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Add back barrier after asserts #5043

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Merged
ThomasRaoux merged 1 commit into from
Nov 2, 2024
Merged

Add back barrier after asserts #5043

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2 changes: 1 addition & 1 deletion include/triton/Dialect/Triton/IR/TritonOps.td
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Expand Up @@ -891,7 +891,7 @@ def TT_AssertOp : TT_Op<"assert", [MemoryEffects<[MemWrite<GlobalMemory>]>]> {
`tt.assert` takes a condition tensor and a message string.
If the condition is false, the message is printed, and the program is aborted.
}];
let arguments = (ins TT_Tensor:$condition, StrAttr:$message);
let arguments = (ins AnyTypeOf<[I1, I1Tensor]>:$condition, StrAttr:$message);
let assemblyFormat = "$condition `,` $message attr-dict `:` type($condition)";
}

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8 changes: 8 additions & 0 deletions lib/Conversion/TritonGPUToLLVM/AssertOpToLLVM.cpp
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Expand Up @@ -35,6 +35,14 @@ struct AssertOpConversion : public ConvertOpToLLVMPattern<triton::AssertOp> {
}
}
llAssert(op, condition, adaptor.getMessage(), rewriter);
if (isa<RankedTensorType>(op.getCondition().getType())) {
// Add a barrier to avoid a race condition in case an assert is followed
// by an op that may trap if the assert condition is true. Since the
// tensor in those two operations may have different layout we need to
// make sure all the threads are done executing the assert before going to
// the next op.
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@peterbell10 peterbell10 Nov 1, 2024

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btw this highlights an interesting thing I noticed a while back. Sometimes we do the same computation in multiple different layouts when there are assert statements because the assertion path doesn't have a data flow path to the next layout anchor operation.

It's not really the end of the world, but an interesting quirk of the remove layout conversion code.

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@ThomasRaoux ThomasRaoux Nov 1, 2024

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right, yes this is definitely a limitation as we haven't tried very hard to make assert efficient.

barrier();
}
rewriter.eraseOp(op);
return success();
}
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4 changes: 0 additions & 4 deletions python/triton/language/semantic.py
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Expand Up @@ -1724,10 +1724,6 @@ def device_print(prefix: str, args: List[tl.tensor], hex: bool, builder: ir.buil
def device_assert(cond: tl.tensor, msg: str, builder: ir.builder) -> tl.tensor:
if not builder.options.debug:
return
cond_ty = cond.type
if not cond_ty.is_block():
cond_ty = tl.block_type(cond_ty.scalar, (1, ))
cond = tl.tensor(builder.create_splat(cond.handle, (1, )), cond_ty)
return tl.tensor(builder.create_assert(cond.handle, msg), tl.void)


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2 changes: 2 additions & 0 deletions test/Conversion/tritongpu_to_llvm.mlir
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Expand Up @@ -1906,6 +1906,8 @@ module attributes {"triton_gpu.num-ctas" = 1 : i32, "triton_gpu.num-warps" = 4 :
// CHECK-DAG: llvm.mlir.global internal constant @assertFunc_0("unknown\00") {addr_space = 0 : i32}
// CHECK-DAG: llvm.mlir.global internal constant @assertFile_0("inner_call\00") {addr_space = 0 : i32}
// CHECK-DAG: llvm.mlir.global internal constant @assertMessage_0("assert text\00") {addr_space = 0 : i32}
// CHECK: llvm.call @__assertfail
// CHECK: nvvm.barrier0
module attributes {"triton_gpu.num-ctas" = 1 : i32, "triton_gpu.num-warps" = 4 : i32, triton_gpu.target = "cuda:90", "triton_gpu.threads-per-warp" = 32 : i32} {
tt.func public @add_kernel(%arg0: tensor<1xi1, #blocked>) {
tt.assert %arg0, "assert text" : tensor<1xi1, #blocked> loc(#loc5)
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