To temporarily increase capacity we put Quartus 16.0.2 on an Ubuntu server, which did not go smooth – but at least smoother than upgrading packages to required versions on RedHat/CentOS. While the download says “Linux” and you’re expecting support for multiple Linux breeds, there is only official support for Redhat 6.5 (and CentOS). Luckily it

One of the world’s most used software is far from performance optimised and there is hardly anything we can do about it. I’m talking about Excel. There are various engine replacements which promise higher speeds, but those have the disadvantage that they’re still not fast enough with really heavy calculations. Another option is to use much faster

We’re going online with our presentations and tutorials. This makes it easy to reach more people and make our trainings more flexible. We’re starting with short introductory trainings, but we have bigger plans. Keep an eye on our events (shared on Twitter, LinkedIn, this blog and the newsletter) to see what the offerings are. And you’re very

In the past years we have been translating several types of software to AMD, targeting OpenCL (and HSA). The main problem was that manual porting limits the size of the to-be-ported code-base. Luckily there is a new tool in town. AMD now offers HIP, which converts over 95% of CUDA, such that it works on

The information you find everywhere: on Linux the current “radeon” and “fglrx” are being replaced by AMDGPU (graphics) and ROCm (compute) for HSA-enabled GPUs. As the whole AMD Linux driver team is seemingly working on getting the new and open source drivers ready, fglrx is now deprecated and will not get updates (or very late).

The CUDA page on Wikipedia includes a table listing Compute Capabilities. While verifying support for AMD Fiji GPUs, such as the Radeon Nano and FirePro S9300 X2, I became curious about how much functionality is still missing in OpenCL. After comparing the feature sets, I found that Fiji GPUs support all the required functionality. Read

From 24 to 28 October we give a 4-day training on OpenCL-on-FPGAs using Altera hardware. The learning goals are correctly writing OpenCL code for FPGAs, learning to work with Quartus and understanding the important optimisation techniques. The total costs are €2760 excluding VAT for the whole week ( 2 + 2 days of training, one pause day), including

When we port software to the GPU or FPGA, testability is very important. A part of making the code testable, is getting its functionality fully under control. And you guessed already that run-time generated random numbers takes good attention. In a selection of past projects random numbers were generated on every run. Statistically the simulations were more correct,