Introduction to Vectorization in ArrayFire

Stefan Yurkevitch ArrayFire Leave a Comment

Programmers and Data Scientists want to take advantage of fast and parallel computational devices. One of the best ways of doing this is to write vectorized code; however, this is often easier said than done. In today’s continuation of the blog series “Learning ArrayFire from scratch“, we will discuss the various methods by which you can maximize the performance of your code by using ArrayFire’s built-in vectorization features.

Parallelized Gene Predictors with Jacket

John Melonakos Case Studies, CUDA Leave a Comment

Researchers at the University of Quebec have developed high-performance gene predictors using Jacket to accelerated their MATLAB® code.  This work has been published in BMC Research Notes and is freely available here. Computerized approaches to studying the human genome are challenged by the exploding amount of data, which doubles roughly every 6 months.  In order to deal with this burgeoning datasets, demands for faster processing power continue to arise. This work focuses on predicting genes using frequency analysis with FFTs and with an equivalent technique known as Goertzel’s algorithm.  In these applications, the emphasis of this paper is to propose tools to geneticists and molecular biologists for the prediction or identification of new genes using existing complementary strategies. The criteria for these …