CODEWITHSUNDEEP
visual-studioqtopenglcudaopencl
eagle.dan.1349
eagle.dan.1349

Reputation: 631

Combining graphic-card and parallel-computation libraries in C++

I'm working on diploma project that heavily uses mathematical calculations and should present some results in 3D. For these purposes I decided to use CUDA or OpenCL for parallel computation of mathematical part and, most possibly, OpenGL for presenting result. In addition, project should be able to be deployed on clusters (operated by MS Windows), for these purposes project supervisor recommended MPI.

My question is the following: where it is easier to combine all these components, in MS Visual tudio

Main part is CUDA + OpenCL + OpenGL, it will be the core of the project.

P.S. This question is not to star holy-war betwen Qt and MS Visual studio.

Upvotes: 1

Views: 261

Answers (1)

datenwolf
datenwolf

Reputation: 162164

OpenCL is not limited to GPUs, it can be used for parallel programming in clusters as well. Intel for example provides a OpenCL implementation, that is aimed at multicore CPU and clusters.

So my recommendation is to use OpenCL for both GPU computing and clustering. MPI (Message Passing Interface) is mainly a way to communicate between tasks running on separate cluster nodes. It's not so much of a clustering framework by itself.

Upvotes: 2

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