[mlir][NVVM] Adds the NVVM target attribute.

[fmorac]

Summary

For an explanation of these patches see D154153.

Commit message:
This patch adds the NVVM target attribute for serializing GPU modules into
strings containing cubin.

Depends on D154113 and D154100 and D154097

[fmorac]

Update the commit message to include D154100

[fmorac]

Update commit message to include D154097

[fmorac]

Rebasing.

[fmorac]

Updated location of ModuleToObject.h

[mehdi_amini]

mlir/include/mlir/Dialect/GPU/IR/GPUCompilationAttr.td

24

Wondering why is this in the gpu dialect and not a target specific one? (like nvvm)

83

Nit: hasFastMath since it returns a bool. I would think that getFastMath would return a FastMathFlag attribute.

[mehdi_amini]

mlir/lib/Dialect/GPU/Targets/NVPTXTarget.cpp

214

We should have options to stop after emitting LLVMIR and PTX, seems like we have to go to cubin right now?

I would also think that going to PTX can be possible without requiring any dependency on the Cuda toolkit?

[mehdi_amini]

Do we have a way to test this without too much of the other code by the way?

[fmorac]

In D154117#4526902, @mehdi_amini wrote:

Do we have a way to test this without too much of the other code by the way?

Not really? I added some on the final patches were you have all the infra ready. The best test I can think of at this point, is an unit test for this serializer?

mlir/include/mlir/Dialect/GPU/IR/GPUCompilationAttr.td

24

I initially added these attributes (NVPTX & AMDGPU) to nvvm & rocdl, however I decided against that in the final patch because it added GPU dependencies to those dialects (includes & libs) and created more libs instead of a single (GPUTargets).

I'm open to change it.

83

I'll change it.

mlir/lib/Dialect/GPU/Targets/NVPTXTarget.cpp

214

These series of patches intend to be a full replacement of the current pipeline, upon approval we should intermediately deprecate the current pipeline and then remove it after a deprecation period.

The idea is that in future patches we change this behavior and stop at LLVM, but that requires having the LLVM Offload work done.

The benefit of this approach is that those future changes would be invisible to users and at the same time it makes them adopt this new mechanism now, that's why I go straight to cubin.

[mehdi_amini]

mlir/include/mlir/Dialect/GPU/IR/GPUCompilationAttr.td

24

Where will the dependency come from? The GPUTargetAttrInterface?

Maybe we should revisit the way the interface is specified. Worse case we're just one level of indirection away :)

Here if the issue is just the gpu::TargetOptions, maybe it can be declared with the interface definition, which makes it an isolated library?

mlir/lib/Dialect/GPU/Targets/NVPTXTarget.cpp

214

OK, thanks for explaining, can you add a TODO with this info in the code?

[fmorac]

Move the target attribute to NVVM and added it as an external model that it's promised.

[fmorac]

Fix typo in unit test.

[mehdi_amini]

mlir/lib/Target/LLVM/NVVM/Target.cpp

55 ↗

(On Diff #545486)

Do we need to the init in the registration? Can we do the init when the serialization is called instead?

mlir/unittests/Target/LLVM/SerializeNVVMTarget.cpp

33 ↗

(On Diff #545486)

Not clear to me where we need the native target?

46 ↗

(On Diff #545486)

Can we tone this down? There is no reason to link all of MLIR into this unit-test.

[fmorac]

Addressed comments.

[mehdi_amini]

(Waiting on update to use ptxas)

[fmorac]

Swtiched to ptxas, added options for stopping compilation at LLVM IR & PTX, as well as unit tests testing the added functionalty.

[mehdi_amini]

Bring @tra here to get feedback on pros/cons of invoking ptxas through a temp file vs using the library APIs exposed by nvptxcompile.

[fmorac]

In D154117#4554942, @mehdi_amini wrote:

Bring @tra here to get feedback on pros/cons of invoking ptxas through a temp file vs using the library APIs exposed by nvptxcompile.

One immediate benefit is that we don't longer have a dependency on the toolkit to build this. You can detect ptxas by setting the env variable CUDA_ROOT to the location of the toolkit or by adding it to PATH.

mlir/lib/Target/LLVM/NVVM/Target.cpp

55 ↗

(On Diff #545486)

Yes, it's possible I'll change it.

mlir/unittests/Target/LLVM/SerializeNVVMTarget.cpp

33 ↗

(On Diff #545486)

Not needed, removed.

46 ↗

(On Diff #545486)

Yes, I've removed it.

[guraypp]

In D154117#4554966, @fmorac wrote:

In D154117#4554942, @mehdi_amini wrote:

Bring @tra here to get feedback on pros/cons of invoking ptxas through a temp file vs using the library APIs exposed by nvptxcompile.

One immediate benefit is that we don't longer have a dependency on the toolkit to build this. You can detect ptxas by setting the env variable CUDA_ROOT to the location of the toolkit or by adding it to PATH.

I think compiling by ptxas has merits. One can different version of ptxas in case of performance regression.

[guraypp]

mlir/lib/Target/LLVM/NVVM/Target.cpp

290 ↗

(On Diff #546432)

It would be nice to pass parameters to ptxas from MLIR.

325 ↗

(On Diff #546432)

What do you think about passsing -v always to ptxas and print the output (perhaps stdout file) using llvm::errs.
I found -v very useful to see compile-time register usage and local memory.

[guraypp]

mlir/lib/Target/LLVM/NVVM/Target.cpp

286 ↗

(On Diff #546432)

Can we keep the PTX file? After codegen, it is very natural to look at the PTX file, if we keep the file via a flag, I think it would be great.

I implemented the dump-ptx flag to the gpu-to-cubin Pass earlier. I guess we cannot use that flag here.

[fmorac]

mlir/lib/Target/LLVM/NVVM/Target.cpp

286 ↗

(On Diff #546432)

If you pass -debug-only=serialize-to-ptx (I'm changing it to serialize-to-isa) to mlir-opt then the PTX file will be printed to stdout. This mechanism also allows emitting PTX instead of binary, so you have multiple ways of obtaining the PTX.

290 ↗

(On Diff #546432)

You can, the args are passed through the targetOptions variable. Below you'll find that I add them to the PTX invocation.

325 ↗

(On Diff #546432)

We could consider adding a dedicated variable, but as it stands you can pass that variable through the cmdline and use --debug-only=serialize-to-binary to dump that output into stdout.

[mehdi_amini]

I think compiling by ptxas has merits. One can different version of ptxas in case of performance regression.

nvptxcompile provides the same facility I believe, doesn't it?

[guraypp]

In D154117#4558565, @mehdi_amini wrote:

I think compiling by ptxas has merits. One can different version of ptxas in case of performance regression.

nvptxcompile provides the same facility I believe, doesn't it?

Though I haven't personally worked with nvptxcompile, it appears to be bundled with the toolkit. If one could use different toolkit version for PTX compilation, then yes it gives the same facility.

Recently, I used the driver (current MLIR compilation) and ptxas for PTX compilation. I noticed that even if I feed the same PTX code, the driver occasionally generates different SASS with ptxas. Maybe I hit a corner case but it was really hard to find the reason.

I believe it's crucial for us to know the potential disparities between nvptxcompile and ptxas if there is any.

[fmorac]

My 2 cents, as far as I know the nvptxcompiler and ptxas should produce the same code for a given release. However unlike ptxas the only way to change the version of nvptxcompiler is to recompile the NVVMTarget library with a different version.

Adding support for nvptxcompiler is like extra 20 lines of code in this patch, and a couple on CMake, how do we feel about having both?

If nvptxcompiler is detected during build then nvptxcompiler is used, if not, then ptxas is used, and we also give the user the ability to choose on CMake?

[mehdi_amini]

If nvptxcompiler is detected during build then nvptxcompiler is used, if not, then ptxas is used, and we also give the user the ability to choose on CMake?

Adding a CMake option looks good to me, I would pick a default and stick to it (that is fail the cmake configuration with a helpful message).

I don't like "magic" fallback because detection is fragile and it makes the behavior dependent on the environment of the user. It's harder to know what you build, and getting bug reports it makes it also harder to know what's happening.

[fmorac]

Added NVPTX compiler support & removed unnecessary fwd declarations. The CMake variable MLIR_ENABLE_NVPTXCOMPILER controls the usage of the NVPTXCompiler library and is disabled by default, as CMake 3.20 doesn't support CUDA::nvptxcompiler_static to find the library.

[tra]

mlir/lib/Target/LLVM/NVVM/Target.cpp

123 ↗

(On Diff #547733)

A word of caution -- some linux distributions scatter CUDA SDK across the 'standard' linux filsystem paths, so a single getToolkitPath() would not be able to find all the necessary bits, as libdevice and the binaries will be in different places. You may need additional heuristics along the lines of what clang driver does.
https://github.com/llvm/llvm-project/blob/1b74459df8a6d960f7387f0c8379047e42811f58/clang/lib/Driver/ToolChains/Cuda.cpp#L180

[fmorac]

mlir/lib/Target/LLVM/NVVM/Target.cpp

123 ↗

(On Diff #547733)

Thank you, that's good to know. I'll see how to rework it or add docs indicating how to make it work.
As it stands the user could specify the CUDA path to /usr/lib/cuda for libdevice, somewhat similar to --cuda-path.

For ptxas this mechanism searches several places in the following order:

1. Command line option.
2. PATH variable.
3. The toolkit path as specified by a couple of env variables or the one detected by CMake.

So it would work on Debian & Ubuntu, but the mechanism could be over burdening the user.

[fmorac]

Reapplied clang-format.
Adds a couple of syntax tests & fixes a bug not displaying the link option in the attribute.

[mehdi_amini]

Thanks Fabian!

mlir/CMakeLists.txt

122 ↗

(On Diff #548030)

The description isn't super clear, because it conflicts with what "the NVPTX backend" is in LLVM.
What about: "Statically link the nvptxlibrary instead of calling ptxas as a subprocess for compiling PTX to cubin" ?

[fmorac]

Changed the description of the CMake variable MLIR_ENABLE_NVPTXCOMPILER. Applied clang-format again.

[fmorac]

Fixed merge conflicts with D157183.

mlir/include/mlir/Dialect/GPU/IR/GPUCompilationAttr.td

+//===-- GPUTargetAttr.td - GPU compilation attributes ------*- tablegen -*-===//
+//
+// 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 defines the GPU NVPTX target attribute.
+//
+//===----------------------------------------------------------------------===//
+
+#ifndef GPU_COMPILATIONATTR
+#define GPU_COMPILATIONATTR
+
+include "mlir/Dialect/GPU/IR/GPUBase.td"
+include "mlir/Dialect/GPU/IR/CompilationAttrInterfaces.td"
+
+//===----------------------------------------------------------------------===//
+// GPU NVPTX target attribute.
+//===----------------------------------------------------------------------===//
+
+def GPU_NVPTXTargetAttr : GPU_Attr<"NVPTXTarget", "nvptx", [
+    DeclareAttrInterfaceMethods<GPUTargetAttrInterface, [
+      "serializeToObject"
+    ]>
+  ]> {
+  let description = [{
+    NVPTX target attribute for controlling compilation of NVIDIA targets. All
+    parameters decay into default values if not present.
+
+    Examples:
+
+    1. Target with default values.
+    ```
+      gpu.module @mymodule [#gpu.nvptx] attributes {...} {
+        ...
+      }
+    ```
+
+    2. Target with `sm_90` chip and fast math.
+    ```
+      gpu.module @mymodule [#gpu.nvptx<chip = "sm_90", flags = {fast}>] {
+        ...
+      }
+    ```
+  }];
+  let parameters = (ins
+    DefaultValuedParameter<"int", "2", "Optimization level to apply.">:$O,
+    StringRefParameter<"Target triple.", "\"nvptx64-nvidia-cuda\"">:$triple,
+    StringRefParameter<"Target chip.", "\"sm_50\"">:$chip,
+    StringRefParameter<"Target chip features.", "\"+ptx60\"">:$features,
+    OptionalParameter<"DictionaryAttr", "Target specific flags.">:$flags,
+    OptionalParameter<"ArrayAttr", "Files to link to the LLVM module.">:$link
+  );
+  let assemblyFormat = [{
+    (`<` struct($O, $triple, $chip, $features, $flags)^ `>`)?
+  }];
+  let builders = [
+    AttrBuilder<(ins CArg<"int", "2">:$optLevel,
+                     CArg<"StringRef", "\"nvptx64-nvidia-cuda\"">:$triple,
+                     CArg<"StringRef", "\"sm_50\"">:$chip,
+                     CArg<"StringRef", "\"+ptx60\"">:$features,
+                     CArg<"DictionaryAttr", "nullptr">:$targetFlags,
+                     CArg<"ArrayAttr", "nullptr">:$linkFiles), [{
+      return Base::get($_ctxt, optLevel, triple, chip, features, targetFlags, linkFiles);
+    }]>
+  ];
+  let skipDefaultBuilders = 1;
+  let genVerifyDecl = 1;
+  let extraClassDeclaration = [{
+    bool hasFlag(StringRef flag) const;
+    bool getFastMath() const;
+    bool getFtz() const;
+  }];
+  let extraClassDefinition = [{
+    bool $cppClass::hasFlag(StringRef flag) const {
+      if (DictionaryAttr flags = getFlags())
+        return flags.get(flag) != nullptr;
+      return false;
+    }
+    bool $cppClass::getFastMath() const {
+      return hasFlag("fast");
+    }
+    bool $cppClass::getFtz() const {
+      return hasFlag("ftz");
+    }
+  }];
+}
+
+#endif // GPU_COMPILATIONATTR

mlir/include/mlir/Dialect/GPU/IR/GPUOps.td

 //===----------------------------------------------------------------------===//
 
 #ifndef GPU_OPS
 #define GPU_OPS
 
 include "mlir/Dialect/DLTI/DLTIBase.td"
 include "mlir/Dialect/GPU/IR/GPUBase.td"
 include "mlir/Dialect/GPU/IR/CompilationAttrInterfaces.td"
+include "mlir/Dialect/GPU/IR/GPUCompilationAttr.td"
 include "mlir/Dialect/GPU/IR/ParallelLoopMapperAttr.td"
 include "mlir/Dialect/GPU/TransformOps/GPUDeviceMappingAttr.td"
 include "mlir/IR/EnumAttr.td"
 include "mlir/IR/FunctionInterfaces.td"
 include "mlir/IR/SymbolInterfaces.td"
 include "mlir/Interfaces/DataLayoutInterfaces.td"
 include "mlir/Interfaces/InferIntRangeInterface.td"
 include "mlir/Interfaces/InferTypeOpInterface.td"

mlir/lib/Dialect/GPU/CMakeLists.txt

add_mlir_dialect_library(MLIRGPUDialect
   LINK_LIBS PUBLIC
   MLIRArithDialect
   MLIRDLTIDialect
   MLIRInferIntRangeInterface
   MLIRIR
   MLIRMemRefDialect
   MLIRSideEffectInterfaces
   MLIRSupport
+
+  PRIVATE
+  MLIRGPUTargets
+  )
+
+add_mlir_dialect_library(MLIRGPUTargets
+  Targets/NVPTXTarget.cpp
+
+  ADDITIONAL_HEADER_DIRS
+  ${MLIR_MAIN_INCLUDE_DIR}/mlir/Dialect/GPU
+
+  LINK_COMPONENTS
+  Core
+  MC
+  Target
+  ${NVPTX_LIBS}
+
+  LINK_LIBS PUBLIC
+  MLIRIR
+  MLIRExecutionEngineUtils
+  MLIRSupport
+  MLIRTargetLLVMIRExport
+
+  PRIVATE
+  MLIRGPUDialect
   )
 
 add_mlir_dialect_library(MLIRGPUTransforms
   Transforms/AllReduceLowering.cpp
   Transforms/AsyncRegionRewriter.cpp
   Transforms/GlobalIdRewriter.cpp
   Transforms/KernelOutlining.cpp
   Transforms/MemoryPromotion.cpp
if(MLIR_ENABLE_CUDA_RUNNER)
 
   find_library(CUDA_DRIVER_LIBRARY cuda HINTS ${CMAKE_CUDA_IMPLICIT_LINK_DIRECTORIES} REQUIRED)
   target_link_libraries(MLIRGPUTransforms
     PRIVATE
     MLIRNVVMToLLVMIRTranslation
     ${CUDA_DRIVER_LIBRARY}
   )
 
+  # Find the CUDA toolkit.
+  if (NOT DEFINED CUDAToolkit_ROOT)
+    find_package(CUDAToolkit)
+    get_filename_component(CUDAToolkit_ROOT ${CUDAToolkit_BIN_DIR} DIRECTORY ABSOLUTE)
+  endif()
+  message(VERBOSE "MLIR Default CUDA toolkit path: ${CUDAToolkit_ROOT}")
+
+  # Enable the gpu to cubin target.
+  target_compile_definitions(obj.MLIRGPUTargets
+    PRIVATE
+    MLIR_GPU_NVPTX_TARGET_ENABLED=1
+    __DEFAULT_CUDATOOLKIT_PATH__="${CUDAToolkit_ROOT}"
+  )
+  # Enable the gpu to cubin target.
+  target_compile_definitions(obj.MLIRGPUTransforms
+    PRIVATE
+    MLIR_GPU_NVPTX_TARGET_ENABLED=1
+  )
+
+  # Add CUDA headers includes and the libcuda.so library.
+  target_include_directories(obj.MLIRGPUTargets
+    PRIVATE
+    ${CMAKE_CUDA_TOOLKIT_INCLUDE_DIRECTORIES}
+  )
+  target_link_libraries(MLIRGPUTargets
+    PRIVATE
+    ${CUDA_DRIVER_LIBRARY}
+  )
+
 endif()
 
 if(MLIR_ENABLE_ROCM_CONVERSIONS)
   if (NOT ("AMDGPU" IN_LIST LLVM_TARGETS_TO_BUILD))
     message(SEND_ERROR
       "Building mlir with ROCm support requires the AMDGPU backend")
   endif()
 

mlir/lib/Dialect/GPU/Targets/NVPTXTarget.cpp

+//===- NVPTXTarget.cpp - MLIR GPU Dialect NVPTX target attribute ----------===//
+//
+// 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 files implements the NVPTX target attribute.
+//
+//===----------------------------------------------------------------------===//
+
+#include "mlir/Dialect/GPU/IR/GPUDialect.h"
+#include "mlir/Dialect/GPU/Transforms/Passes.h"
+
+using namespace mlir;
+using namespace mlir::gpu;
+
+#ifdef MLIR_GPU_NVPTX_TARGET_ENABLED
+#include "mlir/ExecutionEngine/ModuleToObject.h"
+#include "mlir/Target/LLVMIR/Dialect/GPU/GPUToLLVMIRTranslation.h"
+#include "mlir/Target/LLVMIR/Dialect/LLVMIR/LLVMToLLVMIRTranslation.h"
+#include "mlir/Target/LLVMIR/Dialect/NVVM/NVVMToLLVMIRTranslation.h"
+#include "mlir/Target/LLVMIR/Export.h"
+
+#include "llvm/Support/FileSystem.h"
+#include "llvm/Support/Path.h"
+#include "llvm/Support/TargetSelect.h"
+
+#ifndef __DEFAULT_CUDATOOLKIT_PATH__
+#define __DEFAULT_CUDATOOLKIT_PATH__ ""
+#endif
+
+#define DEBUG_TYPE "serialize-to-object"
+
+#include <cuda.h>
+
+static void emitCudaError(const llvm::Twine &expr, const char *buffer,
+                          CUresult result, Location loc) {
+  const char *error;
+  cuGetErrorString(result, &error);
+  emitError(loc, expr.concat(" failed with error code ")
+                     .concat(llvm::Twine{error})
+                     .concat("[")
+                     .concat(buffer)
+                     .concat("]"));
+}
+
+#define RETURN_ON_CUDA_ERROR(expr)                                             \
+  do {                                                                         \
+    if (auto status = (expr)) {                                                \
+      emitCudaError(#expr, jitErrorBuffer, status, loc);                       \
+      return {};                                                               \
+    }                                                                          \
+  } while (false)
+
+namespace {
+struct InitTarget {
+  InitTarget() {
+    LLVMInitializeNVPTXTarget();
+    LLVMInitializeNVPTXTargetInfo();
+    LLVMInitializeNVPTXTargetMC();
+    LLVMInitializeNVPTXAsmPrinter();
+  }
+};
+
+class SerializeToCubin : public ModuleToObject {
+public:
+  SerializeToCubin(Operation &module, NVPTXTargetAttr target,
+                   TargetOptions targetOptions = {});
+
+  // Init the target.
+  static void init();
+
+  std::optional<SmallVector<std::unique_ptr<llvm::Module>>>
+  loadBitcodeFiles(llvm::LLVMContext &context, llvm::Module &module) override;
+
+  std::optional<SmallVector<char, 0>>
+  moduleToObject(llvm::Module &llvmModule,
+                 llvm::TargetMachine &targetMachine) override;
+
+private:
+  StringRef toolkitPath;
+  SmallVector<std::string> fileList;
+};
+} // namespace
+
+SerializeToCubin::SerializeToCubin(Operation &module, NVPTXTargetAttr target,
+                                   TargetOptions targetOptions)
+    : ModuleToObject(module, target.getTriple(), target.getChip(),
+                     target.getFeatures(), target.getO()),
+      toolkitPath(targetOptions.getToolkitPath()),
+      fileList(targetOptions.getBitcodeFiles()) {
+  if (toolkitPath.empty())
+    toolkitPath = __DEFAULT_CUDATOOLKIT_PATH__;
+
+  if (ArrayAttr files = target.getLink())
+    for (Attribute attr : files.getValue())
+      if (auto file = dyn_cast<StringAttr>(attr))
+        fileList.push_back(file.str());
+}
+
+void SerializeToCubin::init() { static InitTarget target = InitTarget(); }
+
+std::optional<SmallVector<std::unique_ptr<llvm::Module>>>
+SerializeToCubin::loadBitcodeFiles(llvm::LLVMContext &context,
+                                   llvm::Module &module) {
+  // Try loading `libdevice` from a CUDA toolkit installation.
+  StringRef pathRef = toolkitPath;
+  if (pathRef.size()) {
+    SmallVector<char, 256> path;
+    path.insert(path.begin(), pathRef.begin(), pathRef.end());
+    pathRef = StringRef(path.data(), path.size());
+    if (!llvm::sys::fs::is_directory(pathRef)) {
+      getOperation().emitError() << "CUDA path: " << pathRef
+                                 << " does not exist or is not a directory.\n";
+      return std::nullopt;
+    }
+    // TODO remove this hard coded path.
+    llvm::sys::path::append(path, "nvvm", "libdevice", "libdevice.10.bc");
+    pathRef = StringRef(path.data(), path.size());
+    if (!llvm::sys::fs::is_regular_file(pathRef)) {
+      getOperation().emitError() << "LibDevice path: " << pathRef
+                                 << " does not exist or is not a file.\n";
+      return std::nullopt;
+    }
+    fileList.push_back(pathRef.str());
+  }
+
+  SmallVector<std::unique_ptr<llvm::Module>> bcFiles;
+  if (failed(loadBitcodeFilesFromList(context, fileList, bcFiles, true)))
+    return std::nullopt;
+  return bcFiles;
+}
+
+std::optional<SmallVector<char, 0>>
+SerializeToCubin::moduleToObject(llvm::Module &llvmModule,
+                                 llvm::TargetMachine &targetMachine) {
+  std::optional<std::string> serializedISA =
+      translateToISA(llvmModule, targetMachine);
+  if (!serializedISA) {
+    getOperation().emitError() << "Failed translating the module to ISA.";
+    return std::nullopt;
+  }
+
+  LLVM_DEBUG({
+    llvm::dbgs() << "ISA for module: "
+                 << dyn_cast<GPUModuleOp>(&getOperation()).getNameAttr()
+                 << "\n";
+    llvm::dbgs() << *serializedISA << "\n";
+    llvm::dbgs().flush();
+  });
+
+  auto loc = getOperation().getLoc();
+  char jitErrorBuffer[4096] = {0};
+
+  RETURN_ON_CUDA_ERROR(cuInit(0));
+
+  // Linking requires a device context.
+  CUdevice device;
+  RETURN_ON_CUDA_ERROR(cuDeviceGet(&device, 0));
+  CUcontext context;
+  RETURN_ON_CUDA_ERROR(cuCtxCreate(&context, 0, device));
+  CUlinkState linkState;
+
+  CUjit_option jitOptions[] = {CU_JIT_ERROR_LOG_BUFFER,
+                               CU_JIT_ERROR_LOG_BUFFER_SIZE_BYTES};
+  void *jitOptionsVals[] = {jitErrorBuffer,
+                            reinterpret_cast<void *>(sizeof(jitErrorBuffer))};
+
+  RETURN_ON_CUDA_ERROR(cuLinkCreate(2,              /* number of jit options */
+                                    jitOptions,     /* jit options */
+                                    jitOptionsVals, /* jit option values */
+                                    &linkState));
+
+  auto kernelName = dyn_cast<gpu::GPUModuleOp>(getOperation()).getName().str();
+  RETURN_ON_CUDA_ERROR(cuLinkAddData(
+      linkState, CUjitInputType::CU_JIT_INPUT_PTX,
+      const_cast<void *>(static_cast<const void *>(serializedISA->c_str())),
+      serializedISA->length(), kernelName.c_str(),
+      0,       /* number of jit options */
+      nullptr, /* jit options */
+      nullptr  /* jit option values */
+      ));
+
+  void *cubinData;
+  size_t cubinSize;
+  RETURN_ON_CUDA_ERROR(cuLinkComplete(linkState, &cubinData, &cubinSize));
+
+  char *cubinAsChar = static_cast<char *>(cubinData);
+  auto result = SmallVector<char, 0>(cubinAsChar, cubinAsChar + cubinSize);
+
+  // This will also destroy the cubin data.
+  RETURN_ON_CUDA_ERROR(cuLinkDestroy(linkState));
+  RETURN_ON_CUDA_ERROR(cuCtxDestroy(context));
+  return result;
+}
+
+std::optional<SmallVector<char, 0>>
+NVPTXTargetAttr::serializeToObject(Operation *module,
+                                   const TargetOptions &options) const {
+  assert(module && "The module must be non null.");
+  if (!module)
+    return std::nullopt;
+  if (!mlir::isa<GPUModuleOp>(module)) {
+    module->emitError("Module must be a GPU module.");
+    return std::nullopt;
+  }
+  SerializeToCubin::init();
+  SerializeToCubin serializer(*module, *this, options);
+  return serializer.run();
+}
+
+#else
+// Provide a null vector for testing purposes.
+std::optional<SmallVector<char, 0>>
+NVPTXTargetAttr::serializeToObject(Operation *module,
+                                   const TargetOptions &options) const {
+  assert(module && "The module must be non null.");
+  if (!module)
+    return std::nullopt;
+  if (!mlir::isa<GPUModuleOp>(module)) {
+    module->emitError("Module must be a GPU module.");
+    return std::nullopt;
+  }
+  return SmallVector<char, 0>{};
+}
+#endif // MLIR_GPU_NVPTX_TARGET_ENABLED
+
+LogicalResult
+NVPTXTargetAttr::verify(function_ref<InFlightDiagnostic()> emitError,
+                        int optLevel, StringRef triple, StringRef chip,
+                        StringRef features, DictionaryAttr flags,
+                        ArrayAttr files) {
+  if (optLevel < 0 || optLevel > 3) {
+    emitError() << "The optimization level must be a number between 0 and 3.";
+    return failure();
+  }
+  if (triple.empty()) {
+    emitError() << "The target triple cannot be empty.";
+    return failure();
+  }
+  if (chip.empty()) {
+    emitError() << "The target chip cannot be empty.";
+    return failure();
+  }
+  if (files && llvm::all_of(files, [](::mlir::Attribute attr) {
+        return attr && mlir::isa<StringAttr>(attr);
+      })) {
+    emitError() << "All the elements in the `link` array must be strings.";
+    return failure();
+  }
+  return success();
+}