[mlir] Replace MLIR_ENABLE_CUDA_CONVERSIONS with LLVM_HAS_NVPTX_TARGET #93008

tyb0807 · 2024-05-22T09:26:30Z

LLVM_HAS_NVPTX_TARGET is automatically set depending on whether NVPTX was enabled when building LLVM. Use this instead of manually defining MLIR_ENABLE_CUDA_CONVERSIONS (whose name is a bit misleading btw).

llvmbot · 2024-05-22T09:26:59Z

@llvm/pr-subscribers-mlir-gpu

@llvm/pr-subscribers-mlir-llvm

Author: None (tyb0807)

Changes

Currently we only allow to serialize GPU module if CUDA toolkit is present, while in fact only serializing to binary format requires the latter.

This change make it possible to serialize GPU module to offload or assembly formats even when CUDA toolkit is not provided. The condition to be able to serialize GPU module is NVPTX target having been specified when building LLVM.

Full diff: https://github.com/llvm/llvm-project/pull/93008.diff

2 Files Affected:

(modified) mlir/lib/Target/LLVM/NVVM/Target.cpp (+29-16)
(modified) mlir/unittests/Target/LLVM/SerializeNVVMTarget.cpp (+1-1)

diff --git a/mlir/lib/Target/LLVM/NVVM/Target.cpp b/mlir/lib/Target/LLVM/NVVM/Target.cpp
index e438ce84af1b5..02b1c1ae3a6b5 100644
--- a/mlir/lib/Target/LLVM/NVVM/Target.cpp
+++ b/mlir/lib/Target/LLVM/NVVM/Target.cpp
@@ -158,7 +158,7 @@ SerializeGPUModuleBase::loadBitcodeFiles(llvm::Module &module) {
   return std::move(bcFiles);
 }
 
-#if MLIR_ENABLE_CUDA_CONVERSIONS
+#if LLVM_HAS_NVPTX_TARGET
 namespace {
 class NVPTXSerializer : public SerializeGPUModuleBase {
 public:
@@ -167,6 +167,15 @@ class NVPTXSerializer : public SerializeGPUModuleBase {
 
   gpu::GPUModuleOp getOperation();
 
+  std::optional<SmallVector<char, 0>>
+  moduleToObject(llvm::Module &llvmModule) override;
+
+private:
+  // Target options.
+  gpu::TargetOptions targetOptions;
+
+#if MLIR_ENABLE_CUDA_CONVERSIONS
+public:
   // Compile PTX to cubin using `ptxas`.
   std::optional<SmallVector<char, 0>>
   compileToBinary(const std::string &ptxCode);
@@ -175,9 +184,6 @@ class NVPTXSerializer : public SerializeGPUModuleBase {
   std::optional<SmallVector<char, 0>>
   compileToBinaryNVPTX(const std::string &ptxCode);
 
-  std::optional<SmallVector<char, 0>>
-  moduleToObject(llvm::Module &llvmModule) override;
-
 private:
   using TmpFile = std::pair<llvm::SmallString<128>, llvm::FileRemover>;
 
@@ -190,9 +196,7 @@ class NVPTXSerializer : public SerializeGPUModuleBase {
   // 2. In the system PATH.
   // 3. The path from `getCUDAToolkitPath()`.
   std::optional<std::string> findTool(StringRef tool);
-
-  // Target options.
-  gpu::TargetOptions targetOptions;
+#endif // MLIR_ENABLE_CUDA_CONVERSIONS
 };
 } // namespace
 
@@ -201,6 +205,11 @@ NVPTXSerializer::NVPTXSerializer(Operation &module, NVVMTargetAttr target,
     : SerializeGPUModuleBase(module, target, targetOptions),
       targetOptions(targetOptions) {}
 
+gpu::GPUModuleOp NVPTXSerializer::getOperation() {
+  return dyn_cast<gpu::GPUModuleOp>(&SerializeGPUModuleBase::getOperation());
+}
+
+#if MLIR_ENABLE_CUDA_CONVERSIONS
 std::optional<NVPTXSerializer::TmpFile>
 NVPTXSerializer::createTemp(StringRef name, StringRef suffix) {
   llvm::SmallString<128> filename;
@@ -214,10 +223,6 @@ NVPTXSerializer::createTemp(StringRef name, StringRef suffix) {
   return TmpFile(filename, llvm::FileRemover(filename.c_str()));
 }
 
-gpu::GPUModuleOp NVPTXSerializer::getOperation() {
-  return dyn_cast<gpu::GPUModuleOp>(&SerializeGPUModuleBase::getOperation());
-}
-
 std::optional<std::string> NVPTXSerializer::findTool(StringRef tool) {
   // Find the `tool` path.
   // 1. Check the toolkit path given in the command line.
@@ -512,10 +517,11 @@ NVPTXSerializer::compileToBinaryNVPTX(const std::string &ptxCode) {
   return binary;
 }
 #endif // MLIR_ENABLE_NVPTXCOMPILER
+#endif // MLIR_ENABLE_CUDA_CONVERSIONS
 
 std::optional<SmallVector<char, 0>>
 NVPTXSerializer::moduleToObject(llvm::Module &llvmModule) {
-  // Return LLVM IR if the compilation target is offload.
+  // Return LLVM IR if the compilation target is `offload`.
 #define DEBUG_TYPE "serialize-to-llvm"
   LLVM_DEBUG({
     llvm::dbgs() << "LLVM IR for module: " << getOperation().getNameAttr()
@@ -549,7 +555,7 @@ NVPTXSerializer::moduleToObject(llvm::Module &llvmModule) {
   });
 #undef DEBUG_TYPE
 
-  // Return PTX if the compilation target is assembly.
+  // Return PTX if the compilation target is `assembly`.
   if (targetOptions.getCompilationTarget() ==
       gpu::CompilationTarget::Assembly) {
     // Make sure to include the null terminator.
@@ -557,6 +563,13 @@ NVPTXSerializer::moduleToObject(llvm::Module &llvmModule) {
     return SmallVector<char, 0>(bin.begin(), bin.end());
   }
 
+  // At this point, compilation target is either `binary` or `fatbinary`, which
+  // requires CUDA toolkit.
+  if (!(MLIR_ENABLE_CUDA_CONVERSIONS)) {
+    getOperation().emitError(
+        "CUDA toolkit not provided when trying to serialize GPU module.");
+    return std::nullopt;
+  }
   // Compile to binary.
 #if MLIR_ENABLE_NVPTXCOMPILER
   return compileToBinaryNVPTX(*serializedISA);
@@ -564,7 +577,7 @@ NVPTXSerializer::moduleToObject(llvm::Module &llvmModule) {
   return compileToBinary(*serializedISA);
 #endif // MLIR_ENABLE_NVPTXCOMPILER
 }
-#endif // MLIR_ENABLE_CUDA_CONVERSIONS
+#endif // LLVM_HAS_NVPTX_TARGET
 
 std::optional<SmallVector<char, 0>>
 NVVMTargetAttrImpl::serializeToObject(Attribute attribute, Operation *module,
@@ -576,7 +589,7 @@ NVVMTargetAttrImpl::serializeToObject(Attribute attribute, Operation *module,
     module->emitError("Module must be a GPU module.");
     return std::nullopt;
   }
-#if MLIR_ENABLE_CUDA_CONVERSIONS
+#if LLVM_HAS_NVPTX_TARGET
   NVPTXSerializer serializer(*module, cast<NVVMTargetAttr>(attribute), options);
   serializer.init();
   return serializer.run();
@@ -584,7 +597,7 @@ NVVMTargetAttrImpl::serializeToObject(Attribute attribute, Operation *module,
   module->emitError(
       "The `NVPTX` target was not built. Please enable it when building LLVM.");
   return std::nullopt;
-#endif // MLIR_ENABLE_CUDA_CONVERSIONS
+#endif // LLVM_HAS_NVPTX_TARGET
 }
 
 Attribute
diff --git a/mlir/unittests/Target/LLVM/SerializeNVVMTarget.cpp b/mlir/unittests/Target/LLVM/SerializeNVVMTarget.cpp
index cea49356538f0..a8fe20d52fb2a 100644
--- a/mlir/unittests/Target/LLVM/SerializeNVVMTarget.cpp
+++ b/mlir/unittests/Target/LLVM/SerializeNVVMTarget.cpp
@@ -30,7 +30,7 @@
 using namespace mlir;
 
 // Skip the test if the NVPTX target was not built.
-#if MLIR_ENABLE_CUDA_CONVERSIONS
+#if LLVM_HAS_NVPTX_TARGET
 #define SKIP_WITHOUT_NVPTX(x) x
 #else
 #define SKIP_WITHOUT_NVPTX(x) DISABLED_##x

llvmbot · 2024-05-22T09:26:59Z

@llvm/pr-subscribers-mlir

Author: None (tyb0807)

Changes

Currently we only allow to serialize GPU module if CUDA toolkit is present, while in fact only serializing to binary format requires the latter.

This change make it possible to serialize GPU module to offload or assembly formats even when CUDA toolkit is not provided. The condition to be able to serialize GPU module is NVPTX target having been specified when building LLVM.

Full diff: https://github.com/llvm/llvm-project/pull/93008.diff

2 Files Affected:

(modified) mlir/lib/Target/LLVM/NVVM/Target.cpp (+29-16)
(modified) mlir/unittests/Target/LLVM/SerializeNVVMTarget.cpp (+1-1)

diff --git a/mlir/lib/Target/LLVM/NVVM/Target.cpp b/mlir/lib/Target/LLVM/NVVM/Target.cpp
index e438ce84af1b5..02b1c1ae3a6b5 100644
--- a/mlir/lib/Target/LLVM/NVVM/Target.cpp
+++ b/mlir/lib/Target/LLVM/NVVM/Target.cpp
@@ -158,7 +158,7 @@ SerializeGPUModuleBase::loadBitcodeFiles(llvm::Module &module) {
   return std::move(bcFiles);
 }
 
-#if MLIR_ENABLE_CUDA_CONVERSIONS
+#if LLVM_HAS_NVPTX_TARGET
 namespace {
 class NVPTXSerializer : public SerializeGPUModuleBase {
 public:
@@ -167,6 +167,15 @@ class NVPTXSerializer : public SerializeGPUModuleBase {
 
   gpu::GPUModuleOp getOperation();
 
+  std::optional<SmallVector<char, 0>>
+  moduleToObject(llvm::Module &llvmModule) override;
+
+private:
+  // Target options.
+  gpu::TargetOptions targetOptions;
+
+#if MLIR_ENABLE_CUDA_CONVERSIONS
+public:
   // Compile PTX to cubin using `ptxas`.
   std::optional<SmallVector<char, 0>>
   compileToBinary(const std::string &ptxCode);
@@ -175,9 +184,6 @@ class NVPTXSerializer : public SerializeGPUModuleBase {
   std::optional<SmallVector<char, 0>>
   compileToBinaryNVPTX(const std::string &ptxCode);
 
-  std::optional<SmallVector<char, 0>>
-  moduleToObject(llvm::Module &llvmModule) override;
-
 private:
   using TmpFile = std::pair<llvm::SmallString<128>, llvm::FileRemover>;
 
@@ -190,9 +196,7 @@ class NVPTXSerializer : public SerializeGPUModuleBase {
   // 2. In the system PATH.
   // 3. The path from `getCUDAToolkitPath()`.
   std::optional<std::string> findTool(StringRef tool);
-
-  // Target options.
-  gpu::TargetOptions targetOptions;
+#endif // MLIR_ENABLE_CUDA_CONVERSIONS
 };
 } // namespace
 
@@ -201,6 +205,11 @@ NVPTXSerializer::NVPTXSerializer(Operation &module, NVVMTargetAttr target,
     : SerializeGPUModuleBase(module, target, targetOptions),
       targetOptions(targetOptions) {}
 
+gpu::GPUModuleOp NVPTXSerializer::getOperation() {
+  return dyn_cast<gpu::GPUModuleOp>(&SerializeGPUModuleBase::getOperation());
+}
+
+#if MLIR_ENABLE_CUDA_CONVERSIONS
 std::optional<NVPTXSerializer::TmpFile>
 NVPTXSerializer::createTemp(StringRef name, StringRef suffix) {
   llvm::SmallString<128> filename;
@@ -214,10 +223,6 @@ NVPTXSerializer::createTemp(StringRef name, StringRef suffix) {
   return TmpFile(filename, llvm::FileRemover(filename.c_str()));
 }
 
-gpu::GPUModuleOp NVPTXSerializer::getOperation() {
-  return dyn_cast<gpu::GPUModuleOp>(&SerializeGPUModuleBase::getOperation());
-}
-
 std::optional<std::string> NVPTXSerializer::findTool(StringRef tool) {
   // Find the `tool` path.
   // 1. Check the toolkit path given in the command line.
@@ -512,10 +517,11 @@ NVPTXSerializer::compileToBinaryNVPTX(const std::string &ptxCode) {
   return binary;
 }
 #endif // MLIR_ENABLE_NVPTXCOMPILER
+#endif // MLIR_ENABLE_CUDA_CONVERSIONS
 
 std::optional<SmallVector<char, 0>>
 NVPTXSerializer::moduleToObject(llvm::Module &llvmModule) {
-  // Return LLVM IR if the compilation target is offload.
+  // Return LLVM IR if the compilation target is `offload`.
 #define DEBUG_TYPE "serialize-to-llvm"
   LLVM_DEBUG({
     llvm::dbgs() << "LLVM IR for module: " << getOperation().getNameAttr()
@@ -549,7 +555,7 @@ NVPTXSerializer::moduleToObject(llvm::Module &llvmModule) {
   });
 #undef DEBUG_TYPE
 
-  // Return PTX if the compilation target is assembly.
+  // Return PTX if the compilation target is `assembly`.
   if (targetOptions.getCompilationTarget() ==
       gpu::CompilationTarget::Assembly) {
     // Make sure to include the null terminator.
@@ -557,6 +563,13 @@ NVPTXSerializer::moduleToObject(llvm::Module &llvmModule) {
     return SmallVector<char, 0>(bin.begin(), bin.end());
   }
 
+  // At this point, compilation target is either `binary` or `fatbinary`, which
+  // requires CUDA toolkit.
+  if (!(MLIR_ENABLE_CUDA_CONVERSIONS)) {
+    getOperation().emitError(
+        "CUDA toolkit not provided when trying to serialize GPU module.");
+    return std::nullopt;
+  }
   // Compile to binary.
 #if MLIR_ENABLE_NVPTXCOMPILER
   return compileToBinaryNVPTX(*serializedISA);
@@ -564,7 +577,7 @@ NVPTXSerializer::moduleToObject(llvm::Module &llvmModule) {
   return compileToBinary(*serializedISA);
 #endif // MLIR_ENABLE_NVPTXCOMPILER
 }
-#endif // MLIR_ENABLE_CUDA_CONVERSIONS
+#endif // LLVM_HAS_NVPTX_TARGET
 
 std::optional<SmallVector<char, 0>>
 NVVMTargetAttrImpl::serializeToObject(Attribute attribute, Operation *module,
@@ -576,7 +589,7 @@ NVVMTargetAttrImpl::serializeToObject(Attribute attribute, Operation *module,
     module->emitError("Module must be a GPU module.");
     return std::nullopt;
   }
-#if MLIR_ENABLE_CUDA_CONVERSIONS
+#if LLVM_HAS_NVPTX_TARGET
   NVPTXSerializer serializer(*module, cast<NVVMTargetAttr>(attribute), options);
   serializer.init();
   return serializer.run();
@@ -584,7 +597,7 @@ NVVMTargetAttrImpl::serializeToObject(Attribute attribute, Operation *module,
   module->emitError(
       "The `NVPTX` target was not built. Please enable it when building LLVM.");
   return std::nullopt;
-#endif // MLIR_ENABLE_CUDA_CONVERSIONS
+#endif // LLVM_HAS_NVPTX_TARGET
 }
 
 Attribute
diff --git a/mlir/unittests/Target/LLVM/SerializeNVVMTarget.cpp b/mlir/unittests/Target/LLVM/SerializeNVVMTarget.cpp
index cea49356538f0..a8fe20d52fb2a 100644
--- a/mlir/unittests/Target/LLVM/SerializeNVVMTarget.cpp
+++ b/mlir/unittests/Target/LLVM/SerializeNVVMTarget.cpp
@@ -30,7 +30,7 @@
 using namespace mlir;
 
 // Skip the test if the NVPTX target was not built.
-#if MLIR_ENABLE_CUDA_CONVERSIONS
+#if LLVM_HAS_NVPTX_TARGET
 #define SKIP_WITHOUT_NVPTX(x) x
 #else
 #define SKIP_WITHOUT_NVPTX(x) DISABLED_##x

ftynse

Looks reasonable, IIRC, the design of the new GPU pipeline was intended to avoid a compile-time dependency on CUDA libraries.

Does the AMD backend suffer from the same issue?

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

ftynse · 2024-05-22T10:21:02Z

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

+  // requires CUDA toolkit.
+  if (!(MLIR_ENABLE_CUDA_CONVERSIONS)) {
+    getOperation().emitError(
+        "CUDA toolkit not provided when trying to serialize GPU module.");


Suggested change

"CUDA toolkit not provided when trying to serialize GPU module.");

"CUDA toolkit not provided when trying to serialize GPU module");

grypp

Looks good, is it possible to add a test?

grypp · 2024-05-22T10:27:03Z

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

+  // requires CUDA toolkit.
+  if (!(MLIR_ENABLE_CUDA_CONVERSIONS)) {
+    getOperation().emitError(
+        "CUDA toolkit not provided when trying to serialize GPU module.");


Can we test that path?

fabianmcg

They're already decoupled, MLIR_ENABLE_CUDA_CONVERSIONS is an alias for checking whether the NVPTX target was built, see:
https://github.com/llvm/llvm-project/blob/main/mlir/CMakeLists.txt#L115C1-L119

Also, moduleToObject will succeed if NVPTX was built and the compilation target is offload or ptx, I know this because I use it frequently in a machine without the toolkit.

I'm ok with changing the name of the flag as it might be confusing.

tyb0807 · 2024-05-22T12:21:12Z

They're already decoupled, MLIR_ENABLE_CUDA_CONVERSIONS is an alias for checking whether the NVPTX target was built, see: https://github.com/llvm/llvm-project/blob/main/mlir/CMakeLists.txt#L115C1-L119

Also, moduleToObject will succeed if NVPTX was built and the compilation target is offload or ptx, I know this because I use it frequently in a machine without the toolkit.

I'm ok with changing the name of the flag as it might be confusing.

Yes, one of the changes introduced here is just replacing MLIR_ENABLE_CUDA_CONVERSIONS with LLVM_HAS_NVPTX_TARGET. However, I'm keeping MLIR_ENABLE_CUDA_CONVERSIONS flag to indicate whether CUDA toolkit is configured or not, as one can build LLVM with NVPTX, then accidentally try to serialize to binary without having the toolkit available. The part of the code that does actual serialization to binary (using ptxas or nvptxcompiler) will now be guarded by MLIR_ENABLE_CUDA_CONVERSIONS and should only be available if CUDA toolkit is configured.

Does this make sense?

fabianmcg · 2024-05-22T12:36:29Z

The part of the code that does actual serialization to binary (using ptxas or nvptxcompiler) will now be guarded by MLIR_ENABLE_CUDA_CONVERSIONS and should only be available if CUDA toolkit is configured.

Does this make sense?

Not really. Because you're not changing the definition of MLIR_ENABLE_CUDA_CONVERSIONS, hence MLIR_ENABLE_CUDA_CONVERSIONS and LLVM_HAS_NVPTX_TARGET still fulfill the same purpose.

If the CUDA toolkit is not installed and try to serialize to binary you'll get:

error: Couldn't find the `ptxas` binary. Please specify the toolkit path, add the compiler to $PATH, or set one of the environment variables in `NVVM::getCUDAToolkitPath()`.

And that's by design, as it allows to ship the functionality of compilation without requiring a hard dependency on the toolkit. This is also what clang does, you don't need the toolkit to build clang, only for compiling the code and if the toolkit is missing then fail gracefully.

tyb0807 · 2024-05-22T13:02:04Z

Because you're not changing the definition of MLIR_ENABLE_CUDA_CONVERSIONS, hence MLIR_ENABLE_CUDA_CONVERSIONS and LLVM_HAS_NVPTX_TARGET still fulfill the same purpose.

Yes I'd wanted to change the definition of MLIR_ENABLE_CUDA_CONVERSIONS in a separate patch, but now I realize it doesn't make much sense w/o that change here.

If the CUDA toolkit is not installed and try to serialize to binary you'll get:

Right, I know this situation is handled, but thought it'd be better to guard the whole definition of compileToBinary behind a flag saying whether CUDA toolkit is available.

Note that naming of MLIR_ENABLE_CUDA_CONVERSIONS is so confusing that it is set here

llvm-project/utils/bazel/llvm-project-overlay/mlir/BUILD.bazel

Lines 54 to 56 in cdcd653

    
           } | if_cuda_available( 
        
               {"#cmakedefine01 MLIR_ENABLE_CUDA_CONVERSIONS": "#define MLIR_ENABLE_CUDA_CONVERSIONS 1"}, 
        
               {"#cmakedefine01 MLIR_ENABLE_CUDA_CONVERSIONS": "#define MLIR_ENABLE_CUDA_CONVERSIONS 0"},

w/o checking NVPTX target.

So I guess we should only change MLIR_ENABLE_CUDA_CONVERSIONS to LLVM_HAS_NVPTX_TARGET here. I've looked at other usages of MLIR_ENABLE_CUDA_CONVERSIONS across the codebase and I believe we can replace MLIR_ENABLE_CUDA_CONVERSIONS by LLVM_HAS_NVPTX_TARGET entirely. WDYT?

joker-eph · 2024-05-22T14:39:48Z

Considering the discussion, the whole PR title and description will need a revamp I believe.

tyb0807 · 2024-05-22T21:52:20Z

I've replaced MLIR_ENABLE_CUDA_CONVERSIONS with LLVM_HAS_NVPTX_TARGET. There are way more modifications than anticipated but these are NFC IMO.

joker-eph · 2024-05-22T21:58:14Z

I don't see a change in mlir-config.h ? Can you grep for MLIR_ENABLE_CUDA_CONVERSIONS and ensure it does not remain any occurrence in the codebase.

mlir/test/lit.site.cfg.py.in

tyb0807 · 2024-05-22T22:14:26Z

I don't see a change in mlir-config.h ? Can you grep for MLIR_ENABLE_CUDA_CONVERSIONS and ensure it does not remain any occurrence in the codebase

Indeed, I messed up during rebase somehow. Thanks!

tyb0807 · 2024-05-23T06:46:26Z

@fabianmcg is it better now?

fabianmcg

LGTM, thank you! Just make sure that:

all integration tests pass
ninja check-mlir succeeds with and without the NVPTX being built.
fix the description of the commit.

ftynse

Looks even cleaner, thanks! But I suspect there is something off with how the macro is interpreted, it should be an always-defined 0/1 macro.

Note that Bazel is an optional build system for LLVM, you don't necessarily have to update it.

ftynse · 2024-05-24T09:50:32Z

mlir/lib/Target/LLVM/CMakeLists.txt

@@ -47,7 +47,7 @@ add_mlir_dialect_library(MLIRNVVMTarget
  MLIRNVVMToLLVMIRTranslation
  )

-if(MLIR_ENABLE_CUDA_CONVERSIONS)
+if ("NVPTX" IN_LIST LLVM_TARGETS_TO_BUILD)
  # Find the CUDA toolkit.
  find_package(CUDAToolkit)


Can we add an INFO message in the else() branch below saying "CUDA not found" rather than always saying "MLIR default CUDA toolkit path"?

This is marked resolved but I don't see the change?

mlir/test/lit.site.cfg.py.in

utils/bazel/llvm-project-overlay/mlir/test/BUILD.bazel

tyb0807 · 2024-05-24T12:40:40Z

Thanks, your comment pushed me to find a better solution, and I'm glad there's a nice one without having to add quotes and stuff. Nice!

This dep was removed in that change, but this library still needs it.

tyb0807 requested review from ftynse, joker-eph, grypp and fabianmcg May 22, 2024 09:26

llvmbot added mlir:llvm mlir labels May 22, 2024

ftynse approved these changes May 22, 2024

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tyb0807 force-pushed the nvptx branch from b92aac4 to 0d31af7 Compare May 22, 2024 20:53

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llvmbot added mlir:gpu bazel "Peripheral" support tier build system: utils/bazel labels May 22, 2024

tyb0807 changed the title ~~[mlir] Decouple NVPTX target from CUDA toolkit presence~~ [mlir] Replace MLIR_ENABLE_CUDA_CONVERSIONS with LLVM_HAS_NVPTX_TARGET May 22, 2024

tyb0807 force-pushed the nvptx branch from 0d31af7 to a992a75 Compare May 22, 2024 21:40

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[mlir] Replace MLIR_ENABLE_CUDA_CONVERSIONS with LLVM_HAS_NVPTX_TARGET

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tyb0807 merged commit 8178a3a into llvm:main May 24, 2024
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keith added a commit that referenced this pull request May 24, 2024

[bazel] Add missing dep after #93008 (#93325)

41c057b

This dep was removed in that change, but this library still needs it.

tyb0807 deleted the nvptx branch May 24, 2024 20:20

	"CUDA toolkit not provided when trying to serialize GPU module.");
	"CUDA toolkit not provided when trying to serialize GPU module");

[mlir] Replace MLIR_ENABLE_CUDA_CONVERSIONS with LLVM_HAS_NVPTX_TARGET #93008

[mlir] Replace MLIR_ENABLE_CUDA_CONVERSIONS with LLVM_HAS_NVPTX_TARGET #93008

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tyb0807 commented May 22, 2024 •

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llvmbot commented May 22, 2024 •

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fabianmcg left a comment •

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tyb0807 commented May 22, 2024 •

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fabianmcg commented May 22, 2024 •

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tyb0807 commented May 22, 2024 •

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