In this week, I investigated a little about Cuda C syntax, I know it's pretty much C, but it contains some new stuff that I think needed to be explained, so it would be easier to pass other language programs to CUDA in order to run them in the GPU. Also it's pretty much the only thing I can do with the GPU team, because I don't have a CUDA enabled GPU, anyway I'm planning to also do parallel programming stuff in other languages(python, java, [also I'm particularly interested a lot in Perl now because of this, I want to do something similar, but legal]).
Anyway my contributions to the wiki for the class were the following:
- CUDA Abstractions(Kernels, Threads[Grids and Blocks], Memory, Host and Device) with code, and CUDA Language Extensions, Function Type qualifiers, variable qualifiers, etc.
- Cuda C compiling guide in Linux, this is a small guide for compiling CUDA code (which doesn't require Nvidia graphic cards). So, because it is a guide and not information itself, I think it's better to post it here in my blog, and put a link in the wiki just in case somebody need it.
And in the laboratory:
And what I'm planning to do in a near future:
- Compile CUDA C code, to learn about common mistakes and what can I do. The area in which I can help is to learn the much I can the language extensions and other CUDA C stuff in case we need it.
- Parallel scipt in some language to copy something from webpages, like the Pirate Bay one, but legal.
My nomination of this week is again Isaias, because he told me that I can compile CUDA C code in my computer(but not run it), and also he made some CUDA C code about sum of arrays which is a pretty good advance.