yaxunl created this revision.
yaxunl added reviewers: tra, rsmith.
Herald added subscribers: mattd, carlosgalvezp.
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yaxunl requested review of this revision.
nvcc allows using std::malloc and std::free in device code.
When std::malloc or std::free is passed as a template
function argument with template argument deduction,
there is no diagnostics. e.g.
#include <memory>
__global__ void kern() {
void *p = std::malloc(1);
std::free(p);
}
int main()
{
std::shared_ptr<float> a;
a = std::shared_ptr<float>(
(float*)std::malloc(sizeof(float) * 100),
std::free
);
return 0;
}
However, the same code fails to compile with clang
(https://godbolt.org/z/1roGvo6YY). The reason is
that clang does not have logic to choose a function
argument from an overloaded set of candidates
based on host/device attributes for template argument
deduction.
Currently, clang does have a logic to choose a candidate
based on the constraints of the candidates. This patch
extends that logic to account for the CUDA host/device-based
preference.
https://reviews.llvm.org/D154300
Files:
clang/lib/Sema/SemaOverload.cpp
clang/test/SemaCUDA/template-arg-deduction.cu
Index: clang/test/SemaCUDA/template-arg-deduction.cu
===================================================================
--- /dev/null
+++ clang/test/SemaCUDA/template-arg-deduction.cu
@@ -0,0 +1,27 @@
+// 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
+
+// expected-no-diagnostics
+
+#include "Inputs/cuda.h"
+
+void foo();
+__device__ void foo();
+
+template<class F>
+void host_temp(F f);
+
+template<class F>
+__device__ void device_temp(F f);
+
+void host_caller() {
+ host_temp(foo);
+}
+
+__global__ void kernel_caller() {
+ device_temp(foo);
+}
+
+__device__ void device_caller() {
+ device_temp(foo);
+}
Index: clang/lib/Sema/SemaOverload.cpp
===================================================================
--- clang/lib/Sema/SemaOverload.cpp
+++ clang/lib/Sema/SemaOverload.cpp
@@ -12697,6 +12697,20 @@
DeclAccessPair DAP;
SmallVector<FunctionDecl *, 2> AmbiguousDecls;
+ auto CheckCUDAPreference = [&](FunctionDecl *FD1,
+ FunctionDecl *FD2) -> std::optional<bool> {
+ FunctionDecl *Caller = getCurFunctionDecl(/*AllowLambda=*/true);
+ int Preference1 = IdentifyCUDAPreference(Caller, FD1);
+ int Preference2 = IdentifyCUDAPreference(Caller, FD2);
+ if (Preference1 > Preference2) {
+ return true;
+ } else if (Preference1 < Preference2) {
+ return false;
+ } else {
+ return std::nullopt;
+ }
+ };
+
auto CheckMoreConstrained = [&](FunctionDecl *FD1,
FunctionDecl *FD2) -> std::optional<bool> {
if (FunctionDecl *MF = FD1->getInstantiatedFromMemberFunction())
@@ -12727,9 +12741,33 @@
if (!checkAddressOfFunctionIsAvailable(FD))
continue;
+ // If we found a better result, update Result.
+ auto FoundBetter = [&]() {
+ IsResultAmbiguous = false;
+ DAP = I.getPair();
+ Result = FD;
+ };
+
// We have more than one result - see if it is more constrained than the
// previous one.
if (Result) {
+ // Check CUDA preference first. If the candidates have differennt CUDA
+ // preference, choose the one with higher CUDA preference. Otherwise,
+ // choose the one with more constraints.
+ if (getLangOpts().CUDA) {
+ std::optional<bool> MorePreferableByCUDA =
+ CheckCUDAPreference(FD, Result);
+ // If FD has different CUDA preference than Result.
+ if (MorePreferableByCUDA) {
+ // FD is less preferable than Result.
+ if (!*MorePreferableByCUDA)
+ continue;
+ // FD is more preferable than Result.
+ FoundBetter();
+ }
+ }
+ // FD has the same CUDA prefernece than Result. Continue check
+ // constraints.
std::optional<bool> MoreConstrainedThanPrevious =
CheckMoreConstrained(FD, Result);
if (!MoreConstrainedThanPrevious) {
@@ -12741,9 +12779,7 @@
continue;
// FD is more constrained - replace Result with it.
}
- IsResultAmbiguous = false;
- DAP = I.getPair();
- Result = FD;
+ FoundBetter();
}
if (IsResultAmbiguous)
@@ -12753,9 +12789,15 @@
SmallVector<const Expr *, 1> ResultAC;
// We skipped over some ambiguous declarations which might be ambiguous with
// the selected result.
- for (FunctionDecl *Skipped : AmbiguousDecls)
+ for (FunctionDecl *Skipped : AmbiguousDecls) {
+ // If skipped candidate has different CUDA preference than the result,
+ // there is no ambiguity. Otherwise check whether they have different
+ // constraints.
+ if (getLangOpts().CUDA && CheckCUDAPreference(Skipped, Result))
+ continue;
if (!CheckMoreConstrained(Skipped, Result))
return nullptr;
+ }
Pair = DAP;
}
return Result;
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