I think we can use here same logic as for nonnull.
strlen(X) - X must be noundef => valid pointer.
for libcalls with size arg, we add noundef only if size is known and greater than 0 - so pointers must be noundef (valid ones)
Reviewed By: jdoerfert, aqjune
Differential Revision: https://reviews.llvm.org/D95122
This patch updates IRBuilder to create insertelement/shufflevector using poison as a placeholder.
Reviewed By: nikic
Differential Revision: https://reviews.llvm.org/D93793
PreservedCFGCheckerInstrumentation was saying that LowerMatrixIntrinsics
didn't properly preserve CFG even though it claimed to. The legacy pass
says it doesn't. Match the legacy pass's preserved analyses.
Reviewed By: thakis
Differential Revision: https://reviews.llvm.org/D89175
This patch uses the TileInfo introduced in D77550 to generate a loop
nest for tiled matrix multiplication, instead of generating the
unrolled code for the whole multiplication. This makes code-generation
more scalable for larger matrixes.
Initially loops are only used if both the number of rows and columns are
divisible by the tile size. Other cases will be added as follow-up.
Reviewers: anemet, Gerolf, hfinkel, andrew.w.kaylor, LuoYuanke, nicolasvasilache
Reviewed By: anemet
Differential Revision: https://reviews.llvm.org/D81308
Some tests were missing alignment info. Subsequent changes properly
preserve the set alignment. Set it properly beforehand, to avoid
unnecessary test changes.
It also updates cases where an alignment of 16 was specified, instead of
the vector element type alignment.
This patch adds initial fusion for load/multiply/store chains of matrix
operations.
The patch contains roughly two parts:
1. Code generation for a fused load/multiply/store chain (LowerMatrixMultiplyFused).
First, we ensure that both loads of the multiply operands do not alias the store.
If they do, we create new non-aliasing copies of the operands. Note that this
may introduce new basic block. Finally we process TileSize x TileSize blocks.
That is: load tiles from the input operands, multiply and store them.
2. Identify fusion candidates & matrix instructions.
As a first step, collect all instructions with shape info and fusion candidates
(currently @llvm.matrix.multiply calls). Next, try to fuse candidates and
collect instructions eliminated by fusion. Finally iterate over all matrix
instructions, skip the ones eliminated by fusion and lower the rest as usual.
Reviewers: anemet, Gerolf, hfinkel, andrew.w.kaylor, LuoYuanke
Reviewed By: anemet
Differential Revision: https://reviews.llvm.org/D75566
Florian Hahn