April 24, 2017 Nicole Hemsoth
In high performance computing, machine learning, and a growing set of other application areas, accelerated, heterogeneous systems are becoming the norm.
With that state come several parallel programming approaches; from OpenMP, OpenACC, OpenCL, CUDA, and others. The trick is choosing the right framework for maximum performance and efficiency—but also productivity.
There have been several studies comparing relative performance between the various frameworks over the last several years, but many take two head to head for compares on a single benchmark or application. A team from Linneaus University in Sweden took these comparisons a step further by developing a custom tool …Read more