ConvertLaunchFuncToCudaCalls.cpp 18.1 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424
//===- ConvertLaunchFuncToCudaCalls.cpp - MLIR CUDA lowering passes -------===//
//
// Part of the MLIR 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 a pass to convert gpu.launch_func op into a sequence of
// CUDA runtime calls. As the CUDA runtime does not have a stable published ABI,
// this pass uses a slim runtime layer that builds on top of the public API from
// the CUDA headers.
//
//===----------------------------------------------------------------------===//

#include "mlir/Conversion/GPUToCUDA/GPUToCUDAPass.h"

#include "mlir/Dialect/GPU/GPUDialect.h"
#include "mlir/Dialect/LLVMIR/LLVMDialect.h"
#include "mlir/IR/Attributes.h"
#include "mlir/IR/Builders.h"
#include "mlir/IR/Function.h"
#include "mlir/IR/Module.h"
#include "mlir/IR/StandardTypes.h"
#include "mlir/Pass/Pass.h"

#include "llvm/ADT/STLExtras.h"
#include "llvm/IR/DataLayout.h"
#include "llvm/IR/DerivedTypes.h"
#include "llvm/IR/Module.h"
#include "llvm/IR/Type.h"
#include "llvm/Support/Error.h"
#include "llvm/Support/FormatVariadic.h"

using namespace mlir;

// To avoid name mangling, these are defined in the mini-runtime file.
static constexpr const char *cuModuleLoadName = "mcuModuleLoad";
static constexpr const char *cuModuleGetFunctionName = "mcuModuleGetFunction";
static constexpr const char *cuLaunchKernelName = "mcuLaunchKernel";
static constexpr const char *cuGetStreamHelperName = "mcuGetStreamHelper";
static constexpr const char *cuStreamSynchronizeName = "mcuStreamSynchronize";
static constexpr const char *kMcuMemHostRegister = "mcuMemHostRegister";

static constexpr const char *kCubinAnnotation = "nvvm.cubin";
static constexpr const char *kCubinStorageSuffix = "_cubin_cst";

namespace {

/// A pass to convert gpu.launch_func operations into a sequence of CUDA
/// runtime calls.
///
/// In essence, a gpu.launch_func operations gets compiled into the following
/// sequence of runtime calls:
///
/// * mcuModuleLoad        -- loads the module given the cubin data
/// * mcuModuleGetFunction -- gets a handle to the actual kernel function
/// * mcuGetStreamHelper   -- initializes a new CUDA stream
/// * mcuLaunchKernelName  -- launches the kernel on a stream
/// * mcuStreamSynchronize -- waits for operations on the stream to finish
///
/// Intermediate data structures are allocated on the stack.
class GpuLaunchFuncToCudaCallsPass
    : public ModulePass<GpuLaunchFuncToCudaCallsPass> {
private:
  LLVM::LLVMDialect *getLLVMDialect() { return llvmDialect; }

  llvm::LLVMContext &getLLVMContext() {
    return getLLVMDialect()->getLLVMContext();
  }

  void initializeCachedTypes() {
    const llvm::Module &module = llvmDialect->getLLVMModule();
    llvmVoidType = LLVM::LLVMType::getVoidTy(llvmDialect);
    llvmPointerType = LLVM::LLVMType::getInt8PtrTy(llvmDialect);
    llvmPointerPointerType = llvmPointerType.getPointerTo();
    llvmInt8Type = LLVM::LLVMType::getInt8Ty(llvmDialect);
    llvmInt32Type = LLVM::LLVMType::getInt32Ty(llvmDialect);
    llvmInt64Type = LLVM::LLVMType::getInt64Ty(llvmDialect);
    llvmIntPtrType = LLVM::LLVMType::getIntNTy(
        llvmDialect, module.getDataLayout().getPointerSizeInBits());
  }

  LLVM::LLVMType getVoidType() { return llvmVoidType; }

  LLVM::LLVMType getPointerType() { return llvmPointerType; }

  LLVM::LLVMType getPointerPointerType() { return llvmPointerPointerType; }

  LLVM::LLVMType getInt8Type() { return llvmInt8Type; }

  LLVM::LLVMType getInt32Type() { return llvmInt32Type; }

  LLVM::LLVMType getInt64Type() { return llvmInt64Type; }

  LLVM::LLVMType getIntPtrType() {
    const llvm::Module &module = getLLVMDialect()->getLLVMModule();
    return LLVM::LLVMType::getIntNTy(
        getLLVMDialect(), module.getDataLayout().getPointerSizeInBits());
  }

  LLVM::LLVMType getCUResultType() {
    // This is declared as an enum in CUDA but helpers use i32.
    return getInt32Type();
  }

  // Allocate a void pointer on the stack.
  Value allocatePointer(OpBuilder &builder, Location loc) {
    auto one = builder.create<LLVM::ConstantOp>(loc, getInt32Type(),
                                                builder.getI32IntegerAttr(1));
    return builder.create<LLVM::AllocaOp>(loc, getPointerPointerType(), one,
                                          /*alignment=*/0);
  }

  void declareCudaFunctions(Location loc);
  Value setupParamsArray(gpu::LaunchFuncOp launchOp, OpBuilder &builder);
  Value generateKernelNameConstant(StringRef name, Location loc,
                                   OpBuilder &builder);
  void translateGpuLaunchCalls(mlir::gpu::LaunchFuncOp launchOp);

public:
  // Run the dialect converter on the module.
  void runOnModule() override {
    // Cache the LLVMDialect for the current module.
    llvmDialect = getContext().getRegisteredDialect<LLVM::LLVMDialect>();
    // Cache the used LLVM types.
    initializeCachedTypes();

    getModule().walk([this](mlir::gpu::LaunchFuncOp op) {
      translateGpuLaunchCalls(op);
    });

    // GPU kernel modules are no longer necessary since we have a global
    // constant with the CUBIN data.
    for (auto m : llvm::make_early_inc_range(getModule().getOps<ModuleOp>()))
      if (m.getAttrOfType<UnitAttr>(gpu::GPUDialect::getKernelModuleAttrName()))
        m.erase();
  }

private:
  LLVM::LLVMDialect *llvmDialect;
  LLVM::LLVMType llvmVoidType;
  LLVM::LLVMType llvmPointerType;
  LLVM::LLVMType llvmPointerPointerType;
  LLVM::LLVMType llvmInt8Type;
  LLVM::LLVMType llvmInt32Type;
  LLVM::LLVMType llvmInt64Type;
  LLVM::LLVMType llvmIntPtrType;
};

} // anonymous namespace

// Adds declarations for the needed helper functions from the CUDA wrapper.
// The types in comments give the actual types expected/returned but the API
// uses void pointers. This is fine as they have the same linkage in C.
void GpuLaunchFuncToCudaCallsPass::declareCudaFunctions(Location loc) {
  ModuleOp module = getModule();
  OpBuilder builder(module.getBody()->getTerminator());
  if (!module.lookupSymbol(cuModuleLoadName)) {
    builder.create<LLVM::LLVMFuncOp>(
        loc, cuModuleLoadName,
        LLVM::LLVMType::getFunctionTy(
            getCUResultType(),
            {
                getPointerPointerType(), /* CUmodule *module */
                getPointerType()         /* void *cubin */
            },
            /*isVarArg=*/false));
  }
  if (!module.lookupSymbol(cuModuleGetFunctionName)) {
    // The helper uses void* instead of CUDA's opaque CUmodule and
    // CUfunction.
    builder.create<LLVM::LLVMFuncOp>(
        loc, cuModuleGetFunctionName,
        LLVM::LLVMType::getFunctionTy(
            getCUResultType(),
            {
                getPointerPointerType(), /* void **function */
                getPointerType(),        /* void *module */
                getPointerType()         /* char *name */
            },
            /*isVarArg=*/false));
  }
  if (!module.lookupSymbol(cuLaunchKernelName)) {
    // Other than the CUDA api, the wrappers use uintptr_t to match the
    // LLVM type if MLIR's index type, which the GPU dialect uses.
    // Furthermore, they use void* instead of CUDA's opaque CUfunction and
    // CUstream.
    builder.create<LLVM::LLVMFuncOp>(
        loc, cuLaunchKernelName,
        LLVM::LLVMType::getFunctionTy(
            getCUResultType(),
            {
                getPointerType(),        /* void* f */
                getIntPtrType(),         /* intptr_t gridXDim */
                getIntPtrType(),         /* intptr_t gridyDim */
                getIntPtrType(),         /* intptr_t gridZDim */
                getIntPtrType(),         /* intptr_t blockXDim */
                getIntPtrType(),         /* intptr_t blockYDim */
                getIntPtrType(),         /* intptr_t blockZDim */
                getInt32Type(),          /* unsigned int sharedMemBytes */
                getPointerType(),        /* void *hstream */
                getPointerPointerType(), /* void **kernelParams */
                getPointerPointerType()  /* void **extra */
            },
            /*isVarArg=*/false));
  }
  if (!module.lookupSymbol(cuGetStreamHelperName)) {
    // Helper function to get the current CUDA stream. Uses void* instead of
    // CUDAs opaque CUstream.
    builder.create<LLVM::LLVMFuncOp>(
        loc, cuGetStreamHelperName,
        LLVM::LLVMType::getFunctionTy(getPointerType(), /*isVarArg=*/false));
  }
  if (!module.lookupSymbol(cuStreamSynchronizeName)) {
    builder.create<LLVM::LLVMFuncOp>(
        loc, cuStreamSynchronizeName,
        LLVM::LLVMType::getFunctionTy(getCUResultType(),
                                      getPointerType() /* CUstream stream */,
                                      /*isVarArg=*/false));
  }
  if (!module.lookupSymbol(kMcuMemHostRegister)) {
    builder.create<LLVM::LLVMFuncOp>(
        loc, kMcuMemHostRegister,
        LLVM::LLVMType::getFunctionTy(getVoidType(),
                                      {
                                          getPointerType(), /* void *ptr */
                                          getInt64Type()    /* int64 sizeBytes*/
                                      },
                                      /*isVarArg=*/false));
  }
}

// Generates a parameters array to be used with a CUDA kernel launch call. The
// arguments are extracted from the launchOp.
// The generated code is essentially as follows:
//
// %array = alloca(numparams * sizeof(void *))
// for (i : [0, NumKernelOperands))
//   %array[i] = cast<void*>(KernelOperand[i])
// return %array
Value GpuLaunchFuncToCudaCallsPass::setupParamsArray(gpu::LaunchFuncOp launchOp,
                                                     OpBuilder &builder) {
  auto numKernelOperands = launchOp.getNumKernelOperands();
  Location loc = launchOp.getLoc();
  auto one = builder.create<LLVM::ConstantOp>(loc, getInt32Type(),
                                              builder.getI32IntegerAttr(1));
  // Provision twice as much for the `array` to allow up to one level of
  // indirection for each argument.
  auto arraySize = builder.create<LLVM::ConstantOp>(
      loc, getInt32Type(), builder.getI32IntegerAttr(numKernelOperands));
  auto array = builder.create<LLVM::AllocaOp>(loc, getPointerPointerType(),
                                              arraySize, /*alignment=*/0);
  for (unsigned idx = 0; idx < numKernelOperands; ++idx) {
    auto operand = launchOp.getKernelOperand(idx);
    auto llvmType = operand.getType().cast<LLVM::LLVMType>();
    Value memLocation = builder.create<LLVM::AllocaOp>(
        loc, llvmType.getPointerTo(), one, /*alignment=*/1);
    builder.create<LLVM::StoreOp>(loc, operand, memLocation);
    auto casted =
        builder.create<LLVM::BitcastOp>(loc, getPointerType(), memLocation);

    // Assume all struct arguments come from MemRef. If this assumption does not
    // hold anymore then we `launchOp` to lower from MemRefType and not after
    // LLVMConversion has taken place and the MemRef information is lost.
    // Extra level of indirection in the `array`:
    //   the descriptor pointer is registered via @mcuMemHostRegisterPtr
    if (llvmType.isStructTy()) {
      auto registerFunc =
          getModule().lookupSymbol<LLVM::LLVMFuncOp>(kMcuMemHostRegister);
      auto nullPtr = builder.create<LLVM::NullOp>(loc, llvmType.getPointerTo());
      auto gep = builder.create<LLVM::GEPOp>(loc, llvmType.getPointerTo(),
                                             ArrayRef<Value>{nullPtr, one});
      auto size = builder.create<LLVM::PtrToIntOp>(loc, getInt64Type(), gep);
      builder.create<LLVM::CallOp>(loc, ArrayRef<Type>{},
                                   builder.getSymbolRefAttr(registerFunc),
                                   ArrayRef<Value>{casted, size});
      Value memLocation = builder.create<LLVM::AllocaOp>(
          loc, getPointerPointerType(), one, /*alignment=*/1);
      builder.create<LLVM::StoreOp>(loc, casted, memLocation);
      casted =
          builder.create<LLVM::BitcastOp>(loc, getPointerType(), memLocation);
    }

    auto index = builder.create<LLVM::ConstantOp>(
        loc, getInt32Type(), builder.getI32IntegerAttr(idx));
    auto gep = builder.create<LLVM::GEPOp>(loc, getPointerPointerType(), array,
                                           ArrayRef<Value>{index});
    builder.create<LLVM::StoreOp>(loc, casted, gep);
  }
  return array;
}

// Generates an LLVM IR dialect global that contains the name of the given
// kernel function as a C string, and returns a pointer to its beginning.
// The code is essentially:
//
// llvm.global constant @kernel_name("function_name\00")
// func(...) {
//   %0 = llvm.addressof @kernel_name
//   %1 = llvm.constant (0 : index)
//   %2 = llvm.getelementptr %0[%1, %1] : !llvm<"i8*">
// }
Value GpuLaunchFuncToCudaCallsPass::generateKernelNameConstant(
    StringRef name, Location loc, OpBuilder &builder) {
  // Make sure the trailing zero is included in the constant.
  std::vector<char> kernelName(name.begin(), name.end());
  kernelName.push_back('\0');

  std::string globalName = llvm::formatv("{0}_kernel_name", name);
  return LLVM::createGlobalString(
      loc, builder, globalName, StringRef(kernelName.data(), kernelName.size()),
      LLVM::Linkage::Internal, llvmDialect);
}

// Emits LLVM IR to launch a kernel function. Expects the module that contains
// the compiled kernel function as a cubin in the 'nvvm.cubin' attribute of the
// kernel function in the IR.
// While MLIR has no global constants, also expects a cubin getter function in
// an 'nvvm.cubingetter' attribute. Such function is expected to return a
// pointer to the cubin blob when invoked.
// With these given, the generated code in essence is
//
// %0 = call %cubingetter
// %1 = alloca sizeof(void*)
// call %mcuModuleLoad(%2, %1)
// %2 = alloca sizeof(void*)
// %3 = load %1
// %4 = <see generateKernelNameConstant>
// call %mcuModuleGetFunction(%2, %3, %4)
// %5 = call %mcuGetStreamHelper()
// %6 = load %2
// %7 = <see setupParamsArray>
// call %mcuLaunchKernel(%6, <launchOp operands 0..5>, 0, %5, %7, nullptr)
// call %mcuStreamSynchronize(%5)
void GpuLaunchFuncToCudaCallsPass::translateGpuLaunchCalls(
    mlir::gpu::LaunchFuncOp launchOp) {
  OpBuilder builder(launchOp);
  Location loc = launchOp.getLoc();
  declareCudaFunctions(loc);

  auto zero = builder.create<LLVM::ConstantOp>(loc, getInt32Type(),
                                               builder.getI32IntegerAttr(0));
  // Create an LLVM global with CUBIN extracted from the kernel annotation and
  // obtain a pointer to the first byte in it.
  auto kernelModule =
      getModule().lookupSymbol<ModuleOp>(launchOp.getKernelModuleName());
  assert(kernelModule && "expected a kernel module");

  auto cubinAttr = kernelModule.getAttrOfType<StringAttr>(kCubinAnnotation);
  if (!cubinAttr) {
    kernelModule.emitOpError()
        << "missing " << kCubinAnnotation << " attribute";
    return signalPassFailure();
  }

  assert(kernelModule.getName() && "expected a named module");
  SmallString<128> nameBuffer(*kernelModule.getName());
  nameBuffer.append(kCubinStorageSuffix);
  Value data = LLVM::createGlobalString(
      loc, builder, nameBuffer.str(), cubinAttr.getValue(),
      LLVM::Linkage::Internal, getLLVMDialect());

  // Emit the load module call to load the module data. Error checking is done
  // in the called helper function.
  auto cuModule = allocatePointer(builder, loc);
  auto cuModuleLoad =
      getModule().lookupSymbol<LLVM::LLVMFuncOp>(cuModuleLoadName);
  builder.create<LLVM::CallOp>(loc, ArrayRef<Type>{getCUResultType()},
                               builder.getSymbolRefAttr(cuModuleLoad),
                               ArrayRef<Value>{cuModule, data});
  // Get the function from the module. The name corresponds to the name of
  // the kernel function.
  auto cuOwningModuleRef =
      builder.create<LLVM::LoadOp>(loc, getPointerType(), cuModule);
  auto kernelName = generateKernelNameConstant(launchOp.kernel(), loc, builder);
  auto cuFunction = allocatePointer(builder, loc);
  auto cuModuleGetFunction =
      getModule().lookupSymbol<LLVM::LLVMFuncOp>(cuModuleGetFunctionName);
  builder.create<LLVM::CallOp>(
      loc, ArrayRef<Type>{getCUResultType()},
      builder.getSymbolRefAttr(cuModuleGetFunction),
      ArrayRef<Value>{cuFunction, cuOwningModuleRef, kernelName});
  // Grab the global stream needed for execution.
  auto cuGetStreamHelper =
      getModule().lookupSymbol<LLVM::LLVMFuncOp>(cuGetStreamHelperName);
  auto cuStream = builder.create<LLVM::CallOp>(
      loc, ArrayRef<Type>{getPointerType()},
      builder.getSymbolRefAttr(cuGetStreamHelper), ArrayRef<Value>{});
  // Invoke the function with required arguments.
  auto cuLaunchKernel =
      getModule().lookupSymbol<LLVM::LLVMFuncOp>(cuLaunchKernelName);
  auto cuFunctionRef =
      builder.create<LLVM::LoadOp>(loc, getPointerType(), cuFunction);
  auto paramsArray = setupParamsArray(launchOp, builder);
  auto nullpointer =
      builder.create<LLVM::IntToPtrOp>(loc, getPointerPointerType(), zero);
  builder.create<LLVM::CallOp>(
      loc, ArrayRef<Type>{getCUResultType()},
      builder.getSymbolRefAttr(cuLaunchKernel),
      ArrayRef<Value>{cuFunctionRef, launchOp.getOperand(0),
                      launchOp.getOperand(1), launchOp.getOperand(2),
                      launchOp.getOperand(3), launchOp.getOperand(4),
                      launchOp.getOperand(5), zero, /* sharedMemBytes */
                      cuStream.getResult(0),        /* stream */
                      paramsArray,                  /* kernel params */
                      nullpointer /* extra */});
  // Sync on the stream to make it synchronous.
  auto cuStreamSync =
      getModule().lookupSymbol<LLVM::LLVMFuncOp>(cuStreamSynchronizeName);
  builder.create<LLVM::CallOp>(loc, ArrayRef<Type>{getCUResultType()},
                               builder.getSymbolRefAttr(cuStreamSync),
                               ArrayRef<Value>(cuStream.getResult(0)));
  launchOp.erase();
}

std::unique_ptr<mlir::OpPassBase<mlir::ModuleOp>>
mlir::createConvertGpuLaunchFuncToCudaCallsPass() {
  return std::make_unique<GpuLaunchFuncToCudaCallsPass>();
}

static PassRegistration<GpuLaunchFuncToCudaCallsPass>
    pass("launch-func-to-cuda",
         "Convert all launch_func ops to CUDA runtime calls");