1 | //===- LowerGpuOpsToNVVMOps.cpp - MLIR GPU to NVVM lowering passes --------===// |
---|---|
2 | // |
3 | // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. |
4 | // See https://llvm.org/LICENSE.txt for license information. |
5 | // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception |
6 | // |
7 | //===----------------------------------------------------------------------===// |
8 | // |
9 | // This file implements a pass to generate NVVMIR operations for higher-level |
10 | // GPU operations. |
11 | // |
12 | //===----------------------------------------------------------------------===// |
13 | |
14 | #include "mlir/Conversion/ConvertToLLVM/ToLLVMInterface.h" |
15 | #include "mlir/Conversion/ConvertToLLVM/ToLLVMPass.h" |
16 | #include "mlir/Conversion/GPUCommon/GPUCommonPass.h" |
17 | #include "mlir/Conversion/GPUToNVVM/GPUToNVVM.h" |
18 | #include "mlir/Conversion/GPUToNVVM/GPUToNVVMPass.h" |
19 | #include "mlir/Conversion/LLVMCommon/ConversionTarget.h" |
20 | #include "mlir/Conversion/LLVMCommon/LoweringOptions.h" |
21 | #include "mlir/Conversion/LLVMCommon/TypeConverter.h" |
22 | #include "mlir/Dialect/ControlFlow/IR/ControlFlow.h" |
23 | #include "mlir/Dialect/ControlFlow/IR/ControlFlowOps.h" |
24 | #include "mlir/Dialect/Func/IR/FuncOps.h" |
25 | #include "mlir/Dialect/GPU/IR/GPUDialect.h" |
26 | #include "mlir/Dialect/GPU/Transforms/Passes.h" |
27 | #include "mlir/Dialect/LLVMIR/NVVMDialect.h" |
28 | #include "mlir/Dialect/Math/IR/Math.h" |
29 | #include "mlir/Dialect/MemRef/IR/MemRef.h" |
30 | #include "mlir/Dialect/NVGPU/IR/NVGPUDialect.h" |
31 | #include "mlir/Transforms/DialectConversion.h" |
32 | #include "mlir/Transforms/GreedyPatternRewriteDriver.h" |
33 | |
34 | #include "../GPUCommon/GPUOpsLowering.h" |
35 | #include "../GPUCommon/IndexIntrinsicsOpLowering.h" |
36 | #include "../GPUCommon/OpToFuncCallLowering.h" |
37 | #include <optional> |
38 | |
39 | namespace mlir { |
40 | #define GEN_PASS_DEF_CONVERTGPUOPSTONVVMOPS |
41 | #include "mlir/Conversion/Passes.h.inc" |
42 | } // namespace mlir |
43 | |
44 | using namespace mlir; |
45 | |
46 | namespace { |
47 | |
48 | /// Convert gpu dialect shfl mode enum to the equivalent nvvm one. |
49 | static NVVM::ShflKind convertShflKind(gpu::ShuffleMode mode) { |
50 | switch (mode) { |
51 | case gpu::ShuffleMode::XOR: |
52 | return NVVM::ShflKind::bfly; |
53 | case gpu::ShuffleMode::UP: |
54 | return NVVM::ShflKind::up; |
55 | case gpu::ShuffleMode::DOWN: |
56 | return NVVM::ShflKind::down; |
57 | case gpu::ShuffleMode::IDX: |
58 | return NVVM::ShflKind::idx; |
59 | } |
60 | llvm_unreachable("unknown shuffle mode"); |
61 | } |
62 | |
63 | static std::optional<NVVM::ReduxKind> |
64 | convertReduxKind(gpu::AllReduceOperation mode) { |
65 | switch (mode) { |
66 | case gpu::AllReduceOperation::ADD: |
67 | return NVVM::ReduxKind::ADD; |
68 | case gpu::AllReduceOperation::MUL: |
69 | return std::nullopt; |
70 | case gpu::AllReduceOperation::MINSI: |
71 | return NVVM::ReduxKind::MIN; |
72 | case gpu::AllReduceOperation::MINUI: |
73 | return std::nullopt; |
74 | case gpu::AllReduceOperation::MINNUMF: |
75 | return NVVM::ReduxKind::MIN; |
76 | case gpu::AllReduceOperation::MAXSI: |
77 | return NVVM::ReduxKind::MAX; |
78 | case gpu::AllReduceOperation::MAXUI: |
79 | return std::nullopt; |
80 | case gpu::AllReduceOperation::MAXNUMF: |
81 | return NVVM::ReduxKind::MAX; |
82 | case gpu::AllReduceOperation::AND: |
83 | return NVVM::ReduxKind::AND; |
84 | case gpu::AllReduceOperation::OR: |
85 | return NVVM::ReduxKind::OR; |
86 | case gpu::AllReduceOperation::XOR: |
87 | return NVVM::ReduxKind::XOR; |
88 | case gpu::AllReduceOperation::MINIMUMF: |
89 | case gpu::AllReduceOperation::MAXIMUMF: |
90 | return std::nullopt; |
91 | } |
92 | return std::nullopt; |
93 | } |
94 | |
95 | /// This pass lowers gpu.subgroup_reduce op into to the nvvm.redux op. The op |
96 | /// must be run by the entire subgroup, otherwise it is undefined behaviour. |
97 | struct GPUSubgroupReduceOpLowering |
98 | : public ConvertOpToLLVMPattern<gpu::SubgroupReduceOp> { |
99 | using ConvertOpToLLVMPattern<gpu::SubgroupReduceOp>::ConvertOpToLLVMPattern; |
100 | LogicalResult |
101 | |
102 | matchAndRewrite(gpu::SubgroupReduceOp op, OpAdaptor adaptor, |
103 | ConversionPatternRewriter &rewriter) const override { |
104 | if (op.getClusterSize()) |
105 | return rewriter.notifyMatchFailure( |
106 | op, "lowering for clustered reduce not implemented"); |
107 | |
108 | if (!op.getUniform()) |
109 | return rewriter.notifyMatchFailure( |
110 | op, "cannot be lowered to redux as the op must be run " |
111 | "uniformly (entire subgroup)."); |
112 | if (!op.getValue().getType().isInteger(32)) |
113 | return rewriter.notifyMatchFailure(op, "unsupported data type"); |
114 | |
115 | std::optional<NVVM::ReduxKind> mode = convertReduxKind(op.getOp()); |
116 | if (!mode.has_value()) |
117 | return rewriter.notifyMatchFailure( |
118 | op, "unsupported reduction mode for redux"); |
119 | |
120 | Location loc = op->getLoc(); |
121 | auto int32Type = IntegerType::get(rewriter.getContext(), 32); |
122 | Value offset = rewriter.create<LLVM::ConstantOp>(loc, int32Type, -1); |
123 | |
124 | auto reduxOp = rewriter.create<NVVM::ReduxOp>(loc, int32Type, op.getValue(), |
125 | mode.value(), offset); |
126 | |
127 | rewriter.replaceOp(op, reduxOp->getResult(0)); |
128 | return success(); |
129 | } |
130 | }; |
131 | |
132 | struct GPUShuffleOpLowering : public ConvertOpToLLVMPattern<gpu::ShuffleOp> { |
133 | using ConvertOpToLLVMPattern<gpu::ShuffleOp>::ConvertOpToLLVMPattern; |
134 | |
135 | /// Lowers a shuffle to the corresponding NVVM op. |
136 | /// |
137 | /// Convert the `width` argument into an activeMask (a bitmask which specifies |
138 | /// which threads participate in the shuffle) and a maskAndClamp (specifying |
139 | /// the highest lane which participates in the shuffle). |
140 | /// |
141 | /// %one = llvm.constant(1 : i32) : i32 |
142 | /// %minus_one = llvm.constant(-1 : i32) : i32 |
143 | /// %thirty_two = llvm.constant(32 : i32) : i32 |
144 | /// %num_lanes = llvm.sub %thirty_two, %width : i32 |
145 | /// %active_mask = llvm.lshr %minus_one, %num_lanes : i32 |
146 | /// %mask_and_clamp = llvm.sub %width, %one : i32 |
147 | /// %shfl = nvvm.shfl.sync.bfly %active_mask, %value, %offset, |
148 | /// %mask_and_clamp : !llvm<"{ float, i1 }"> |
149 | /// %shfl_value = llvm.extractvalue %shfl[0] : |
150 | /// !llvm<"{ float, i1 }"> |
151 | /// %shfl_pred = llvm.extractvalue %shfl[1] : |
152 | /// !llvm<"{ float, i1 }"> |
153 | LogicalResult |
154 | matchAndRewrite(gpu::ShuffleOp op, OpAdaptor adaptor, |
155 | ConversionPatternRewriter &rewriter) const override { |
156 | Location loc = op->getLoc(); |
157 | |
158 | auto valueTy = adaptor.getValue().getType(); |
159 | auto int32Type = IntegerType::get(rewriter.getContext(), 32); |
160 | auto predTy = IntegerType::get(rewriter.getContext(), 1); |
161 | |
162 | Value one = rewriter.create<LLVM::ConstantOp>(loc, int32Type, 1); |
163 | Value minusOne = rewriter.create<LLVM::ConstantOp>(loc, int32Type, -1); |
164 | Value thirtyTwo = rewriter.create<LLVM::ConstantOp>(loc, int32Type, 32); |
165 | Value numLeadInactiveLane = rewriter.create<LLVM::SubOp>( |
166 | loc, int32Type, thirtyTwo, adaptor.getWidth()); |
167 | // Bit mask of active lanes: `(-1) >> (32 - activeWidth)`. |
168 | Value activeMask = rewriter.create<LLVM::LShrOp>(loc, int32Type, minusOne, |
169 | numLeadInactiveLane); |
170 | Value maskAndClamp; |
171 | if (op.getMode() == gpu::ShuffleMode::UP) { |
172 | // Clamp lane: `32 - activeWidth` |
173 | maskAndClamp = numLeadInactiveLane; |
174 | } else { |
175 | // Clamp lane: `activeWidth - 1` |
176 | maskAndClamp = |
177 | rewriter.create<LLVM::SubOp>(loc, int32Type, adaptor.getWidth(), one); |
178 | } |
179 | |
180 | bool predIsUsed = !op->getResult(1).use_empty(); |
181 | UnitAttr returnValueAndIsValidAttr = nullptr; |
182 | Type resultTy = valueTy; |
183 | if (predIsUsed) { |
184 | returnValueAndIsValidAttr = rewriter.getUnitAttr(); |
185 | resultTy = LLVM::LLVMStructType::getLiteral(rewriter.getContext(), |
186 | {valueTy, predTy}); |
187 | } |
188 | Value shfl = rewriter.create<NVVM::ShflOp>( |
189 | loc, resultTy, activeMask, adaptor.getValue(), adaptor.getOffset(), |
190 | maskAndClamp, convertShflKind(op.getMode()), returnValueAndIsValidAttr); |
191 | if (predIsUsed) { |
192 | Value shflValue = rewriter.create<LLVM::ExtractValueOp>(loc, shfl, 0); |
193 | Value isActiveSrcLane = |
194 | rewriter.create<LLVM::ExtractValueOp>(loc, shfl, 1); |
195 | rewriter.replaceOp(op, {shflValue, isActiveSrcLane}); |
196 | } else { |
197 | rewriter.replaceOp(op, {shfl, nullptr}); |
198 | } |
199 | return success(); |
200 | } |
201 | }; |
202 | |
203 | struct GPULaneIdOpToNVVM : ConvertOpToLLVMPattern<gpu::LaneIdOp> { |
204 | using ConvertOpToLLVMPattern<gpu::LaneIdOp>::ConvertOpToLLVMPattern; |
205 | |
206 | LogicalResult |
207 | matchAndRewrite(gpu::LaneIdOp op, gpu::LaneIdOp::Adaptor adaptor, |
208 | ConversionPatternRewriter &rewriter) const override { |
209 | auto loc = op->getLoc(); |
210 | MLIRContext *context = rewriter.getContext(); |
211 | LLVM::ConstantRangeAttr bounds = nullptr; |
212 | if (std::optional<APInt> upperBound = op.getUpperBound()) |
213 | bounds = rewriter.getAttr<LLVM::ConstantRangeAttr>( |
214 | /*bitWidth=*/32, /*lower=*/0, upperBound->getZExtValue()); |
215 | else |
216 | bounds = rewriter.getAttr<LLVM::ConstantRangeAttr>( |
217 | /*bitWidth=*/32, /*lower=*/0, /*upper=*/kWarpSize); |
218 | Value newOp = |
219 | rewriter.create<NVVM::LaneIdOp>(loc, rewriter.getI32Type(), bounds); |
220 | // Truncate or extend the result depending on the index bitwidth specified |
221 | // by the LLVMTypeConverter options. |
222 | const unsigned indexBitwidth = getTypeConverter()->getIndexTypeBitwidth(); |
223 | if (indexBitwidth > 32) { |
224 | newOp = rewriter.create<LLVM::SExtOp>( |
225 | loc, IntegerType::get(context, indexBitwidth), newOp); |
226 | } else if (indexBitwidth < 32) { |
227 | newOp = rewriter.create<LLVM::TruncOp>( |
228 | loc, IntegerType::get(context, indexBitwidth), newOp); |
229 | } |
230 | rewriter.replaceOp(op, {newOp}); |
231 | return success(); |
232 | } |
233 | }; |
234 | |
235 | /// Lowering of cf.assert into a conditional __assertfail. |
236 | struct AssertOpToAssertfailLowering |
237 | : public ConvertOpToLLVMPattern<cf::AssertOp> { |
238 | using ConvertOpToLLVMPattern<cf::AssertOp>::ConvertOpToLLVMPattern; |
239 | |
240 | LogicalResult |
241 | matchAndRewrite(cf::AssertOp assertOp, cf::AssertOpAdaptor adaptor, |
242 | ConversionPatternRewriter &rewriter) const override { |
243 | MLIRContext *ctx = rewriter.getContext(); |
244 | Location loc = assertOp.getLoc(); |
245 | Type i8Type = typeConverter->convertType(rewriter.getIntegerType(8)); |
246 | Type i32Type = typeConverter->convertType(rewriter.getIntegerType(32)); |
247 | Type i64Type = typeConverter->convertType(rewriter.getIntegerType(64)); |
248 | Type ptrType = LLVM::LLVMPointerType::get(ctx); |
249 | Type voidType = LLVM::LLVMVoidType::get(ctx); |
250 | |
251 | // Find or create __assertfail function declaration. |
252 | auto moduleOp = assertOp->getParentOfType<gpu::GPUModuleOp>(); |
253 | auto assertfailType = LLVM::LLVMFunctionType::get( |
254 | voidType, {ptrType, ptrType, i32Type, ptrType, i64Type}); |
255 | LLVM::LLVMFuncOp assertfailDecl = getOrDefineFunction( |
256 | moduleOp, loc, rewriter, "__assertfail", assertfailType); |
257 | assertfailDecl.setPassthroughAttr( |
258 | ArrayAttr::get(ctx, StringAttr::get(ctx, "noreturn"))); |
259 | |
260 | // Split blocks and insert conditional branch. |
261 | // ^before: |
262 | // ... |
263 | // cf.cond_br %condition, ^after, ^assert |
264 | // ^assert: |
265 | // cf.assert |
266 | // cf.br ^after |
267 | // ^after: |
268 | // ... |
269 | Block *beforeBlock = assertOp->getBlock(); |
270 | Block *assertBlock = |
271 | rewriter.splitBlock(block: beforeBlock, before: assertOp->getIterator()); |
272 | Block *afterBlock = |
273 | rewriter.splitBlock(block: assertBlock, before: ++assertOp->getIterator()); |
274 | rewriter.setInsertionPointToEnd(beforeBlock); |
275 | rewriter.create<cf::CondBranchOp>(loc, adaptor.getArg(), afterBlock, |
276 | assertBlock); |
277 | rewriter.setInsertionPointToEnd(assertBlock); |
278 | rewriter.create<cf::BranchOp>(loc, afterBlock); |
279 | |
280 | // Continue cf.assert lowering. |
281 | rewriter.setInsertionPoint(assertOp); |
282 | |
283 | // Populate file name, file number and function name from the location of |
284 | // the AssertOp. |
285 | StringRef fileName = "(unknown)"; |
286 | StringRef funcName = "(unknown)"; |
287 | int32_t fileLine = 0; |
288 | while (auto callSiteLoc = dyn_cast<CallSiteLoc>(loc)) |
289 | loc = callSiteLoc.getCallee(); |
290 | if (auto fileLineColLoc = dyn_cast<FileLineColRange>(loc)) { |
291 | fileName = fileLineColLoc.getFilename().strref(); |
292 | fileLine = fileLineColLoc.getStartLine(); |
293 | } else if (auto nameLoc = dyn_cast<NameLoc>(loc)) { |
294 | funcName = nameLoc.getName().strref(); |
295 | if (auto fileLineColLoc = |
296 | dyn_cast<FileLineColRange>(nameLoc.getChildLoc())) { |
297 | fileName = fileLineColLoc.getFilename().strref(); |
298 | fileLine = fileLineColLoc.getStartLine(); |
299 | } |
300 | } |
301 | |
302 | // Create constants. |
303 | auto getGlobal = [&](LLVM::GlobalOp global) { |
304 | // Get a pointer to the format string's first element. |
305 | Value globalPtr = rewriter.create<LLVM::AddressOfOp>( |
306 | loc, LLVM::LLVMPointerType::get(ctx, global.getAddrSpace()), |
307 | global.getSymNameAttr()); |
308 | Value start = |
309 | rewriter.create<LLVM::GEPOp>(loc, ptrType, global.getGlobalType(), |
310 | globalPtr, ArrayRef<LLVM::GEPArg>{0, 0}); |
311 | return start; |
312 | }; |
313 | Value assertMessage = getGlobal(getOrCreateStringConstant( |
314 | rewriter, loc, moduleOp, i8Type, "assert_message_", assertOp.getMsg())); |
315 | Value assertFile = getGlobal(getOrCreateStringConstant( |
316 | rewriter, loc, moduleOp, i8Type, "assert_file_", fileName)); |
317 | Value assertFunc = getGlobal(getOrCreateStringConstant( |
318 | rewriter, loc, moduleOp, i8Type, "assert_func_", funcName)); |
319 | Value assertLine = |
320 | rewriter.create<LLVM::ConstantOp>(loc, i32Type, fileLine); |
321 | Value c1 = rewriter.create<LLVM::ConstantOp>(loc, i64Type, 1); |
322 | |
323 | // Insert function call to __assertfail. |
324 | SmallVector<Value> arguments{assertMessage, assertFile, assertLine, |
325 | assertFunc, c1}; |
326 | rewriter.replaceOpWithNewOp<LLVM::CallOp>(assertOp, assertfailDecl, |
327 | arguments); |
328 | return success(); |
329 | } |
330 | }; |
331 | |
332 | /// Import the GPU Ops to NVVM Patterns. |
333 | #include "GPUToNVVM.cpp.inc" |
334 | |
335 | /// A pass that replaces all occurrences of GPU device operations with their |
336 | /// corresponding NVVM equivalent. |
337 | /// |
338 | /// This pass only handles device code and is not meant to be run on GPU host |
339 | /// code. |
340 | struct LowerGpuOpsToNVVMOpsPass final |
341 | : public impl::ConvertGpuOpsToNVVMOpsBase<LowerGpuOpsToNVVMOpsPass> { |
342 | using Base::Base; |
343 | |
344 | void getDependentDialects(DialectRegistry ®istry) const override { |
345 | Base::getDependentDialects(registry); |
346 | registerConvertToLLVMDependentDialectLoading(registry); |
347 | } |
348 | |
349 | void runOnOperation() override { |
350 | gpu::GPUModuleOp m = getOperation(); |
351 | |
352 | // Request C wrapper emission. |
353 | for (auto func : m.getOps<func::FuncOp>()) { |
354 | func->setAttr(LLVM::LLVMDialect::getEmitCWrapperAttrName(), |
355 | UnitAttr::get(&getContext())); |
356 | } |
357 | |
358 | // Customize the bitwidth used for the device side index computations. |
359 | LowerToLLVMOptions options( |
360 | m.getContext(), |
361 | DataLayout(cast<DataLayoutOpInterface>(m.getOperation()))); |
362 | if (indexBitwidth != kDeriveIndexBitwidthFromDataLayout) |
363 | options.overrideIndexBitwidth(indexBitwidth); |
364 | options.useBarePtrCallConv = useBarePtrCallConv; |
365 | |
366 | // Apply in-dialect lowering. In-dialect lowering will replace |
367 | // ops which need to be lowered further, which is not supported by a |
368 | // single conversion pass. |
369 | { |
370 | RewritePatternSet patterns(m.getContext()); |
371 | populateGpuRewritePatterns(patterns); |
372 | if (failed(applyPatternsGreedily(m, std::move(patterns)))) |
373 | return signalPassFailure(); |
374 | } |
375 | |
376 | LLVMTypeConverter converter(m.getContext(), options); |
377 | configureGpuToNVVMTypeConverter(converter); |
378 | RewritePatternSet llvmPatterns(m.getContext()); |
379 | LLVMConversionTarget target(getContext()); |
380 | |
381 | // Set higher benefit, so patterns will run before generic LLVM lowering. |
382 | populateGpuToNVVMConversionPatterns(converter, patterns&: llvmPatterns, |
383 | /*benefit=*/10); |
384 | |
385 | llvm::SmallDenseSet<StringRef> allowedDialectsSet(allowedDialects.begin(), |
386 | allowedDialects.end()); |
387 | for (Dialect *dialect : getContext().getLoadedDialects()) { |
388 | // Skip math patterns as nvvm needs custom math lowering. |
389 | if (isa<math::MathDialect>(dialect)) |
390 | continue; |
391 | |
392 | bool allowed = allowedDialectsSet.contains(dialect->getNamespace()); |
393 | // Empty `allowedDialectsSet` means all dialects are allowed. |
394 | if (!allowedDialectsSet.empty() && !allowed) |
395 | continue; |
396 | |
397 | auto iface = dyn_cast<ConvertToLLVMPatternInterface>(dialect); |
398 | if (!iface) { |
399 | // Error out if dialect was explicily specified but doesn't implement |
400 | // conversion interface. |
401 | if (allowed) { |
402 | m.emitError() |
403 | << "dialect does not implement ConvertToLLVMPatternInterface: " |
404 | << dialect->getNamespace(); |
405 | return signalPassFailure(); |
406 | } |
407 | continue; |
408 | } |
409 | |
410 | iface->populateConvertToLLVMConversionPatterns(target, converter, |
411 | llvmPatterns); |
412 | } |
413 | |
414 | populateGpuWMMAToNVVMConversionPatterns(converter, patterns&: llvmPatterns); |
415 | if (this->hasRedux) |
416 | populateGpuSubgroupReduceOpLoweringPattern(converter, patterns&: llvmPatterns); |
417 | configureGpuToNVVMConversionLegality(target); |
418 | if (failed(applyPartialConversion(m, target, std::move(llvmPatterns)))) |
419 | signalPassFailure(); |
420 | } |
421 | }; |
422 | |
423 | } // namespace |
424 | |
425 | void mlir::configureGpuToNVVMConversionLegality(ConversionTarget &target) { |
426 | target.addIllegalOp<func::FuncOp>(); |
427 | target.addIllegalOp<cf::AssertOp>(); |
428 | target.addLegalDialect<::mlir::LLVM::LLVMDialect>(); |
429 | target.addLegalDialect<::mlir::NVVM::NVVMDialect>(); |
430 | target.addIllegalDialect<gpu::GPUDialect>(); |
431 | target.addIllegalOp<LLVM::CopySignOp, LLVM::CosOp, LLVM::ExpOp, LLVM::Exp2Op, |
432 | LLVM::FAbsOp, LLVM::FCeilOp, LLVM::FFloorOp, LLVM::FMAOp, |
433 | LLVM::FRemOp, LLVM::LogOp, LLVM::Log10Op, LLVM::Log2Op, |
434 | LLVM::PowOp, LLVM::RoundEvenOp, LLVM::RoundOp, |
435 | LLVM::SinOp, LLVM::SqrtOp>(); |
436 | |
437 | // TODO: Remove once we support replacing non-root ops. |
438 | target.addLegalOp<gpu::YieldOp, gpu::GPUModuleOp>(); |
439 | } |
440 | |
441 | void mlir::configureGpuToNVVMTypeConverter(LLVMTypeConverter &converter) { |
442 | // NVVM uses alloca in the default address space to represent private |
443 | // memory allocations, so drop private annotations. NVVM uses address |
444 | // space 3 for shared memory. NVVM uses the default address space to |
445 | // represent global memory. |
446 | populateGpuMemorySpaceAttributeConversions( |
447 | typeConverter&: converter, mapping: [](gpu::AddressSpace space) -> unsigned { |
448 | switch (space) { |
449 | case gpu::AddressSpace::Global: |
450 | return static_cast<unsigned>( |
451 | NVVM::NVVMMemorySpace::kGlobalMemorySpace); |
452 | case gpu::AddressSpace::Workgroup: |
453 | return static_cast<unsigned>( |
454 | NVVM::NVVMMemorySpace::kSharedMemorySpace); |
455 | case gpu::AddressSpace::Private: |
456 | return 0; |
457 | } |
458 | llvm_unreachable("unknown address space enum value"); |
459 | return 0; |
460 | }); |
461 | // Lowering for MMAMatrixType. |
462 | converter.addConversion(callback: [&](gpu::MMAMatrixType type) -> Type { |
463 | return convertMMAToLLVMType(type); |
464 | }); |
465 | } |
466 | |
467 | template <typename OpTy> |
468 | static void populateOpPatterns(const LLVMTypeConverter &converter, |
469 | RewritePatternSet &patterns, |
470 | PatternBenefit benefit, StringRef f32Func, |
471 | StringRef f64Func, StringRef f32ApproxFunc = "", |
472 | StringRef f16Func = "") { |
473 | patterns.add<ScalarizeVectorOpLowering<OpTy>>(converter, benefit); |
474 | patterns.add<OpToFuncCallLowering<OpTy>>(converter, f32Func, f64Func, |
475 | f32ApproxFunc, f16Func, |
476 | /*i32Func=*/"", benefit); |
477 | } |
478 | |
479 | template <typename OpTy> |
480 | static void populateIntOpPatterns(const LLVMTypeConverter &converter, |
481 | RewritePatternSet &patterns, |
482 | PatternBenefit benefit, StringRef i32Func) { |
483 | patterns.add<ScalarizeVectorOpLowering<OpTy>>(converter, benefit); |
484 | patterns.add<OpToFuncCallLowering<OpTy>>(converter, "", "", "", "", i32Func, |
485 | benefit); |
486 | } |
487 | |
488 | template <typename OpTy> |
489 | static void populateFloatIntOpPatterns(const LLVMTypeConverter &converter, |
490 | RewritePatternSet &patterns, |
491 | PatternBenefit benefit, |
492 | StringRef f32Func, StringRef f64Func) { |
493 | patterns.add<ScalarizeVectorOpLowering<OpTy>>(converter, benefit); |
494 | patterns.add<OpToFuncCallLowering<OpTy>>(converter, f32Func, f64Func, "", "", |
495 | /*i32Func=*/"", benefit); |
496 | } |
497 | |
498 | void mlir::populateGpuSubgroupReduceOpLoweringPattern( |
499 | const LLVMTypeConverter &converter, RewritePatternSet &patterns, |
500 | PatternBenefit benefit) { |
501 | patterns.add<GPUSubgroupReduceOpLowering>(arg: converter, args&: benefit); |
502 | } |
503 | |
504 | void mlir::populateLibDeviceConversionPatterns( |
505 | const LLVMTypeConverter &converter, RewritePatternSet &patterns, |
506 | PatternBenefit benefit) { |
507 | populateOpPatterns<arith::RemFOp>(converter, patterns, benefit, "__nv_fmodf", |
508 | "__nv_fmod"); |
509 | populateOpPatterns<arith::MaxNumFOp>(converter, patterns, benefit, |
510 | "__nv_fmaxf", "__nv_fmax"); |
511 | populateOpPatterns<arith::MinNumFOp>(converter, patterns, benefit, |
512 | "__nv_fminf", "__nv_fmin"); |
513 | |
514 | populateIntOpPatterns<math::AbsIOp>(converter, patterns, benefit, "__nv_abs"); |
515 | populateOpPatterns<math::AbsFOp>(converter, patterns, benefit, "__nv_fabsf", |
516 | "__nv_fabs"); |
517 | populateOpPatterns<math::AcosOp>(converter, patterns, benefit, "__nv_acosf", |
518 | "__nv_acos"); |
519 | populateOpPatterns<math::AcoshOp>(converter, patterns, benefit, "__nv_acoshf", |
520 | "__nv_acosh"); |
521 | populateOpPatterns<math::AsinOp>(converter, patterns, benefit, "__nv_asinf", |
522 | "__nv_asin"); |
523 | populateOpPatterns<math::AsinhOp>(converter, patterns, benefit, "__nv_asinhf", |
524 | "__nv_asinh"); |
525 | populateOpPatterns<math::AtanOp>(converter, patterns, benefit, "__nv_atanf", |
526 | "__nv_atan"); |
527 | populateOpPatterns<math::Atan2Op>(converter, patterns, benefit, "__nv_atan2f", |
528 | "__nv_atan2"); |
529 | populateOpPatterns<math::AtanhOp>(converter, patterns, benefit, "__nv_atanhf", |
530 | "__nv_atanh"); |
531 | populateOpPatterns<math::CbrtOp>(converter, patterns, benefit, "__nv_cbrtf", |
532 | "__nv_cbrt"); |
533 | populateOpPatterns<math::CeilOp>(converter, patterns, benefit, "__nv_ceilf", |
534 | "__nv_ceil"); |
535 | populateOpPatterns<math::CopySignOp>(converter, patterns, benefit, |
536 | "__nv_copysignf", "__nv_copysign"); |
537 | populateOpPatterns<math::CosOp>(converter, patterns, benefit, "__nv_cosf", |
538 | "__nv_cos", "__nv_fast_cosf"); |
539 | populateOpPatterns<math::CoshOp>(converter, patterns, benefit, "__nv_coshf", |
540 | "__nv_cosh"); |
541 | populateOpPatterns<math::ErfOp>(converter, patterns, benefit, "__nv_erff", |
542 | "__nv_erf"); |
543 | populateOpPatterns<math::ErfcOp>(converter, patterns, benefit, "__nv_erfcf", |
544 | "__nv_erfc"); |
545 | populateOpPatterns<math::ExpOp>(converter, patterns, benefit, "__nv_expf", |
546 | "__nv_exp", "__nv_fast_expf"); |
547 | populateOpPatterns<math::Exp2Op>(converter, patterns, benefit, "__nv_exp2f", |
548 | "__nv_exp2"); |
549 | populateOpPatterns<math::ExpM1Op>(converter, patterns, benefit, "__nv_expm1f", |
550 | "__nv_expm1"); |
551 | populateOpPatterns<math::FloorOp>(converter, patterns, benefit, "__nv_floorf", |
552 | "__nv_floor"); |
553 | populateOpPatterns<math::FmaOp>(converter, patterns, benefit, "__nv_fmaf", |
554 | "__nv_fma"); |
555 | // Note: libdevice uses a different name for 32-bit finite checking |
556 | populateOpPatterns<math::IsFiniteOp>(converter, patterns, benefit, |
557 | "__nv_finitef", "__nv_isfinited"); |
558 | populateOpPatterns<math::IsInfOp>(converter, patterns, benefit, "__nv_isinff", |
559 | "__nv_isinfd"); |
560 | populateOpPatterns<math::IsNaNOp>(converter, patterns, benefit, "__nv_isnanf", |
561 | "__nv_isnand"); |
562 | populateOpPatterns<math::LogOp>(converter, patterns, benefit, "__nv_logf", |
563 | "__nv_log", "__nv_fast_logf"); |
564 | populateOpPatterns<math::Log10Op>(converter, patterns, benefit, "__nv_log10f", |
565 | "__nv_log10", "__nv_fast_log10f"); |
566 | populateOpPatterns<math::Log1pOp>(converter, patterns, benefit, "__nv_log1pf", |
567 | "__nv_log1p"); |
568 | populateOpPatterns<math::Log2Op>(converter, patterns, benefit, "__nv_log2f", |
569 | "__nv_log2", "__nv_fast_log2f"); |
570 | populateOpPatterns<math::PowFOp>(converter, patterns, benefit, "__nv_powf", |
571 | "__nv_pow", "__nv_fast_powf"); |
572 | populateFloatIntOpPatterns<math::FPowIOp>(converter, patterns, benefit, |
573 | "__nv_powif", "__nv_powi"); |
574 | populateOpPatterns<math::RoundOp>(converter, patterns, benefit, "__nv_roundf", |
575 | "__nv_round"); |
576 | populateOpPatterns<math::RoundEvenOp>(converter, patterns, benefit, |
577 | "__nv_rintf", "__nv_rint"); |
578 | populateOpPatterns<math::RsqrtOp>(converter, patterns, benefit, "__nv_rsqrtf", |
579 | "__nv_rsqrt"); |
580 | populateOpPatterns<math::SinOp>(converter, patterns, benefit, "__nv_sinf", |
581 | "__nv_sin", "__nv_fast_sinf"); |
582 | populateOpPatterns<math::SinhOp>(converter, patterns, benefit, "__nv_sinhf", |
583 | "__nv_sinh"); |
584 | populateOpPatterns<math::SqrtOp>(converter, patterns, benefit, "__nv_sqrtf", |
585 | "__nv_sqrt"); |
586 | populateOpPatterns<math::TanOp>(converter, patterns, benefit, "__nv_tanf", |
587 | "__nv_tan", "__nv_fast_tanf"); |
588 | populateOpPatterns<math::TanhOp>(converter, patterns, benefit, "__nv_tanhf", |
589 | "__nv_tanh"); |
590 | } |
591 | |
592 | void mlir::populateGpuToNVVMConversionPatterns( |
593 | const LLVMTypeConverter &converter, RewritePatternSet &patterns, |
594 | PatternBenefit benefit) { |
595 | using gpu::index_lowering::IndexKind; |
596 | using gpu::index_lowering::IntrType; |
597 | |
598 | // TODO: Pass benefit to generated patterns. |
599 | populateWithGenerated(patterns); |
600 | |
601 | patterns.add<GPUPrintfOpToVPrintfLowering, AssertOpToAssertfailLowering>( |
602 | arg: converter, args&: benefit); |
603 | patterns.add< |
604 | gpu::index_lowering::OpLowering<gpu::ThreadIdOp, NVVM::ThreadIdXOp, |
605 | NVVM::ThreadIdYOp, NVVM::ThreadIdZOp>>( |
606 | converter, IndexKind::Block, IntrType::Id, benefit); |
607 | patterns.add< |
608 | gpu::index_lowering::OpLowering<gpu::BlockDimOp, NVVM::BlockDimXOp, |
609 | NVVM::BlockDimYOp, NVVM::BlockDimZOp>>( |
610 | converter, IndexKind::Block, IntrType::Dim, benefit); |
611 | patterns.add< |
612 | gpu::index_lowering::OpLowering<gpu::ClusterIdOp, NVVM::ClusterIdXOp, |
613 | NVVM::ClusterIdYOp, NVVM::ClusterIdZOp>>( |
614 | converter, IndexKind::Other, IntrType::Id, benefit); |
615 | patterns.add<gpu::index_lowering::OpLowering< |
616 | gpu::ClusterDimOp, NVVM::ClusterDimXOp, NVVM::ClusterDimYOp, |
617 | NVVM::ClusterDimZOp>>(converter, IndexKind::Other, IntrType::Dim, |
618 | benefit); |
619 | patterns.add<gpu::index_lowering::OpLowering< |
620 | gpu::ClusterBlockIdOp, NVVM::BlockInClusterIdXOp, |
621 | NVVM::BlockInClusterIdYOp, NVVM::BlockInClusterIdZOp>>( |
622 | converter, IndexKind::Other, IntrType::Id, benefit); |
623 | patterns.add<gpu::index_lowering::OpLowering< |
624 | gpu::ClusterDimBlocksOp, NVVM::ClusterDimBlocksXOp, |
625 | NVVM::ClusterDimBlocksYOp, NVVM::ClusterDimBlocksZOp>>( |
626 | converter, IndexKind::Other, IntrType::Dim, benefit); |
627 | patterns.add<gpu::index_lowering::OpLowering< |
628 | gpu::BlockIdOp, NVVM::BlockIdXOp, NVVM::BlockIdYOp, NVVM::BlockIdZOp>>( |
629 | converter, IndexKind::Grid, IntrType::Id, benefit); |
630 | patterns.add<gpu::index_lowering::OpLowering< |
631 | gpu::GridDimOp, NVVM::GridDimXOp, NVVM::GridDimYOp, NVVM::GridDimZOp>>( |
632 | converter, IndexKind::Grid, IntrType::Dim, benefit); |
633 | patterns.add<GPULaneIdOpToNVVM, GPUShuffleOpLowering, GPUReturnOpLowering>( |
634 | arg: converter, args&: benefit); |
635 | |
636 | patterns.add<GPUDynamicSharedMemoryOpLowering>( |
637 | arg: converter, args: NVVM::kSharedMemoryAlignmentBit, args&: benefit); |
638 | |
639 | // Explicitly drop memory space when lowering private memory |
640 | // attributions since NVVM models it as `alloca`s in the default |
641 | // memory space and does not support `alloca`s with addrspace(5). |
642 | patterns.add<GPUFuncOpLowering>( |
643 | converter, |
644 | GPUFuncOpLoweringOptions{ |
645 | /*allocaAddrSpace=*/0, |
646 | /*workgroupAddrSpace=*/ |
647 | static_cast<unsigned>(NVVM::NVVMMemorySpace::kSharedMemorySpace), |
648 | StringAttr::get(&converter.getContext(), |
649 | NVVM::NVVMDialect::getKernelFuncAttrName()), |
650 | StringAttr::get(&converter.getContext(), |
651 | NVVM::NVVMDialect::getMaxntidAttrName())}, |
652 | benefit); |
653 | |
654 | populateLibDeviceConversionPatterns(converter, patterns, benefit); |
655 | } |
656 | |
657 | //===----------------------------------------------------------------------===// |
658 | // NVVMTargetAttr convert to LLVM attr interface |
659 | //===----------------------------------------------------------------------===// |
660 | |
661 | namespace { |
662 | struct NVVMTargetConvertToLLVMAttrInterface |
663 | : public ConvertToLLVMAttrInterface::ExternalModel< |
664 | NVVMTargetConvertToLLVMAttrInterface, NVVM::NVVMTargetAttr> { |
665 | /// Configure GPU to NVVM. |
666 | void populateConvertToLLVMConversionPatterns( |
667 | Attribute attr, ConversionTarget &target, |
668 | LLVMTypeConverter &typeConverter, RewritePatternSet &patterns) const; |
669 | }; |
670 | } // namespace |
671 | |
672 | void NVVMTargetConvertToLLVMAttrInterface:: |
673 | populateConvertToLLVMConversionPatterns(Attribute attr, |
674 | ConversionTarget &target, |
675 | LLVMTypeConverter &typeConverter, |
676 | RewritePatternSet &patterns) const { |
677 | configureGpuToNVVMConversionLegality(target); |
678 | configureGpuToNVVMTypeConverter(converter&: typeConverter); |
679 | populateGpuToNVVMConversionPatterns(converter: typeConverter, patterns); |
680 | } |
681 | |
682 | void mlir::NVVM::registerConvertGpuToNVVMInterface(DialectRegistry ®istry) { |
683 | registry.addExtension(extensionFn: +[](MLIRContext *ctx, NVVMDialect *dialect) { |
684 | NVVMTargetAttr::attachInterface<NVVMTargetConvertToLLVMAttrInterface>(*ctx); |
685 | }); |
686 | } |
687 |
Definitions
- convertShflKind
- convertReduxKind
- GPUSubgroupReduceOpLowering
- matchAndRewrite
- GPUShuffleOpLowering
- matchAndRewrite
- GPULaneIdOpToNVVM
- matchAndRewrite
- AssertOpToAssertfailLowering
- matchAndRewrite
- LowerGpuOpsToNVVMOpsPass
- getDependentDialects
- runOnOperation
- configureGpuToNVVMConversionLegality
- configureGpuToNVVMTypeConverter
- populateOpPatterns
- populateIntOpPatterns
- populateFloatIntOpPatterns
- populateGpuSubgroupReduceOpLoweringPattern
- populateLibDeviceConversionPatterns
- populateGpuToNVVMConversionPatterns
- NVVMTargetConvertToLLVMAttrInterface
- populateConvertToLLVMConversionPatterns
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