Which algorithms map is best to which accelerator? In other words: What kind of algorithms are faster when using accelerators and OpenCL/CUDA?
Professor Wu Feng and his group from VirginiaTech took a close look at which types of algorithms were a good fit for vector-processors. This resulted in a document: “The 13 (computational) dwarves of OpenCL” (2011). It became an important document here in StreamHPC, as it gave a good starting point for investigating new problem spaces.
The document is inspired by Phil Colella, who identified seven numerical methods that are important for science and engineering. He named “dwarves” these algorithmic methods. With 6 more application areas in which GPUs and other vector-accelerated processors did well, the list was completed.
As a funny side-note, in Brothers Grimm’s “Snow White” there were 7 dwarves and in Tolkien’s “The Hobbit” there were 13.
Continue reading “The 13 application areas where OpenCL and CUDA can be used”
Typos are a programmers worst nightmare, as they are bad for concentration. The code in your head is not the same as the code on the screen and therefore doesn’t have much to do with the actual problem solving. Code highlighting in the IDE helps, but better is to use the actual OpenCL compiler without running your whole software: an Online OpenCL Compiler. In short is just an OpenCL-program with a variable kernel as input, and thus uses the compilers of Intel, AMD, NVidia or whatever you have installed to try to compile the source. I have found two solutions, which both have to be built from source – so a C-compiler is needed.
In the series 
The earlier blog-post was about how to use Qt Creator with OpenCL. The examples are all around Images, but nowhere a simple Hello World. So here it is: 
