VUDA

VUDA is a header-only library based on Vulkan that provides a CUDA Runtime API interface for writing GPU-accelerated applications.

Setup

The only requirements for developing with the VUDA library is to have access to a Vulkan compatible system and install the Vulkan SDK.

To compile a c++17 program (x64) using the VUDA library it is necessary to specify:

• the path to the VUDA header file
• the path to the Vulkan SDK header files
• the path to the Vulkan SDK library files and add the additional library dependency

Running a sample

Each sample accompanying the VUDA library includes a simple Makefile for compilation with g++. Simply set the path to the sample folder and run make. Additionally, some of the samples includes an equivalent cuda version (for quick comparison). To compile cuda source code, install the cuda toolkit.

Usage

#include <vuda.hpp>

int main(void)
{
    // assign a device to the thread
    vuda::setDevice(0);
    // allocate memory on the device
    const int N = 5000;
    int a[N], b[N], c[N];
    for(int i = 0; i < N; ++i)
    {
        a[i] = -i;
        b[i] = i * i;
    }
    int *dev_a, *dev_b, *dev_c;
    vuda::malloc((void**)&dev_a, N * sizeof(int));
    vuda::malloc((void**)&dev_b, N * sizeof(int));
    vuda::malloc((void**)&dev_c, N * sizeof(int));
    // copy the arrays a and b to the device
    vuda::memcpy(dev_a, a, N * sizeof(int), vuda::memcpyHostToDevice);
    vuda::memcpy(dev_b, b, N * sizeof(int), vuda::memcpyHostToDevice);
    // run kernel (vulkan shader module)
    const int stream_id = 0;
    const int blocks = 128;
    const int threads = 128;
    vuda::launchKernel("add.spv", "main", stream_id, blocks, threads, dev_a, dev_b, dev_c, N);
    // copy result to host
    vuda::memcpy(c, dev_c, N * sizeof(int), vuda::memcpyDeviceToHost);

    // do something useful with the result in array c ...    
    
    // free memory on device
    vuda::free(dev_a);
    vuda::free(dev_b);
    vuda::free(dev_c);
}

Compile flags

Flag	Comment
VUDA_STD_LAYER_ENABLED	Enables the std vulkan layer
VUDA_DEBUG_ENABLED	Enables run-time exceptions

Change Log

Date	Changes
15/10/2019	internal state and memory allocation improvements, shared memory sample
20/12/2018	data structure for managing descriptor set and command buffer pool allocations
25/11/2018	Makefiles and gcc conformity
13/11/2018	virtual alloc for local device mem, one buffer per mem alloc, vuda::events, sync memcpy conformity, bandwidthtest, julia set
25/10/2018	memory allocator introduced: mallocHost, hostAlloc, optimized memory transfers, (comparable speeds with cuda in simple vector addition)
17/10/2018	kernel interface updated: kernel specialization, arbitrary arguments
06/10/2018	initial commit