CUDA_CALLABLE_MEMBER 是一个常见的宏定义,通常用于声明在 CUDA 编程中既可以在 设备端 (device) 又可以在 主机端 (host) 调用的函数。它通过组合 CUDA 的关键字 __host__ 和__device__ 来实现 机制:为主机和设备分别编译代码 并不是所有主机代码在设备上都能运行。例如,使用标准库函数(如 std::vector 或...
You probably want to define a macro like #ifdef__CUDACC__#defineCUDA_CALLABLE_MEMBER __host__ __device__#else#defineCUDA_CALLABLE_MEMBER#endif Then use this macro on your member functions classFoo{public: CUDA_CALLABLE_MEMBERFoo(){} CUDA_CALLABLE_MEMBER ~Foo() {} CUDA_CALLABLE_MEMBERvoid...
hemi::launchcan also be used to portably launch function objects (orfunctors), which are objects of classes that define anoperator()member. To be launched on the GPU, theoperator()should be declared withHEMI_DEV_CALLABLE_MEMBER. To make this easy, Hemi 2 provides the convenience macroHEMI_...
To be launched on the GPU, the operator() should be declared with HEMI_DEV_CALLABLE_MEMBER. To make this easy, Hemi 2 provides the convenience macro HEMI_KERNEL_FUNCTION(). The simple example hello.cpp demonstrates its use:HEMI_KERNEL_FUNCTION(hello) { printf("Hello World from thread %d ...
今天这个部分讲完后，下期将开始讲解 Texture and Surface Memory 3.2.9. Error Checking All run...
For additional information, you can also watch our talk about grCUDA, “Simplifying NVIDIA GPU Access: A Polyglot Binding for GPUs with GraalVM“. References [Ester et al. 1996] Martin Ester, Hans-Peter Kriegel, Jörg Sander, Xiaowei Xu:A density-based algorithm for discovering clusters a de...
2.7.2. CUDA Libraries 2.7.2.1. CUBLAS ‣ In addition to the usual CUBLAS Library host interface that supports all architectures, the CUDA toolkit now delivers a static CUBLAS library (cublas_device.a) that provides the same interface but is callable from the device from within kernels....
We have a material_type member to keep track of what type of material the object is to which scatter() to call. scatter() delegates its work to one of the xxx_scatter() functions. __device__ is a CUDA directive that indicates the function is callable on the CUDA device. On the ...
classFoo{public: CUDA_CALLABLE_MEMBERFoo(){} CUDA_CALLABLE_MEMBER ~Foo() {} CUDA_CALLABLE_MEMBERvoidaMethod(){} }; The reason for this is that only the CUDA compiler knows__device__and__host__-- your host C++ compiler will raise an error....
bpl-subset/bpl_subset/libs/python/src/object/class.cpp: In static member function ‘static void* pycudaboost::python::instance_holder::allocate(PyObject*, std::size_t, std::size_t)’: /usr/include/python3.11/object.h:145:30: error: lvalue required as left operand of assignment ...