ArrayFire - CUDA Interoperability

Brian Kloppenborg ArrayFire, CUDA 2 Comments

Although ArrayFire is quite extensive, there remain many cases in which you may want to write custom kernels in CUDA or OpenCL. For example, you may wish to add ArrayFire to an existing code base to increase your productivity, or you may need to supplement ArrayFire's functionality with your own custom implementation of specific algorithms. Today's "Learning ArrayFire from scratch", blog post discusses how you can interface ArrayFire and CUDA.

Introduction to Vectorization in ArrayFire

Stefan 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.

Introduction to the ArrayFire array

Brian Kloppenborg ArrayFire Leave a Comment

The fundamental primitive of the ArrayFire Library is our container object, the array. As the next post in our blog series, "Learning ArrayFire from scratch", we will describe how to construct arrays, what datatypes arrays support, indexing, how to query an array for various properties (content, dimensions), and how to write mathematical expressions that involve arrays.

Learning ArrayFire from scratch: Installation

Brian Kloppenborg ArrayFire 9 Comments

Recently one of our interns completed his project ahead of schedule and asked if he could spend some time writing a particle filtering demo in ArrayFire for use at our upcoming trade shows. While learning the ins and outs of ArrayFire he posed several excellent questions which prompted us to start a series of blog posts entitled "Learning ArrayFire from scratch" that are geared to first-time users of our library. In today's post I will cover the installation process on Windows, Mac, and Linux. Our next post will discuss the basics of setting up your first ArrayFire project.