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文件	最后提交记录	最后更新时间
no_blocks_no_threads.mlir	[mlir][gpu] Add Support for Cluster of Thread Blocks in gpu.launch (#76924)	2 年前
parallel_loop.mlir	[MLIR][SCFToGPU] Guard operands before AffineApplyOp::create to avoid crash (#167959) This fixes a crash in SCF→GPU when building the per‑dim index for mapped scf.parallel. **Change**: - Map step/lb through cloningMap, then run ensureLaunchIndependent. - If either is still unavailable at launch scope, emit a match‑failure; otherwise build the affine.apply. **Why this is correct:** - Matches how the pass already handles launch bounds; avoids creating an op with invalid operands and replaces a segfault with a clear diagnostic. **Tests**: - Added two small regressions that lower to gpu.launch and exercise the affine.apply path. Fixes : #167654 Signed-off-by: Shashi Shankar <shashishankar1687@gmail.com>	8 个月前
step_one.mlir	[mlir][Pass] Include anchor op in -pass-pipeline In D134622 the printed form of a pass manager is changed to include the name of the op that the pass manager is anchored on. This updates the -pass-pipeline argument format to include the anchor op as well, so that the printed form of a pipeline can be directly passed to -pass-pipeline. In most cases this requires updating -pass-pipeline='pipeline' to -pass-pipeline='builtin.module(pipeline)'. This also fixes an outdated assert that prevented running a PassManager anchored on 'any'. Reviewed By: rriddle Differential Revision: https://reviews.llvm.org/D134900	3 年前
step_positive.mlir	[mlir][affine][gpu] Replace DivSIOp to CeilDivSIOp when lowering to GPU launch (#73328) When converting affine.for to GPU launch operator, we have to calculate the block dimension and thread dimension for the launch operator. The formula of the dimension size is (upper_bound - lower_bound) / step_size When the difference is indivisible by step_size, we use rounding-to-zero as the division result. However, the block dimension and thread dimension is right-open range, i.e., [0, block_dim) and [0, thread_dim). So, we will get the wrong result if we use DivSIOp. In this patch, we replace it with CeilDivSIOp to get the correct block and thread dimension values.	2 年前