Successfully identified regression in *llvm* in CI configuration
tcwg_bmk_llvm_tx1/llvm-master-aarch64-spec2k6-O2_LTO. So far, this commit has
regressed CI configurations:
- tcwg_bmk_llvm_tx1/llvm-master-aarch64-spec2k6-O2_LTO
Culprit:
<cut>
commit 428a62f65f16f1640b1bfe033d20e6a4f545dd3e
Author: thomasraoux <thomasra...@google.com>
Date: Wed Jun 9 09:42:32 2021 -0700
[mlir][gpu] Add op to create MMA constant matrix
This allow creating a matrix with all elements set to a given value. This is
needed to be able to implement a simple dot op.
Differential Revision: https://reviews.llvm.org/D103870
</cut>
Results regressed to (for first_bad == 428a62f65f16f1640b1bfe033d20e6a4f545dd3e)
# reset_artifacts:
-10
# build_abe binutils:
-9
# build_abe stage1 -- --set gcc_override_configure=--disable-libsanitizer:
-8
# build_abe linux:
-7
# build_abe glibc:
-6
# build_abe stage2 -- --set gcc_override_configure=--disable-libsanitizer:
-5
# build_llvm true:
-3
# true:
0
# benchmark -O2_LTO --
artifacts/build-428a62f65f16f1640b1bfe033d20e6a4f545dd3e/results_id:
1
# 400.perlbench,perlbench_base.default regressed by 103
from (for last_good == 3b46283c1539f89619f2b40ab7732f434d7c68ff)
# reset_artifacts:
-10
# build_abe binutils:
-9
# build_abe stage1 -- --set gcc_override_configure=--disable-libsanitizer:
-8
# build_abe linux:
-7
# build_abe glibc:
-6
# build_abe stage2 -- --set gcc_override_configure=--disable-libsanitizer:
-5
# build_llvm true:
-3
# true:
0
# benchmark -O2_LTO --
artifacts/build-3b46283c1539f89619f2b40ab7732f434d7c68ff/results_id:
1
Artifacts of last_good build:
https://ci.linaro.org/job/tcwg_bmk_ci_llvm-bisect-tcwg_bmk_tx1-llvm-master-aarch64-spec2k6-O2_LTO/18/artifact/artifacts/build-3b46283c1539f89619f2b40ab7732f434d7c68ff/
Results ID of last_good:
tx1_64/tcwg_bmk_llvm_tx1/bisect-llvm-master-aarch64-spec2k6-O2_LTO/1827
Artifacts of first_bad build:
https://ci.linaro.org/job/tcwg_bmk_ci_llvm-bisect-tcwg_bmk_tx1-llvm-master-aarch64-spec2k6-O2_LTO/18/artifact/artifacts/build-428a62f65f16f1640b1bfe033d20e6a4f545dd3e/
Results ID of first_bad:
tx1_64/tcwg_bmk_llvm_tx1/bisect-llvm-master-aarch64-spec2k6-O2_LTO/1831
Build top page/logs:
https://ci.linaro.org/job/tcwg_bmk_ci_llvm-bisect-tcwg_bmk_tx1-llvm-master-aarch64-spec2k6-O2_LTO/18/
Configuration details:
Reproduce builds:
<cut>
mkdir investigate-llvm-428a62f65f16f1640b1bfe033d20e6a4f545dd3e
cd investigate-llvm-428a62f65f16f1640b1bfe033d20e6a4f545dd3e
git clone https://git.linaro.org/toolchain/jenkins-scripts
mkdir -p artifacts/manifests
curl -o artifacts/manifests/build-baseline.sh
https://ci.linaro.org/job/tcwg_bmk_ci_llvm-bisect-tcwg_bmk_tx1-llvm-master-aarch64-spec2k6-O2_LTO/18/artifact/artifacts/manifests/build-baseline.sh
--fail
curl -o artifacts/manifests/build-parameters.sh
https://ci.linaro.org/job/tcwg_bmk_ci_llvm-bisect-tcwg_bmk_tx1-llvm-master-aarch64-spec2k6-O2_LTO/18/artifact/artifacts/manifests/build-parameters.sh
--fail
curl -o artifacts/test.sh
https://ci.linaro.org/job/tcwg_bmk_ci_llvm-bisect-tcwg_bmk_tx1-llvm-master-aarch64-spec2k6-O2_LTO/18/artifact/artifacts/test.sh
--fail
chmod +x artifacts/test.sh
# Reproduce the baseline build (build all pre-requisites)
./jenkins-scripts/tcwg_bmk-build.sh @@ artifacts/manifests/build-baseline.sh
# Save baseline build state (which is then restored in artifacts/test.sh)
rsync -a --del --delete-excluded --exclude bisect/ --exclude artifacts/
--exclude llvm/ ./ ./bisect/baseline/
cd llvm
# Reproduce first_bad build
git checkout --detach 428a62f65f16f1640b1bfe033d20e6a4f545dd3e
../artifacts/test.sh
# Reproduce last_good build
git checkout --detach 3b46283c1539f89619f2b40ab7732f434d7c68ff
../artifacts/test.sh
cd ..
</cut>
History of pending regressions and results:
https://git.linaro.org/toolchain/ci/base-artifacts.git/log/?h=linaro-local/ci/tcwg_bmk_llvm_tx1/llvm-master-aarch64-spec2k6-O2_LTO
Artifacts:
https://ci.linaro.org/job/tcwg_bmk_ci_llvm-bisect-tcwg_bmk_tx1-llvm-master-aarch64-spec2k6-O2_LTO/18/artifact/artifacts/
Build log:
https://ci.linaro.org/job/tcwg_bmk_ci_llvm-bisect-tcwg_bmk_tx1-llvm-master-aarch64-spec2k6-O2_LTO/18/consoleText
Full commit (up to 1000 lines):
<cut>
commit 428a62f65f16f1640b1bfe033d20e6a4f545dd3e
Author: thomasraoux <thomasra...@google.com>
Date: Wed Jun 9 09:42:32 2021 -0700
[mlir][gpu] Add op to create MMA constant matrix
This allow creating a matrix with all elements set to a given value. This is
needed to be able to implement a simple dot op.
Differential Revision: https://reviews.llvm.org/D103870
---
mlir/include/mlir/Dialect/GPU/GPUOps.td | 45 ++++++++++++++++++++++
mlir/lib/Conversion/GPUToNVVM/WmmaOpsToNvvm.cpp | 42 +++++++++++++++++++-
.../Conversion/GPUToNVVM/wmma-ops-to-nvvm.mlir | 25 ++++++++++++
mlir/test/Dialect/GPU/ops.mlir | 4 ++
4 files changed, 115 insertions(+), 1 deletion(-)
diff --git a/mlir/include/mlir/Dialect/GPU/GPUOps.td
b/mlir/include/mlir/Dialect/GPU/GPUOps.td
index 8e2520b675ae..1e78e4af4d51 100644
--- a/mlir/include/mlir/Dialect/GPU/GPUOps.td
+++ b/mlir/include/mlir/Dialect/GPU/GPUOps.td
@@ -1022,4 +1022,49 @@ def GPU_SubgroupMmaComputeOp :
GPU_Op<"subgroup_mma_compute",
let verifier = [{ return ::verify(*this); }];
}
+def GPU_SubgroupMmaConstantMatrixOp : GPU_Op<"subgroup_mma_constant_matrix",
+ [NoSideEffect,
+ TypesMatchWith<"value type matches element type of mma_matrix",
+ "res", "value",
+ "$_self.cast<gpu::MMAMatrixType>().getElementType()">]>{
+
+ let summary = "GPU warp synchronous constant matrix";
+
+ let description = [{
+ The `gpu.subgroup_mma_constant_matrix` creates a `!gpu.mma_matrix` with
+ constant elements.
+
+ The operation takes a scalar input and return a `!gpu.mma_matrix` where
each
+ element of is equal to the operand constant. The destination mma_matrix
type
+ must have elememt type equal to the constant type. Since the layout of
+ `!gpu.mma_matrix` is opaque this only support setting all the elements to
+ the same value.
+
+ This op is meant to be used along with `gpu.subgroup_mma_compute`.
+
+ Example:
+
+ ```mlir
+ %0 = gpu.subgroup_mma_constant_matrix %a :
+ !gpu.mma_matrix<16x16xf16, "AOp">
+ %1 = gpu.subgroup_mma_constant_matrix %b :
+ !gpu.mma_matrix<16x16xf32, "COp">
+ ```
+ }];
+
+ let arguments = (ins AnyTypeOf<[F16, F32]>:$value);
+
+ let results = (outs GPU_MMAMatrix:$res);
+
+ let extraClassDeclaration = [{
+ gpu::MMAMatrixType getType() {
+ return res().getType().cast<gpu::MMAMatrixType>();
+ }
+ }];
+
+ let assemblyFormat = [{
+ $value attr-dict `:` type($res)
+ }];
+}
+
#endif // GPU_OPS
diff --git a/mlir/lib/Conversion/GPUToNVVM/WmmaOpsToNvvm.cpp
b/mlir/lib/Conversion/GPUToNVVM/WmmaOpsToNvvm.cpp
index d72c8c217f86..d46a185dec22 100644
--- a/mlir/lib/Conversion/GPUToNVVM/WmmaOpsToNvvm.cpp
+++ b/mlir/lib/Conversion/GPUToNVVM/WmmaOpsToNvvm.cpp
@@ -348,12 +348,52 @@ struct WmmaMmaOpToNVVMLowering
}
};
+/// Convert GPU MMA ConstantMatrixOp to a chain of InsertValueOp.
+struct WmmaConstantOpToNVVMLowering
+ : public ConvertOpToLLVMPattern<gpu::SubgroupMmaConstantMatrixOp> {
+ using ConvertOpToLLVMPattern<
+ gpu::SubgroupMmaConstantMatrixOp>::ConvertOpToLLVMPattern;
+
+ LogicalResult
+ matchAndRewrite(gpu::SubgroupMmaConstantMatrixOp subgroupMmaConstantOp,
+ ArrayRef<Value> operands,
+ ConversionPatternRewriter &rewriter) const override {
+ if (failed(areAllLLVMTypes(subgroupMmaConstantOp.getOperation(), operands,
+ rewriter)))
+ return failure();
+ Location loc = subgroupMmaConstantOp.getLoc();
+ Value cst = operands[0];
+ LLVM::LLVMStructType type = convertMMAToLLVMType(
+ subgroupMmaConstantOp.getType().cast<gpu::MMAMatrixType>());
+ // If the element type is a vector create a vector from the operand.
+ if (auto vecType = type.getBody()[0].dyn_cast<VectorType>()) {
+ Value vecCst = rewriter.create<LLVM::UndefOp>(loc, vecType);
+ for (int64_t vecEl = 0; vecEl < vecType.getNumElements(); vecEl++) {
+ Value idx = rewriter.create<LLVM::ConstantOp>(
+ loc, typeConverter->convertType(rewriter.getIntegerType(32)),
+ rewriter.getI32ArrayAttr(vecEl));
+ vecCst = rewriter.create<LLVM::InsertElementOp>(loc, vecType, vecCst,
+ cst, idx);
+ }
+ cst = vecCst;
+ }
+ Value matrixStruct = rewriter.create<LLVM::UndefOp>(loc, type);
+ for (size_t i : llvm::seq(size_t(0), type.getBody().size())) {
+ matrixStruct = rewriter.create<LLVM::InsertValueOp>(
+ loc, matrixStruct, cst, rewriter.getI32ArrayAttr(i));
+ }
+ rewriter.replaceOp(subgroupMmaConstantOp, matrixStruct);
+ return success();
+ }
+};
+
} // anonymous namespace
namespace mlir {
void populateGpuWMMAToNVVMConversionPatterns(LLVMTypeConverter &converter,
RewritePatternSet &patterns) {
patterns.insert<WmmaLoadOpToNVVMLowering, WmmaMmaOpToNVVMLowering,
- WmmaStoreOpToNVVMLowering>(converter);
+ WmmaStoreOpToNVVMLowering, WmmaConstantOpToNVVMLowering>(
+ converter);
}
} // namespace mlir
diff --git a/mlir/test/Conversion/GPUToNVVM/wmma-ops-to-nvvm.mlir
b/mlir/test/Conversion/GPUToNVVM/wmma-ops-to-nvvm.mlir
index de5d0d3fcf1c..f692dffdfcba 100644
--- a/mlir/test/Conversion/GPUToNVVM/wmma-ops-to-nvvm.mlir
+++ b/mlir/test/Conversion/GPUToNVVM/wmma-ops-to-nvvm.mlir
@@ -151,3 +151,28 @@ gpu.module @test_module {
return
}
}
+
+
+// -----
+
+gpu.module @test_module {
+
+// CHECK-LABEL: func @gpu_wmma_constant_op
+// CHECK: %[[CST:.+]] = llvm.mlir.constant(1.000000e+00 : f16) : f16
+// CHECK: %[[V0:.+]] = llvm.mlir.undef : vector<2xf16>
+// CHECK: %[[C0:.+]] = llvm.mlir.constant([0 : i32]) : i32
+// CHECK: %[[V1:.+]] = llvm.insertelement %[[CST]], %[[V0]][%[[C0]] :
i32] : vector<2xf16>
+// CHECK: %[[C1:.+]] = llvm.mlir.constant([1 : i32]) : i32
+// CHECK: %[[V2:.+]] = llvm.insertelement %[[CST]], %[[V1]][%[[C1]] :
i32] : vector<2xf16>
+// CHECK: %[[M0:.+]] = llvm.mlir.undef : !llvm.struct<(vector<2xf16>,
vector<2xf16>, vector<2xf16>, vector<2xf16>)>
+// CHECK: %[[M1:.+]] = llvm.insertvalue %[[V2]], %[[M0]][0 : i32] :
!llvm.struct<(vector<2xf16>, vector<2xf16>, vector<2xf16>, vector<2xf16>)>
+// CHECK: %[[M2:.+]] = llvm.insertvalue %[[V2]], %[[M1]][1 : i32] :
!llvm.struct<(vector<2xf16>, vector<2xf16>, vector<2xf16>, vector<2xf16>)>
+// CHECK: %[[M3:.+]] = llvm.insertvalue %[[V2]], %[[M2]][2 : i32] :
!llvm.struct<(vector<2xf16>, vector<2xf16>, vector<2xf16>, vector<2xf16>)>
+// CHECK: %[[M4:.+]] = llvm.insertvalue %[[V2]], %[[M3]][3 : i32] :
!llvm.struct<(vector<2xf16>, vector<2xf16>, vector<2xf16>, vector<2xf16>)>
+// CHECK: llvm.return %[[M4]] : !llvm.struct<(vector<2xf16>,
vector<2xf16>, vector<2xf16>, vector<2xf16>)>
+ func @gpu_wmma_constant_op() ->(!gpu.mma_matrix<16x16xf16, "COp">) {
+ %cst = constant 1.0 : f16
+ %C = gpu.subgroup_mma_constant_matrix %cst : !gpu.mma_matrix<16x16xf16,
"COp">
+ return %C : !gpu.mma_matrix<16x16xf16, "COp">
+ }
+}
diff --git a/mlir/test/Dialect/GPU/ops.mlir b/mlir/test/Dialect/GPU/ops.mlir
index a98fe1c49683..1bed13c4b21a 100644
--- a/mlir/test/Dialect/GPU/ops.mlir
+++ b/mlir/test/Dialect/GPU/ops.mlir
@@ -201,8 +201,12 @@ module attributes {gpu.container_module} {
// CHECK: %[[wg:.*]] = memref.alloca()
%i = constant 16 : index
// CHECK: %[[i:.*]] = constant 16 : index
+ %cst = constant 1.000000e+00 : f32
+ // CHECK: %[[cst:.*]] = constant 1.000000e+00 : f32
%0 = gpu.subgroup_mma_load_matrix %wg[%i, %i] {leadDimension = 32 : index}
: memref<32x32xf16, 3> -> !gpu.mma_matrix<16x16xf16, "AOp">
// CHECK: gpu.subgroup_mma_load_matrix %[[wg]][%[[i]], %[[i]]]
{leadDimension = 32 : index} : memref<32x32xf16, 3> ->
!gpu.mma_matrix<16x16xf16, "AOp">
+ %1 = gpu.subgroup_mma_constant_matrix %cst : !gpu.mma_matrix<16x16xf32,
"COp">
+ // CHECK: gpu.subgroup_mma_constant_matrix %[[cst]] :
!gpu.mma_matrix<16x16xf32, "COp">
return
}
}
</cut>
_______________________________________________
linaro-toolchain mailing list
linaro-toolchain@lists.linaro.org
https://lists.linaro.org/mailman/listinfo/linaro-toolchain
