You  ha ve parallelized your serial application ,  but as you use more cores you are  n o t seeing any improvement  in performance . What gives?

In this third and last article on OpenMP, we look at good OpenMP coding habits and present a short introduction to employing OpenMP with GPUs.

OpenACC directives can improve performance if you know how to find where parallel code will make the greatest difference.

The OpenACC data directive and its associated clauses allow you to control the movement of data between the host CPU and the accelerator GPU.

OpenACC is a great tool for parallelizing applications for a variety of processors.  In t his article , I  look at one of the most powerful directives,  loop .

The Joblib Python Library handles frequent problems – like parallelization, memorization, and saving and loading objects – in almost no time, giving programmers more freedom to push on with their core tasks.

Getting started in the HPC world requires learning to write parallel applications and learning to administer and manage clusters. We take a look at some ways to get started.

We take a close look at how to integrate graphics processors into your parallel programs with OpenCL.