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[NFC] Change term kMajor to kContig #5679

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Merged
antiagainst merged 1 commit into from
Jan 23, 2025
Merged

[NFC] Change term kMajor to kContig #5679

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4 changes: 2 additions & 2 deletions include/triton/Dialect/TritonGPU/IR/Dialect.h
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Original file line number Diff line number Diff line change
Expand Up @@ -178,11 +178,11 @@ unsigned getNumCTAs(Attribute layout);
// len(shape) == rank.
SmallVector<unsigned> getMatrixOrder(unsigned rank, bool rowMajor);

// Return the order that represents that the dot operand is in kMajor
// Return the order that represents that the dot operand is in kContig
// (contiguous in the inner dimension) or it's contiguous on the outer
// dimension.
SmallVector<unsigned> getOrderForDotOperand(unsigned opIdx, unsigned rank,
bool kMajor);
bool kContig);

bool isExpensiveCat(CatOp cat, Attribute targetEncoding);

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16 changes: 8 additions & 8 deletions lib/Dialect/TritonGPU/IR/Dialect.cpp
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Expand Up @@ -227,15 +227,15 @@ SmallVector<unsigned> getMatrixOrder(unsigned rank, bool rowMajor) {
}

SmallVector<unsigned> getOrderForDotOperand(unsigned opIdx, unsigned rank,
bool kMajor) {
// kMajor: if true, the matrix is fastest-running on k,
bool kContig) {
// kContig: if true, the matrix is fastest-running on k,
// otherwise it is on m (resp. n)
// opIdx=0: [batch, m, k] if rank == 3 else [m, k]
// opIdx=1: [batch, k, n] if rank == 3 else [k, n]
// batch (if rank == 3) is always the slowest running dimension
assert(rank == 2 || rank == 3);
assert(opIdx == 0 || opIdx == 1);
auto rowMajor = bool(opIdx) != kMajor;
auto rowMajor = bool(opIdx) != kContig;
return getMatrixOrder(rank, rowMajor);
}

Expand Down Expand Up @@ -268,7 +268,7 @@ SmallVector<unsigned> getOrder(Attribute layout) {
}
if (auto dotLayout = dyn_cast<DotOperandEncodingAttr>(layout)) {
auto rank = dotLayout.getWarpsPerCTA().size();
return getOrderForDotOperand(dotLayout.getOpIdx(), rank, /*kMajor*/ true);
return getOrderForDotOperand(dotLayout.getOpIdx(), rank, /*kContig*/ true);
}
if (auto sliceLayout = dyn_cast<SliceEncodingAttr>(layout)) {
SmallVector<unsigned> parentOrder = getOrder(sliceLayout.getParent());
Expand Down Expand Up @@ -987,7 +987,7 @@ SmallVector<unsigned> DotOperandEncodingAttr::getWarpOrder() const {
}
SmallVector<unsigned> DotOperandEncodingAttr::getThreadOrder() const {
return getOrderForDotOperand(getOpIdx(), getWarpsPerCTA().size(),
/*kMajor*/ true);
/*kContig*/ true);
}

LogicalResult DotOperandEncodingAttr::verify(
Expand Down Expand Up @@ -1959,7 +1959,7 @@ SmallVector<unsigned> AMDMfmaEncodingAttr::getRepOrder() const {
SmallVector<unsigned>
AMDMfmaEncodingAttr::getRepOrderForOperand(int opIdx) const {
auto rank = getWarpsPerCTA().size();
return getOrderForDotOperand(opIdx, rank, /*kMajor*/ true);
return getOrderForDotOperand(opIdx, rank, /*kContig*/ true);
}

SmallVector<unsigned>
Expand Down Expand Up @@ -2027,7 +2027,7 @@ SmallVector<unsigned> AMDWmmaEncodingAttr::getRepOrder() const {
SmallVector<unsigned>
AMDWmmaEncodingAttr::getRepOrderForOperand(int opIdx) const {
auto rank = getWarpsPerCTA().size();
return getOrderForDotOperand(opIdx, rank, /*kMajor*/ true);
return getOrderForDotOperand(opIdx, rank, /*kContig*/ true);
}

SmallVector<unsigned>
Expand Down Expand Up @@ -2219,7 +2219,7 @@ SmallVector<unsigned> NvidiaMmaEncodingAttr::getSizePerThread() const {
SmallVector<unsigned>
NvidiaMmaEncodingAttr::getRepOrderForOperand(int opIdx) const {
auto rank = getWarpsPerCTA().size();
return getOrderForDotOperand(opIdx, rank, /*kMajor*/ true);
return getOrderForDotOperand(opIdx, rank, /*kContig*/ true);
}

SmallVector<unsigned>
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6 changes: 3 additions & 3 deletions third_party/amd/lib/TritonAMDGPUToLLVM/ConvertLayoutOpToLLVM/SharedToDotOperandHelper.cpp
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Expand Up @@ -74,7 +74,7 @@ Value computeBasePtr(ConversionPatternRewriter &rewriter, Location loc,
return base;
}

bool isKMajor(llvm::ArrayRef<unsigned> order, int opIdx) {
bool isKContig(llvm::ArrayRef<unsigned> order, int opIdx) {
auto rank = order.size();
int kdim = opIdx == 0 ? rank - 1 : rank - 2;
return order[0] == kdim;
Expand Down Expand Up @@ -102,9 +102,9 @@ bool isSwizzlePatternFitsIntoBlock(const SharedEncodingAttr sharedLayout,
const auto swizzleSlowDimSize =
sharedLayout.getMaxPhase() * sharedLayout.getPerPhase();
const auto swizzlePatternSizeK =
isKMajor(order, opIdx) ? swizzleFastDimSize : swizzleSlowDimSize;
isKContig(order, opIdx) ? swizzleFastDimSize : swizzleSlowDimSize;
const auto swizzlePatternSizeNonK =
!isKMajor(order, opIdx) ? swizzleFastDimSize : swizzleSlowDimSize;
!isKContig(order, opIdx) ? swizzleFastDimSize : swizzleSlowDimSize;

const auto blockSizeK = mfmaInstrK * reps[reps.size() - 1];
const auto blockSizeNonK = mfmaInstrNonK * warpsPerBlockNonK;
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2 changes: 1 addition & 1 deletion third_party/amd/lib/TritonAMDGPUToLLVM/ConvertLayoutOpToLLVM/SharedToDotOperandHelper.h
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Expand Up @@ -36,7 +36,7 @@ Value computeBasePtr(ConversionPatternRewriter &rewriter, Location loc,
const SharedMemoryObject &smemObj,
ArrayRef<Value> strides);

bool isKMajor(llvm::ArrayRef<unsigned> order, int opIdx);
bool isKContig(llvm::ArrayRef<unsigned> order, int opIdx);

using computeTensorElemMappingInBlockT =
std::function<llvm::SmallVector<llvm::SmallVector<Value>>(
Expand Down
2 changes: 1 addition & 1 deletion third_party/amd/lib/TritonAMDGPUToLLVM/ConvertLayoutOpToLLVM/SharedToDotOperandMFMA.cpp
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Expand Up @@ -279,7 +279,7 @@ Value convertLayout(int opIdx, ConversionPatternRewriter &rewriter,
Value smemBase;
auto smemStrides = smemObj.getStrides(aTensorTy, loc, rewriter);
bool isFastPath =
!AMD::isKMajor(order, opIdx) && !hasSwizzleEnabled(sharedLayout);
!AMD::isKContig(order, opIdx) && !hasSwizzleEnabled(sharedLayout);
if (isFastPath) {
// fast path handles tensors that are not k-major and have swizzling
// disabled, in which case offsets computation can be simplified
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4 changes: 2 additions & 2 deletions third_party/nvidia/lib/TritonNVIDIAGPUToLLVM/DotOpToLLVM/MMAv2.cpp
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Expand Up @@ -498,13 +498,13 @@ LogicalResult convertDot(const LLVMTypeConverter *typeConverter,
// getValuesFromDotOperandLayoutStruct as both a and b are K-major
assert(dotOpA.getRepOrder() == getOrderForDotOperand(dotOpA.getOpIdx(),
aShapePerCTA.size(),
/*kMajor=*/true));
/*kContig=*/true));
auto ha = getValuesFromDotOperandLayoutStruct(
typeConverter, loc, rewriter, loadedA, repBatch, repM, repK, aTensorTy);

assert(dotOpB.getRepOrder() == getOrderForDotOperand(dotOpB.getOpIdx(),
bShapePerCTA.size(),
/*kMajor=*/true));
/*kContig=*/true));
auto hb = getValuesFromDotOperandLayoutStruct(
typeConverter, loc, rewriter, loadedB, repBatch, repN, repK, bTensorTy);

Expand Down