In “Separation of compute, control and transfer” I talked about node-wise programming as a method we should embrace instead of trying to unroll the existing loops. In this article I get into loops and discuss a few types and how they can be run in a parallel form. Dependency is the big variable in each type:

Say you have a device which is extremely good in numerical trigoniometrics (including integrals, transformations, etc to support mainly Fourier transforms) by using massive parallelism. You also have an optimised library which takes care of the transfer to the device and the handling of trigoniometric math. Then you find out that the strength of your company is

In the beginning of 2012 I spoke with Patrick Viry, former CEO of Ateji – now out-of-business. We shared ideas on GPGPU, OpenCL and programming in general. While talking about the strengths of his product, he came with a remark which I found important and interesting: separation of transfer. This triggered me to think further – those were the times

There are two overviews I use during my training, and I would like to share with you. Normally I write them on a whiteboard, but it has advantages having it in a digital form. Transfer speeds per bus The below image gives an idea of theoretical transfer speeds, so you know how a fast network

Does your computer have OpenCL-capable hardware? Read on and find out if your computer is compatible… If you want to know what other non-PC hardware (phones, tablets, FPGAs, DSPs, etc) is running OpenCL, see the OpenCL SDK page. For people who only want to run OpenCL-software and have recent hardware, just read this paragraph. If you have