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
Separation of Compute and Transfer from the rest of the code. Read More »
With the launch of twitter-channel @OpenCLonARM we now officially show a strong interest in ARM for compute. And we are not the only ones, as the twitter already has 80 followers (60 in 1.5 day and 12 retweets of the welcome-message). ARM has made tremendous progress in both technology and market-share. With ARM-64, companies like
StreamHPC flirts with ARM Read More »
There is a lot going on at the path to GPGPU 2.0 – the libraries on top of OpenCL and/or CUDA. Among many solutions we see for example Microsoft with C++ AMP on top of DirectCompute, NVidia (and more) with OpenACC, and now AccelerEyes (most known for their Matlab-extension Jacket and libJacket) with ArrayFire. I want you to
AccelerEyes ArrayFire Read More »
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
Theoretical transfer speeds visualised Read More »
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
Do your (X86) CPU and GPU support OpenCL? Read More »
In the OpenCL-code, you have run-time and compile-time of the C-code. It is very important to make this clear when you talk about compile-time of the kernel as this can be confusing. Compile-time of the kernel is at run-time of the software after the compute-devices have been queried. The OpenCL-compiler can make better optimised code
Basic concepts: Function Qualifiers Read More »
Intel, AMD and NVidia have all written implementations of the Black-Scholes algorithm for their devices. Intel has described a kernels in their OpenCL optimisation-document (page 28 and further) with 3 random factors as input: S, K and T, and two configuration-constants R and V. NVidia is easy to compare to Intel’s, while AMD chose to write down the
Black-Scholes mixing on SandyBridge, Radeon and Geforce Read More »
HTML5 is the future. Flash and Silverlight are leaving the market, clearing the way for HTML5 video. One big problem remains: protecting the content. Before you know it, the movie is on the free market. Could OpenCL video watermarking be the answer? DRM is only a temporary solution, and it often frustrates users who just
OpenCL potentials: Watermarked media for content protection Read More »
This article will be of interest if you don’t want to read the whole new specifications [PDF] for OpenCL 1.2. As always, feedback will be much appreciated. After many meetings with the many members of the OpenCL task force, a lot of ideas sprouted. And every 17 or 18 months a new version comes out of OpenCL to
Differences from OpenCL 1.1 to 1.2 Read More »
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
Basic Concepts: online kernel compiling Read More »