[PATCH] D24522: [CUDA] Do not merge CUDA target attributes.

[Artem Belevich via cfe-commits]

tra created this revision.
tra added a reviewer: jlebar.
tra added a subscriber: cfe-commits.
Herald added a subscriber: jlebar.

CUDA target attributes are used for function overloading and must not be merged.

This fixes a bug where attributes were inherited during function template 
specialization in CUDA and made it impossible for specialized function 
to provide its own target attributes.


https://reviews.llvm.org/D24522

Files:
  lib/Sema/SemaDecl.cpp
  test/SemaCUDA/function-overload.cu
  test/SemaCUDA/target_attr_inheritance.cu

Index: test/SemaCUDA/target_attr_inheritance.cu
===================================================================
--- /dev/null
+++ test/SemaCUDA/target_attr_inheritance.cu
@@ -0,0 +1,31 @@
+// Verifies correct inheritance of target attributes during template
+// instantiation and specialization.
+// REQUIRES: x86-registered-target
+// REQUIRES: nvptx-registered-target
+
+// RUN: %clang_cc1 -triple x86_64-unknown-linux-gnu -fsyntax-only -verify %s
+// RUN: %clang_cc1 -triple nvptx64-nvidia-cuda -fsyntax-only -fcuda-is-device -verify %s
+
+#include "Inputs/cuda.h"
+
+// Function must inherit target attributes during instantiation, but not during
+// specialization.
+template <typename T> __host__ __device__ T function_template(const T &a);
+
+// Specialized functions have their own attributes.
+// expected-note at +1 {{candidate function not viable: call to __host__ function from __device__ function}}
+template <> __host__ float function_template<float>(const float &from);
+
+// expected-note at +1 {{candidate function not viable: call to __device__ function from __host__ function}}
+template <> __device__ double function_template<double>(const double &from);
+
+__host__ void hf() {
+  function_template<float>(1.0f); // OK. Specialization is __host__.
+  function_template<double>(2.0); // expected-error {{no matching function for call to 'function_template'}}
+  function_template(1);           // OK. Instantiated function template is HD.
+}
+__device__ void df() {
+  function_template<float>(3.0f); // expected-error {{no matching function for call to 'function_template'}}
+  function_template<double>(4.0); // OK. Specialization is __device__.
+  function_template(1);           // OK. Instantiated function template is HD.
+}
Index: test/SemaCUDA/function-overload.cu
===================================================================
--- test/SemaCUDA/function-overload.cu
+++ test/SemaCUDA/function-overload.cu
@@ -379,3 +379,14 @@
   HostReturnTy ret3 = host_only_function(1);
   HostReturnTy2 ret4 = host_only_function(1.0f);
 }
+
+// Verify that we allow overloading function templates.
+template <typename T> __host__ T template_overload(const T &a) { return a; };
+template <typename T> __device__ T template_overload(const T &a) { return a; };
+
+__host__ void test_host_template_overload() {
+  template_overload(1); // OK. Attribute-based overloading picks __host__ variant.
+}
+__device__ void test_device_template_overload() {
+  template_overload(1); // OK. Attribute-based overloading picks __device__ variant.
+}
Index: lib/Sema/SemaDecl.cpp
===================================================================
--- lib/Sema/SemaDecl.cpp
+++ lib/Sema/SemaDecl.cpp
@@ -2292,7 +2292,13 @@
     NewAttr = S.mergeAlwaysInlineAttr(D, AA->getRange(),
                                       &S.Context.Idents.get(AA->getSpelling()),
                                       AttrSpellingListIndex);
-  else if (const auto *MA = dyn_cast<MinSizeAttr>(Attr))
+  else if (S.getLangOpts().CUDA && isa<FunctionDecl>(D) &&
+           (isa<CUDAHostAttr>(Attr) || isa<CUDADeviceAttr>(Attr) ||
+            isa<CUDAGlobalAttr>(Attr))) {
+    // CUDA target attributes are part of function signature for
+    // overloading purposes and must not be merged.
+    return false;
+  } else if (const auto *MA = dyn_cast<MinSizeAttr>(Attr))
     NewAttr = S.mergeMinSizeAttr(D, MA->getRange(), AttrSpellingListIndex);
   else if (const auto *OA = dyn_cast<OptimizeNoneAttr>(Attr))
     NewAttr = S.mergeOptimizeNoneAttr(D, OA->getRange(), AttrSpellingListIndex);


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