lkoshale/cuda-smart-pointers

A simple wrapper on C++ smart pointers for CUDA

CUDA SMART POINTERS

A simple wrapper for std::unique_ptr and std::shared_ptr for GPU on CUDA.

How to build?

All definitions are in a single header file memory.cuh, you need to include it in your project. Test programs can be found at src/test/.

How to use?

#include "memory.cuh"
// creates a gpu pointer of type int* with 10 elements
// and returns a std::shared_ptr encapsulating it
auto sptr1 = cuda::shared<int>(10);
//or
std::shared_ptr<int> sptr2 = cuda::shared<int>(10);
{
	// returns std::unique_ptr
	auto uptr = cuda::unique<float>(100);
} // deallocation when out of scope

The header gives the following four functions to create valid GPU smart pointers:

1. auto ptr = cuda::shared<TYPE>(NUM_ElEMENTS) //std::shared_ptr
2. auto ptr = cuda::unique<TYPE>(NUM_ElEMENTS) //std::unique_ptr
3. auto ptr = cuda::unified_shared<TYPE>(NUM_ElEMENTS) //std::shared_ptr
4. auto ptr = cuda::unified_unique<TYPE>(NUM_ElEMENTS) //std::unique_ptr

1-2 creates pointers valid only on GPU, while 3-4 creates pointers valid on both CPU and GPU by using CUDA unified memory.

Sample Program

#include  <iostream>
#include  "memory.cuh"

int  main() {
// creates std::shared_ptr which hold GPU memory
auto ptr1 = cuda::shared<int>(1);
auto ptr2(ptr1);

// Returns the number of shared_ptr objects
// referring to the same managed object.
std::cout << "[4] ptr1 use count: " << ptr1.use_count() << std::endl;  // output: 2
std::cout << "[5] ptr2 use count: " << ptr2.use_count() << std::endl;  // output: 2

// Relinquishes ownership of ptr1 on the object
// and pointer becomes NULL
ptr1.reset();
std::cout << "ptr1 relinquishes ownership" << std::endl;
std::cout << "[6] ptr1 is " << ptr1.get() << std::endl	//output: 0x0000;
std::cout << "[7] ptr2 use count: " << ptr2.use_count() << std::endl; //output: 1

std::shared_ptr<int> ptr3;
{
   auto ptr4 = cuda::shared<int>(1);
   ptr3 = ptr4;
   std::cout << "[9] ptr3 use count: " << ptr3.use_count() << std::endl; //output: 2
   std::cout << "[10] ptr4 use count: " << ptr4.use_count() << std::endl; //ouput: 2
}// deallocates ptr4

std::cout << "[11] ptr3 use count: " << ptr3.use_count() << std::endl; //ouput: 1
return  0;
}

Building Test programs

Requirements:

1. CUDA and C++ (std:11)
2. CMake (3.8+)

Linux

In the directory "cuda-smart-pointers" run:

./build.sh

It will build the executables at ./build/src/test/ To Run the test programs:

# in directory cuda-smart-pointers
./build/src/test/app_name

where app_name can be any one of the following: unique, shared, unified_unique, unified_shared

Windows with msvc and CUDA

To Build the VS project:

1. Open cmake-gui and point the source code to ".../cuda-smart-pointers", and build and binaries to repository ".../cuda-smart-pointers/build".
2. Click "Configure"
3. Select your visual studio version
4. Click "Configure"
5. Click "Generate"

To Build and Run:

1. Open Project "Example.sln" in build directory
2. Right click the test app you want to run and click "Set as Startup Project"
3. Click "Build" from main menu, to build the project
4. Click "Debug"->"Start Without Debugging" to run and see the output.