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[Draft] [BACKEND] Enhance the remove layout implementation to reduce the duplicated values with different layout in scf.for. #4527

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[Draft] [BACKEND] Enhance the remove layout implementation to reduce the duplicated values with different layout in scf.for. #4527

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3 changes: 2 additions & 1 deletion third_party/intel/include/Dialect/TritonIntelGPU/Transforms/Utility.h
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Original file line number Diff line number Diff line change
Expand Up @@ -50,7 +50,8 @@ LogicalResult getConvertBackwardSlice(
DenseMap<Value, Attribute> &layout,
std::function<bool(Operation *)> stopPropagation = nullptr,
std::function<Value(OpOperand &, Attribute)> getExistingConversion =
nullptr);
nullptr,
bool includeForOp = false);

LLVM::LLVMFuncOp lookupOrCreateSPIRVFn(Operation *symbolTable, StringRef name,
ArrayRef<Type> paramTypes,
Expand Down
78 changes: 50 additions & 28 deletions third_party/intel/lib/TritonIntelGPUTransforms/RemoveLayoutConversions.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -149,19 +149,22 @@ class LayoutRematerialization {
getConvertBackwardSlice(OpOperand &root, Attribute rootEncoding,
SetVector<Value> &slice,
DenseMap<Value, Attribute> &layout,
std::function<bool(Operation *)> stopPropagation);
std::function<bool(Operation *)> stopPropagation,
bool includeForOp = false);

LogicalResult getRematerializableSlice(
OpOperand &root, Attribute rootEncoding, SetVector<Value> &slice,
DenseMap<Value, Attribute> &layout,
std::function<bool(Operation *)> stopPropagation = nullptr);
std::function<bool(Operation *)> stopPropagation = nullptr,
bool includeForOp = false);

private:
void updateRematMapping(SmallVector<std::tuple<Value, Value>> &values);
// Existing tuples of (value, layout) that needs to be updated when recreating
// scf ops. This prevents keeping track of Values that have been delete when
// rewriting slices.
DenseMap<Value, Attribute> mappedValues;
// rewriting slices. The Value maybe mapped to different attributes in remove
// layout.
DenseMap<Value, SmallVector<Attribute>> mappedValues;
// map of the values remat based on encoding.
DenseMap<std::pair<Value, Attribute>, Value> rematMapping;
// DenseMap<std::pair<Operation*, Attribute>, Operation*>
Expand All @@ -174,7 +177,11 @@ void LayoutRematerialization::addRematValue(Value old, Attribute encoding,
Value newV) {
LDBG("addRematValue " << old << " encoding " << encoding << " " << newV);
rematMapping[{old, encoding}] = newV;
mappedValues[old] = encoding;
if (mappedValues.contains(old)) {
mappedValues[old].push_back(encoding);
} else {
mappedValues[old] = {encoding};
}
}

// Remove unneeded values now that we are done with the rematMapping.
Expand Down Expand Up @@ -955,22 +962,28 @@ void LayoutRematerialization::updateRematMapping(
for (auto [old, newV] : values) {
auto it = mappedValues.find(old);
if (it != mappedValues.end()) {
Attribute encoding = it->second;
auto rematIt = rematMapping.find({old, it->second});
assert(rematIt != rematMapping.end());
Value replacedValue = rematIt->second;
rematMapping.erase(rematIt);
mappedValues.erase(it);
// Loop through the replacement value to find the new version of remat
// value. This should be okay as the number of values should be small.
for (auto [before, after] : values) {
if (before == replacedValue) {
replacedValue = after;
break;
SmallVector<Attribute> encodings = it->second;
for (auto encoding : encodings) {
auto rematIt = rematMapping.find({old, encoding});
assert(rematIt != rematMapping.end());
Value replacedValue = rematIt->second;
rematMapping.erase(rematIt);
// Loop through the replacement value to find the new version of remat
// value. This should be okay as the number of values should be small.
for (auto [before, after] : values) {
if (before == replacedValue) {
replacedValue = after;
break;
}
}
rematMapping[{newV, encoding}] = replacedValue;
}
mappedValues.erase(it);
if (mappedValues.contains(newV)) {
mappedValues[newV].append(encodings);
} else {
mappedValues[newV] = std::move(encodings);
}
rematMapping[{newV, encoding}] = replacedValue;
mappedValues[newV] = encoding;
}
}
}
Expand Down Expand Up @@ -1045,6 +1058,7 @@ void LayoutRematerialization::rewriteSlice(SetVector<Value> &slice,
deadOps.push_back(forOp.getOperation());
Block &loopBody = *newForOp.getBody();
for (auto m : argMapping) {
mapping.map(newForOp.getResult(m.first), newForOp.getResult(m.second));
mapping.map(forOp.getResult(m.first), newForOp.getResult(m.second));
int numIndVars = newForOp.getNumInductionVars();
mapping.map(loopBody.getArgument(m.first + numIndVars),
Expand Down Expand Up @@ -1161,8 +1175,12 @@ void LayoutRematerialization::rewriteSlice(SetVector<Value> &slice,
builder.replaceAllUsesWith(std::get<0>(kv), std::get<1>(kv));
}

for (Operation *op : deadOps)
opToDelete.insert(op);
for (Operation *op : deadOps) {
if (!isa<scf::ForOp>(op))
opToDelete.insert(op);
else
op->erase();
}
}

void LayoutRematerialization::rewriteSlice(SetVector<Value> &slice,
Expand All @@ -1175,7 +1193,7 @@ void LayoutRematerialization::rewriteSlice(SetVector<Value> &slice,
LogicalResult LayoutRematerialization::getConvertBackwardSlice(
OpOperand &root, Attribute rootEncoding, SetVector<Value> &slice,
DenseMap<Value, Attribute> &layout,
std::function<bool(Operation *)> stopPropagation) {
std::function<bool(Operation *)> stopPropagation, bool includeForOp) {
// Allow re-using existing conversions for a value. Check dominance of any
// reusable materializations against the root value. This is sufficient
// because the conversions are processed in post-order.
Expand Down Expand Up @@ -1204,15 +1222,18 @@ LogicalResult LayoutRematerialization::getConvertBackwardSlice(
};

return ttgi::getConvertBackwardSlice(root, slice, rootEncoding, layout,
stopPropagation, getExistingConversion);
stopPropagation, getExistingConversion,
includeForOp);
}

LogicalResult LayoutRematerialization::getRematerializableSlice(
OpOperand &root, Attribute rootEncoding, SetVector<Value> &slice,
DenseMap<Value, Attribute> &layout,
std::function<bool(Operation *)> stopPropagation) {
LogicalResult result = getConvertBackwardSlice(
root, rootEncoding, slice, layout, std::move(stopPropagation));
std::function<bool(Operation *)> stopPropagation, bool includeForOp) {

LogicalResult result =
getConvertBackwardSlice(root, rootEncoding, slice, layout,
std::move(stopPropagation), includeForOp);
if (result.failed() || slice.empty())
return failure();

Expand Down Expand Up @@ -1301,8 +1322,9 @@ void LayoutRematerialization::backwardRematerialization(
// rematerialized.
SetVector<Value> slice;
DenseMap<Value, Attribute> layout;
LogicalResult result = getRematerializableSlice(
convertOp.getSrcMutable(), targetType.getEncoding(), slice, layout);
LogicalResult result = getRematerializableSlice(convertOp.getSrcMutable(),
targetType.getEncoding(),
slice, layout, nullptr, true);
if (result.failed()) {
LDBG(" getRematerializableSlice failed");
return;
Expand Down
41 changes: 39 additions & 2 deletions third_party/intel/lib/TritonIntelGPUTransforms/Utility.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -182,7 +182,8 @@ LogicalResult getConvertBackwardSlice(
OpOperand &root, SetVector<Value> &slice, Attribute rootEncoding,
DenseMap<Value, Attribute> &layout,
std::function<bool(Operation *)> stopPropagation,
std::function<Value(OpOperand &, Attribute)> getExistingConversion) {
std::function<Value(OpOperand &, Attribute)> getExistingConversion,
bool includeForOp) {
DenseSet<std::pair<OpOperand *, Attribute>> seen;
SmallVector<std::pair<OpOperand *, Attribute>> queue;

Expand All @@ -197,6 +198,12 @@ LogicalResult getConvertBackwardSlice(

auto updateLayout = [&](Value value, Attribute encoding) {
assert(isTensorOrTensorPointerType(value.getType()));
auto tensorType = getRankedTensorType(value.getType());
auto originEncoding = tensorType.getEncoding();
if (originEncoding == encoding) {
return success();
}

slice.insert(value);
Attribute &existing = layout[value];
if (existing && existing != encoding)
Expand All @@ -213,8 +220,38 @@ LogicalResult getConvertBackwardSlice(
continue;
// Skip propagating through for op results for now.
// TODO: enable this based on needs.
if (currentValue.getDefiningOp<scf::ForOp>())
if (auto forOp = currentValue.getDefiningOp<scf::ForOp>()) {
if (!includeForOp)
return failure();
if (stopPropagation && stopPropagation(forOp))
continue;
unsigned argIdx = mlir::cast<OpResult>(currentValue).getResultNumber();
int numIndVars = forOp.getNumInductionVars();
Block &loopBody = *forOp.getBody();
auto blockArg = loopBody.getArgument(argIdx + numIndVars);

Value existing;
if (getExistingConversion &&
(existing = getExistingConversion(*currentValueUse, encoding))) {
if (failed(updateLayout(currentValue, encoding)))
return failure();

continue;
}
return failure();

OpOperand *initOperand = forOp.getTiedLoopInit(blockArg);
OpOperand &yieldOperand = loopBody.getTerminator()->getOpOperand(argIdx);
llvm::outs() << "johnlu getBackward slice check scf.for initOperand: "
<< initOperand->get() << "\n";
llvm::outs() << "johnlu getBackward slice check scf.for yieldOperand: "
<< yieldOperand.get() << "\n";
if (failed(updateLayout(blockArg, encoding)))
return failure();
enqueue(*initOperand, encoding);
enqueue(yieldOperand, encoding);
continue;
}
if (failed(updateLayout(currentValue, encoding)))
return failure();

Expand Down
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