KernelOutlining.cpp
12.3 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
//===- KernelOutlining.cpp - Implementation of GPU kernel outlining -------===//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
//
//===----------------------------------------------------------------------===//
//
// This file implements the GPU dialect kernel outlining pass.
//
//===----------------------------------------------------------------------===//
#include "PassDetail.h"
#include "mlir/Dialect/GPU/GPUDialect.h"
#include "mlir/Dialect/GPU/Passes.h"
#include "mlir/Dialect/GPU/Utils.h"
#include "mlir/Dialect/StandardOps/IR/Ops.h"
#include "mlir/IR/BlockAndValueMapping.h"
#include "mlir/IR/Builders.h"
#include "mlir/IR/SymbolTable.h"
#include "mlir/Transforms/RegionUtils.h"
using namespace mlir;
template <typename OpTy>
static void createForAllDimensions(OpBuilder &builder, Location loc,
SmallVectorImpl<Value> &values) {
for (StringRef dim : {"x", "y", "z"}) {
Value v = builder.create<OpTy>(loc, builder.getIndexType(),
builder.getStringAttr(dim));
values.push_back(v);
}
}
// Add operations generating block/thread ids and grid/block dimensions at the
// beginning of the `launchFuncOpBody` region. Add mapping from argument in
// entry block of `launchOpBody`, to the corresponding result value of the added
// operations.
static void injectGpuIndexOperations(Location loc, Region &launchFuncOpBody,
Region &launchOpBody,
BlockAndValueMapping &map) {
OpBuilder builder(loc->getContext());
Block &firstBlock = launchOpBody.front();
builder.setInsertionPointToStart(&launchFuncOpBody.front());
SmallVector<Value, 12> indexOps;
createForAllDimensions<gpu::BlockIdOp>(builder, loc, indexOps);
createForAllDimensions<gpu::ThreadIdOp>(builder, loc, indexOps);
createForAllDimensions<gpu::GridDimOp>(builder, loc, indexOps);
createForAllDimensions<gpu::BlockDimOp>(builder, loc, indexOps);
// Replace the leading 12 function args with the respective thread/block index
// operations. Iterate backwards since args are erased and indices change.
for (auto indexOp : enumerate(indexOps))
map.map(firstBlock.getArgument(indexOp.index()), indexOp.value());
}
static bool isSinkingBeneficiary(Operation *op) {
return isa<ConstantOp, DimOp>(op);
}
LogicalResult mlir::sinkOperationsIntoLaunchOp(gpu::LaunchOp launchOp) {
Region &launchOpBody = launchOp.body();
// Identify uses from values defined outside of the scope of the launch
// operation.
llvm::SetVector<Value> sinkCandidates;
getUsedValuesDefinedAbove(launchOpBody, sinkCandidates);
llvm::SetVector<Value> sunkValues;
llvm::SetVector<Operation *> sunkOperations;
for (Value operand : sinkCandidates) {
Operation *operandOp = operand.getDefiningOp();
if (!operandOp || !isSinkingBeneficiary(operandOp))
continue;
// Only sink operations that do not create new sinkCandidates.
if (!llvm::all_of(operandOp->getOperands(), [&sinkCandidates](Value value) {
return sinkCandidates.count(value);
}))
continue;
sunkValues.insert(operand);
sunkOperations.insert(operandOp);
}
// Insert operations so that the defs get cloned before uses.
BlockAndValueMapping map;
OpBuilder builder(launchOpBody);
DenseSet<Operation *> processed;
SmallVector<Operation *, 2> clonedOps;
while (processed.size() != sunkOperations.size()) {
auto startSize = processed.size();
for (Operation *sunkOperation : sunkOperations) {
if (processed.count(sunkOperation))
continue;
// Operation cant be cloned yet if any of its operands is also being sunk,
// but isnt cloned yet.
if (llvm::any_of(
sunkOperation->getOperands(), [&sunkValues, &map](Value value) {
return sunkValues.count(value) && !map.lookupOrNull(value);
}))
continue;
Operation *clonedOp = builder.clone(*sunkOperation, map);
// Only replace uses within the launch op.
for (auto result : llvm::enumerate(sunkOperation->getResults())) {
auto replacement = clonedOp->getResult(result.index());
for (auto &use : llvm::make_early_inc_range(result.value().getUses()))
if (use.getOwner()->getParentOfType<gpu::LaunchOp>() == launchOp)
use.set(replacement);
}
processed.insert(sunkOperation);
}
if (startSize == processed.size())
return launchOp.emitError(
"found illegal cyclic dependency between operations while sinking");
}
return success();
}
// Outline the `gpu.launch` operation body into a kernel function. Replace
// `gpu.terminator` operations by `gpu.return` in the generated function.
static gpu::GPUFuncOp outlineKernelFuncImpl(gpu::LaunchOp launchOp,
StringRef kernelFnName,
llvm::SetVector<Value> &operands) {
Location loc = launchOp.getLoc();
// Create a builder with no insertion point, insertion will happen separately
// due to symbol table manipulation.
OpBuilder builder(launchOp.getContext());
Region &launchOpBody = launchOp.body();
// Identify uses from values defined outside of the scope of the launch
// operation.
getUsedValuesDefinedAbove(launchOpBody, operands);
// Create the gpu.func operation.
SmallVector<Type, 4> kernelOperandTypes;
kernelOperandTypes.reserve(operands.size());
for (Value operand : operands) {
kernelOperandTypes.push_back(operand.getType());
}
FunctionType type =
FunctionType::get(kernelOperandTypes, {}, launchOp.getContext());
auto outlinedFunc = builder.create<gpu::GPUFuncOp>(loc, kernelFnName, type);
outlinedFunc.setAttr(gpu::GPUDialect::getKernelFuncAttrName(),
builder.getUnitAttr());
BlockAndValueMapping map;
// Map the arguments corresponding to the launch parameters like blockIdx,
// threadIdx, etc.
Region &outlinedFuncBody = outlinedFunc.body();
injectGpuIndexOperations(loc, outlinedFuncBody, launchOpBody, map);
// Map arguments from gpu.launch region to the arguments of the gpu.func
// operation.
Block &entryBlock = outlinedFuncBody.front();
for (auto operand : enumerate(operands))
map.map(operand.value(), entryBlock.getArgument(operand.index()));
// Clone the region of the gpu.launch operation into the gpu.func operation.
// TODO: If cloneInto can be modified such that if a mapping for
// a block exists, that block will be used to clone operations into (at the
// end of the block), instead of creating a new block, this would be much
// cleaner.
launchOpBody.cloneInto(&outlinedFuncBody, map);
// Branch from entry of the gpu.func operation to the block that is cloned
// from the entry block of the gpu.launch operation.
Block &launchOpEntry = launchOpBody.front();
Block *clonedLaunchOpEntry = map.lookup(&launchOpEntry);
builder.setInsertionPointToEnd(&entryBlock);
builder.create<BranchOp>(loc, clonedLaunchOpEntry);
outlinedFunc.walk([](gpu::TerminatorOp op) {
OpBuilder replacer(op);
replacer.create<gpu::ReturnOp>(op.getLoc());
op.erase();
});
return outlinedFunc;
}
gpu::GPUFuncOp mlir::outlineKernelFunc(gpu::LaunchOp launchOp,
StringRef kernelFnName,
llvm::SmallVectorImpl<Value> &operands) {
DenseSet<Value> inputOperandSet;
inputOperandSet.insert(operands.begin(), operands.end());
llvm::SetVector<Value> operandSet(operands.begin(), operands.end());
auto funcOp = outlineKernelFuncImpl(launchOp, kernelFnName, operandSet);
for (auto operand : operandSet) {
if (!inputOperandSet.count(operand))
operands.push_back(operand);
}
return funcOp;
}
// Replace `gpu.launch` operations with an `gpu.launch_func` operation launching
// `kernelFunc`. The kernel func contains the body of the `gpu.launch` with
// constant region arguments inlined.
static void convertToLaunchFuncOp(gpu::LaunchOp launchOp,
gpu::GPUFuncOp kernelFunc,
ValueRange operands) {
OpBuilder builder(launchOp);
builder.create<gpu::LaunchFuncOp>(
launchOp.getLoc(), kernelFunc, launchOp.getGridSizeOperandValues(),
launchOp.getBlockSizeOperandValues(), operands);
launchOp.erase();
}
namespace {
/// Pass that moves the kernel of each LaunchOp into its separate nested module.
///
/// This pass moves the kernel code of each LaunchOp into a function created
/// inside a nested module. It also creates an external function of the same
/// name in the parent module.
///
/// The gpu.modules are intended to be compiled to a cubin blob independently in
/// a separate pass. The external functions can then be annotated with the
/// symbol of the cubin accessor function.
class GpuKernelOutliningPass
: public GpuKernelOutliningBase<GpuKernelOutliningPass> {
public:
void runOnOperation() override {
SymbolTable symbolTable(getOperation());
bool modified = false;
for (auto func : getOperation().getOps<FuncOp>()) {
// Insert just after the function.
Block::iterator insertPt(func.getOperation()->getNextNode());
auto funcWalkResult = func.walk([&](gpu::LaunchOp op) {
llvm::SetVector<Value> operands;
std::string kernelFnName =
Twine(op.getParentOfType<FuncOp>().getName(), "_kernel").str();
// Pull in instructions that can be sunk
if (failed(sinkOperationsIntoLaunchOp(op)))
return WalkResult::interrupt();
gpu::GPUFuncOp outlinedFunc =
outlineKernelFuncImpl(op, kernelFnName, operands);
// Create nested module and insert outlinedFunc. The module will
// originally get the same name as the function, but may be renamed on
// insertion into the parent module.
auto kernelModule = createKernelModule(outlinedFunc, symbolTable);
symbolTable.insert(kernelModule, insertPt);
// Potentially changes signature, pulling in constants.
convertToLaunchFuncOp(op, outlinedFunc, operands.getArrayRef());
modified = true;
return WalkResult::advance();
});
if (funcWalkResult.wasInterrupted())
return signalPassFailure();
}
// If any new module was inserted in this module, annotate this module as
// a container module.
if (modified)
getOperation().setAttr(gpu::GPUDialect::getContainerModuleAttrName(),
UnitAttr::get(&getContext()));
}
private:
// Returns a gpu.module containing kernelFunc and all callees (recursive).
gpu::GPUModuleOp createKernelModule(gpu::GPUFuncOp kernelFunc,
const SymbolTable &parentSymbolTable) {
// TODO: This code cannot use an OpBuilder because it must be inserted into
// a SymbolTable by the caller. SymbolTable needs to be refactored to
// prevent manual building of Ops with symbols in code using SymbolTables
// and then this needs to use the OpBuilder.
auto context = getOperation().getContext();
OpBuilder builder(context);
OperationState state(kernelFunc.getLoc(),
gpu::GPUModuleOp::getOperationName());
gpu::GPUModuleOp::build(builder, state, kernelFunc.getName());
auto kernelModule = cast<gpu::GPUModuleOp>(Operation::create(state));
SymbolTable symbolTable(kernelModule);
symbolTable.insert(kernelFunc);
SmallVector<Operation *, 8> symbolDefWorklist = {kernelFunc};
while (!symbolDefWorklist.empty()) {
if (Optional<SymbolTable::UseRange> symbolUses =
SymbolTable::getSymbolUses(symbolDefWorklist.pop_back_val())) {
for (SymbolTable::SymbolUse symbolUse : *symbolUses) {
StringRef symbolName =
symbolUse.getSymbolRef().cast<FlatSymbolRefAttr>().getValue();
if (symbolTable.lookup(symbolName))
continue;
Operation *symbolDefClone =
parentSymbolTable.lookup(symbolName)->clone();
symbolDefWorklist.push_back(symbolDefClone);
symbolTable.insert(symbolDefClone);
}
}
}
return kernelModule;
}
};
} // namespace
std::unique_ptr<OperationPass<ModuleOp>> mlir::createGpuKernelOutliningPass() {
return std::make_unique<GpuKernelOutliningPass>();
}