For engineers, the best learning approach is try to build something, no matter you familiar with it or not.
The thing I am trying to study is parallel programming. So here is CUDA. CUDA(Compute Unified Device Architecture) is developed by NVIDIA which makes use of GPU for parallel programming. That means a smartly programmed function can be divided into many threads for a GPU to run.
There are lots of interesting comparisons between CUDA and OpenCL, it seems that both of them are very popular. Is OpenCL suitable for all display cards? I will find out later.
For this week, I think I should at least setup a development environment for CUDA. Luckily, my laptop has configured a NIVIDA CUDA compatible display card (GeForce GT 740M, https://developer.nvidia.com/cuda-gpus). It is not a good one but seems can support CUDA.
Installing CUDA is easy, just need to download from https://developer.nvidia.com/cuda-downloads. I have upgraded just upgraded Windows 10, so I downloaded the Windows 8.1 package. But I made a mistake which costed me a day to fix. I shouldn't install Visual Studio 2015! I had to restart my laptop several times to complete the installation. The worst thing is CUDA doesn't support it. How come 2015 is not backward compatible? It works finally after I uninstalled Visual Studio 2015 and installed 2013 community version.
Ok. The development environment was ready. But I had no idea if it can work. So I followed some online tutorial available on youtube (https://www.youtube.com/watch?v=Ed_h2km0liI). Great, it worked. It seems not difficult. There is a good introduction on the net (http://geco.mines.edu/tesla/cuda_tutorial_mio/). As a beginner, I should read it through.
This is the report that generated by CUDA device query which is telling how weak my GPU is.
Note that the CPP source code is located at:
C:\ProgramData\NVIDIA Corporation\CUDA Samples\v7.0\1_Utilities\deviceQuery\
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