問題描述
我已經到處搜索有關如何在 CUDA 中使用類的一些見解，雖然普遍認為它可以完成并且顯然是由人們完成的，但我很難找到如何真正做到這一點.
我有一個類，它實現了一個帶有運算符重載等的基本位集.我需要能夠在主機和設備上實例化此類的對象，在兩者之間進行復制等.我是否在 .cu 中定義了此類?如果是這樣，我如何在我的主機端 C++ 代碼中使用它?類的函數不需要訪問像threadId這樣的特殊CUDA變量；它只需要能夠用于主機和設備端.
感謝您的幫助，如果我以完全錯誤的方式處理這個問題，我很樂意聽到替代方案.
在 #include 的頭文件中定義類，就像在 C++ 中一樣.
任何必須從設備代碼調用的方法都應該使用 __device__ 和 __host__ 聲明規范，包括構造函數和析構函數，如果您打算使用 new/delete 在設備上(注意 new/delete 需要 CUDA 4.0 和計算能力 2.0 或更高的 GPU).>
你可能想定義一個像
這樣的宏#ifdef __CUDACC__#define CUDA_CALLABLE_MEMBER __host__ __device__#別的#define CUDA_CALLABLE_MEMBER#萬一然后在你的成員函數上使用這個宏
class Foo {民眾:CUDA_CALLABLE_MEMBER Foo() {}CUDA_CALLABLE_MEMBER ~Foo() {}CUDA_CALLABLE_MEMBER void aMethod() {}};這樣做的原因是只有 CUDA 編譯器知道 __device__ 和 __host__ —— 你的主機 C++ 編譯器會引發錯誤.
注意 __CUDACC__ 已定義由 NVCC 在編譯 CUDA 文件時使用.這可以是在使用 NVCC 編譯 .cu 文件時，也可以是在使用命令行選項 -x cu 編譯任何文件時.
I've searched all over for some insight on how exactly to use classes with CUDA, and while there is a general consensus that it can be done and apparently is being done by people, I've had a hard time finding out how to actually do it.
I have a class which implements a basic bitset with operator overloading and the like. I need to be able to instantiate objects of this class on both the host and the device, copy between the two, etc. Do I define this class in a .cu? If so, how do I use it in my host-side C++ code? The functions of the class do not need to access special CUDA variables like threadId; it just needs to be able to be used host and device side.
Thanks for any help, and if I'm approaching this in completely the wrong way, I'd love to hear alternatives.
Define the class in a header that you #include, just like in C++.
Any method that must be called from device code should be defined with both __device__ and __host__ declspecs, including the constructor and destructor if you plan to use new/delete on the device (note new/delete require CUDA 4.0 and a compute capability 2.0 or higher GPU).
You probably want to define a macro like
#ifdef __CUDACC__
#define CUDA_CALLABLE_MEMBER __host__ __device__
#else
#define CUDA_CALLABLE_MEMBER
#endif
Then use this macro on your member functions
class Foo {
public:
CUDA_CALLABLE_MEMBER Foo() {}
CUDA_CALLABLE_MEMBER ~Foo() {}
CUDA_CALLABLE_MEMBER void aMethod() {}
};
The reason for this is that only the CUDA compiler knows __device__ and __host__ -- your host C++ compiler will raise an error.
Edit:
Note __CUDACC__ is defined by NVCC when it is compiling CUDA files. This can be either when compiling a .cu file with NVCC or when compiling any file with the command line option -x cu.
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