more comments to TypeConverter & update warpTileSize
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@@ -2,7 +2,6 @@
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#include "triton/Dialect/Triton/IR/Dialect.h"
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#include "triton/Dialect/TritonGPU/IR/Dialect.h"
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#include <algorithm>
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#include <llvm-6.0/llvm/Support/ErrorHandling.h>
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using namespace mlir;
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@@ -23,6 +22,7 @@ TritonGPUTypeConverter::TritonGPUTypeConverter(MLIRContext *context,
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int64_t rank = tensorType.getRank();
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int64_t numElements = tensorType.getNumElements();
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// TODO: are there any better ways to raise this error?
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if (!(numElements >= numThreads)) {
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SmallVector<char> buffer;
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llvm::raw_svector_ostream os(buffer);
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@@ -38,16 +38,18 @@ TritonGPUTypeConverter::TritonGPUTypeConverter(MLIRContext *context,
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// Now we assume:
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// contiguous = 1, order = 0, 1, 2, ...,
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llvm::SmallVector<unsigned> threadTileSize(rank, 1); // naive layout
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// TODO: compute warpTileSize.
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llvm::SmallVector<unsigned> warpTileSize(rank, 1);
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llvm::SmallVector<unsigned> blockTileSize(rank);
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llvm::SmallVector<unsigned> order(rank);
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int remainingThreads = numThreads;
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int remainingLanes = /*warp size*/32;
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for (int64_t dim = 0; dim < rank; ++dim) {
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blockTileSize[dim] = std::clamp(remainingThreads, 1, int(shape[dim]));
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warpTileSize[dim] = std::clamp(remainingLanes, 1, int(shape[dim]));
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order[dim] = dim;
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remainingThreads /= blockTileSize[dim];
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remainingLanes /= warpTileSize[dim];
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// TODO: will we need repetition?
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}
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Attribute encoding = triton::gpu::TritonGPUBlockedEncodingAttr::get(
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@@ -55,17 +57,28 @@ TritonGPUTypeConverter::TritonGPUTypeConverter(MLIRContext *context,
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return RankedTensorType::get(shape, elementType, encoding);
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});
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//
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// materailizations
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//
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// This will be called when (newArgType != origArgType)
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// This will create newArg, and map(origArg, newArg)
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addArgumentMaterialization([&](OpBuilder &builder, RankedTensorType tensorType,
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ValueRange inputs, Location loc) {
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llvm_unreachable("Not implemented");
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return llvm::None;
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});
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// If the origValue still has live user(s), use this to
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// convert origValue to newValue
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addSourceMaterialization([&](OpBuilder &builder, RankedTensorType tensorType,
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ValueRange inputs, Location loc) {
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llvm_unreachable("Not implemented");
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return llvm::None;
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});
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// This will be called when (desiredType != newOperandType)
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// where, desiredType = typeConverter->convertType(origType)
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// NOTE: only for remapped values.
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addTargetMaterialization([&](OpBuilder &builder, RankedTensorType tensorType,
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ValueRange inputs, Location loc) {
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assert(inputs.size() == 1);
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@@ -104,9 +117,9 @@ TritonGPUConversionTarget::TritonGPUConversionTarget(
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if (aEncoding && aEncoding.isa<triton::gpu::TritonGPUSharedEncodingAttr>() &&
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bEncoding && bEncoding.isa<triton::gpu::TritonGPUSharedEncodingAttr>())
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return true;
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// TODO: we should delete this
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if (this->typeConverter.isLegal(dotOp))
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return true;
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// // TODO: we should delete this
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// if (this->typeConverter.isLegal(dotOp))
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// return true;
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return false;
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});
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