might be better. | 8 个月前 | |
[mlir] Remove unused includes (NFC) (#148396) | 1 年前 | |
| 1 年前 | ||
[mlir][NFC] update mlir/Dialect create APIs (21/n) (#149928) See https://github.com/llvm/llvm-project/pull/147168 for more info. | 1 年前 | |
[MLIR] Apply clang-tidy fixes for bugprone-argument-comment in SparseBufferRewriting.cpp (NFC) | 8 个月前 | |
[mlir][NFC] update mlir/Dialect create APIs (33/n) (#150659) See https://github.com/llvm/llvm-project/pull/147168 for more info. | 1 年前 | |
[mlir][NFC] update mlir/Dialect create APIs (33/n) (#150659) See https://github.com/llvm/llvm-project/pull/147168 for more info. | 1 年前 | |
[MLIR][SparseTensor] Loop ordering strategy infrastructure (flag) (#154656) As discussed before, this PR adds the basic infrastructure/boiler plate for loop ordering strategies to be implemented. If this looks ok, I wanted to also mention some of the heuristics that I would implement next, if they sound reasonable to you guys: - Parallel first : prioritize parallel loops over reduction loops - Dense outer : prioritize the most dense loops first - Sparse outer : the opposite, potentially useful in some cases? There is another that I am considering, stride/memory aware, which would prioritize loops with better stride patterns (like sequential or linear). Not sure how well this carries over to Sparse Tensor though. Are there any ideas/heuristics that I should definitely try to implement? As we discussed, I will try to incrementally add heuristics. Sorry for the delay on my end, and thank you so much for the feedback! --------- Co-authored-by: Aart Bik <ajcbik@google.com> | 9 个月前 | |
[mlir][NFC] update mlir/Dialect create APIs (21/n) (#149928) See https://github.com/llvm/llvm-project/pull/147168 for more info. | 1 年前 | |
[mlir][NFC] update mlir/Dialect create APIs (21/n) (#149928) See https://github.com/llvm/llvm-project/pull/147168 for more info. | 1 年前 | |
[mlir] Remove redundant typename (NFC) (#166108) Identified with readability-redundant-typename. | 8 个月前 | |
[mlir][Transforms] Dialect Conversion Driver without Rollback (#151865) This commit improves the allowPatternRollback flag handling in the dialect conversion driver. Previously, this flag was used to merely detect cases that are incompatible with the new One-Shot Dialect Conversion driver. This commit implements the driver itself: when the flag is set to "false", all IR changes are materialized immediately, bypassing the IRRewrite and ConversionValueMapping infrastructure. A few selected test cases now run with both the old and the new driver. RFC: https://discourse.llvm.org/t/rfc-a-new-one-shot-dialect-conversion-driver/79083 | 11 个月前 | |
[MLIR][SparseTensor] Loop ordering strategy infrastructure (flag) (#154656) As discussed before, this PR adds the basic infrastructure/boiler plate for loop ordering strategies to be implemented. If this looks ok, I wanted to also mention some of the heuristics that I would implement next, if they sound reasonable to you guys: - Parallel first : prioritize parallel loops over reduction loops - Dense outer : prioritize the most dense loops first - Sparse outer : the opposite, potentially useful in some cases? There is another that I am considering, stride/memory aware, which would prioritize loops with better stride patterns (like sequential or linear). Not sure how well this carries over to Sparse Tensor though. Are there any ideas/heuristics that I should definitely try to implement? As we discussed, I will try to incrementally add heuristics. Sorry for the delay on my end, and thank you so much for the feedback! --------- Co-authored-by: Aart Bik <ajcbik@google.com> | 9 个月前 | |
[mlir][NFC] update mlir/Dialect create APIs (33/n) (#150659) See https://github.com/llvm/llvm-project/pull/147168 for more info. | 1 年前 | |
[MLIR] Extend vector.scatter to accept tensor as base (#165548) This PR makes the following improvements to vector.scatter and its lowering pipeline: - In addition to memref, accept a ranked tensor as the base operand of vector.scatter, similar to vector.transfer_write. - Implement bufferization support for vector.scatter, so that tensor-based scatter ops can be fully lowered to memref-based forms. It's worth to complete the functionality of map_scatter decomposition. Full discussion can be found here: https://github.com/iree-org/iree/issues/21135 --------- Signed-off-by: Ryutaro Okada <1015ryu88@gmail.com> | 8 个月前 | |
[mlir][NFC] update mlir/Dialect create APIs (21/n) (#149928) See https://github.com/llvm/llvm-project/pull/147168 for more info. | 1 年前 | |
[mlir] Remove duplicate includes (NFC) (#167187) Identified with readability-duplicate-include. | 8 个月前 | |
[mlir][NFC] update mlir/Dialect create APIs (21/n) (#149928) See https://github.com/llvm/llvm-project/pull/147168 for more info. | 1 年前 |
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