我重载运算符,使float3
中的vectorspace.cuh
(和类似结构)上的向量空间:
// Boilerplate vector space over data type Pt
#pragma once
#include <type_traits>
// float3
__device__ __host__ float3 operator+=(float3& a, const float3& b) {
a.x += b.x; a.y += b.y; a.z += b.z;
return a;
}
__device__ __host__ float3 operator*=(float3& a, const float b) {
a.x *= b; a.y *= b; a.z *= b;
return a;
}
// float4
__device__ __host__ float4 operator+=(float4& a, const float4& b) {
a.x += b.x; a.y += b.y; a.z += b.z; a.w += b.w;
return a;
}
__device__ __host__ float4 operator*=(float4& a, const float b) {
a.x *= b; a.y *= b; a.z *= b; a.w *= b;
return a;
}
// Generalize += and *= to +, -=, -, *, /= and /
template<typename Pt> __device__ __host__
typename std::enable_if<std::is_class<Pt>::value || std::is_enum<Pt>::value, Pt>::type
operator+(const Pt& a, const Pt& b) {
auto sum = a;
sum += b;
return sum;
}
template<typename Pt> __device__ __host__
typename std::enable_if<std::is_class<Pt>::value || std::is_enum<Pt>::value, Pt>::type
operator-=(Pt& a, const Pt& b) {
a += -1*b;
return a;
}
template<typename Pt> __device__ __host__
typename std::enable_if<std::is_class<Pt>::value || std::is_enum<Pt>::value, Pt>::type
operator-(const Pt& a, const Pt& b) {
auto diff = a;
diff -= b;
return diff;
}
template<typename Pt> __device__ __host__
typename std::enable_if<std::is_class<Pt>::value || std::is_enum<Pt>::value, Pt>::type
operator-(const Pt& a) {
return -1*a;
}
template<typename Pt> __device__ __host__
typename std::enable_if<std::is_class<Pt>::value || std::is_enum<Pt>::value, Pt>::type
operator*(const Pt& a, const float b) {
auto prod = a;
prod *= b;
return prod;
}
template<typename Pt> __device__ __host__
typename std::enable_if<std::is_class<Pt>::value || std::is_enum<Pt>::value, Pt>::type
operator*(const float b, const Pt& a) {
auto prod = a;
prod *= b;
return prod;
}
template<typename Pt> __device__ __host__
typename std::enable_if<std::is_class<Pt>::value || std::is_enum<Pt>::value, Pt>::type
operator/=(Pt& a, const float b) {
a *= 1./b;
return a;
}
template<typename Pt> __device__ __host__
typename std::enable_if<std::is_class<Pt>::value || std::is_enum<Pt>::value, Pt>::type
operator/(const Pt& a, const float b) {
auto quot = a;
quot /= b;
return quot;
}
这些重载会破坏thrust::reduce
的编译,这里有一个例子:
#include <thrust/reduce.h>
#include <thrust/execution_policy.h>
#include "vectorspace.cuh"
int main(int argc, char const *argv[]) {
int n = 10;
float3* d_arr;
cudaMalloc(&d_arr, n*sizeof(float3));
auto sum = thrust::reduce(thrust::device, d_arr, d_arr + n, float3 {0});
return 0;
}
在Ubuntu 16.04上使用nvcc -std=c++11 -arch=sm_52
会导致200多行编译错误:
$ nvcc -std=c++11 -arch=sm_52 sandbox/mean.cu
sandbox/mean.cu(26): error: no operator "*" matches these operands
operand types are: int * const thrust::zip_iterator<thrust::tuple<const float3 *, thrust::pointer<float3, thrust::system::cuda::detail::par_t, thrust::use_default, thrust::use_default>, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type>>
detected during:
instantiation of "std::enable_if<<expression>, Pt>::type operator-=(Pt &, const Pt &) [with Pt=thrust::zip_iterator<thrust::tuple<const float3 *, thrust::pointer<float3, thrust::system::cuda::detail::par_t, thrust::use_default, thrust::use_default>, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type>>]"
(35): here
instantiation of "std::enable_if<<expression>, Pt>::type operator-(const Pt &, const Pt &) [with Pt=thrust::zip_iterator<thrust::tuple<const float3 *, thrust::pointer<float3, thrust::system::cuda::detail::par_t, thrust::use_default, thrust::use_default>, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type, thrust::null_type>>]"
...
如何在不破坏thrust
的情况下重载运算符?
答案 0 :(得分:2)
(在OP的编辑后编辑。)
问题在于运算符重载的“范围”:您不仅仅为您感兴趣的类重载,而是适合您enable_if
条件的所有类的重载 - 这很放松。即使事情会编译,这已经是一个严重的错误。
所以你必须:
std::is_same
中enable_if
的分离)或使用trait class:
template<class T> struct needs_qivs_arithmetic_operators : public std::false_type {};
template<> struct needs_qivs_arithmetic_operators<float3> : public std::true_type {};
template<> struct needs_qivs_arithmetic_operators<float4> : public std::true_type {};
/* ... etc. You can also add specializations elsewhere in the translation unit. */