Context.BuiltinInfo.isPredefinedLibFunction(BuiltinID))
return 0;
+ // CUDA does not have device-side standard library. printf and malloc are the
+ // only special cases that are supported by device-side runtime.
+ if (Context.getLangOpts().CUDA && hasAttr<CUDADeviceAttr>() &&
+ !hasAttr<CUDAHostAttr>() &&
+ !(BuiltinID == Builtin::BIprintf || BuiltinID == Builtin::BImalloc))
+ return 0;
+
return BuiltinID;
}
--- /dev/null
+// REQUIRES: x86-registered-target
+// REQUIRES: nvptx-registered-target
+
+// RUN: %clang_cc1 -triple x86_64-unknown-linux-gnu -emit-llvm -o - %s | \
+// RUN: FileCheck --check-prefixes=HOST,BOTH %s
+// RUN: %clang_cc1 -fcuda-is-device -triple nvptx64-nvidia-cuda \
+// RUN: -emit-llvm -o - %s | FileCheck %s --check-prefixes=DEVICE,BOTH
+
+// BOTH-LABEL: define float @logf(float
+
+// logf() should be calling itself recursively as we don't have any standard
+// library on device side.
+// DEVICE: call float @logf(float
+extern "C" __attribute__((device)) float logf(float __x) { return logf(__x); }
+
+// NOTE: this case is to illustrate the expected differences in behavior between
+// the host and device. In general we do not mess with host-side standard
+// library.
+//
+// Host is assumed to have standard library, so logf() calls LLVM intrinsic.
+// HOST: call float @llvm.log.f32(float
+extern "C" float logf(float __x) { return logf(__x); }