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December 17, 2013

ArrayFire v2.0 Released

ATLANTA, Ga. Dec. 17 — Today we announce the release of ArrayFire v2.0, adding full commercial support for OpenCL devices including all AMD APUs and AMD FirePro graphics, Intel Xeon Phi coprocessors, CUDA GPUs from NVIDIA, and other OpenCL devices from Imagination, Freescale, ARM, Altera, and Apple. A complete list ArrayFire v2.0 updates and new features can be found in the product Release Notes.

ArrayFire is a CUDA and OpenCL library designed for maximum speed without the hassle of writing time-consuming CUDA and OpenCL device code. With ArrayFire’s library functions, developers can maximize productivity and performance. Each of ArrayFire’s functions has been hand-tuned by CUDA and OpenCL experts.

The library contains hundreds of functions for math, signal processing, image processing, and algorithms. Through its broad function set, nearly every engineering, science, or financial simulation can be accelerated today.

ArrayFire includes the innovative GFOR-loop, enabling all iterations of a FOR-loop to run simultaneously on CUDA and OpenCL devices. It also includes the notable Graphics Library for stunning data visualizations.

Major Updates and New Features

Announcing ArrayFire for OpenCL

  • Support for all of ArrayFire’s function library (with a few exceptions)
  • Same API as ArrayFire for CUDA enabling seamless interoperability
  • Just-In-Time (JIT) compilation of kernels for top performance
  • Specific tuning for Intel Xeon Phi coprocessors
  • Specific tuning for AMD APUs and AMD GPUs
  • Accelerated algorithms for image processing, signal processing, visualization, and more.

Updates to ArrayFire for CUDA

  • New signal and image processing functions
  • Faster transpose and matrix multiplication
  • Enhanced debugging support for GDB and Visual Studio
  • Better examples and documentation

About ArrayFire

ArrayFire launched in 2007 to commercialize GPU and accelerated libraries for scientists, engineers, and financial analysts, building the first and best platform for productivity in GPU computing. With advanced language processing and runtime technology to transform CPU applications to high performance GPU and accelerator codes, ArrayFire extends from desktop workstation performance to also fully leverage GPU and accelerator clusters. Based in Atlanta, Georgia, the privately held company markets ArrayFire for a range of defense, intelligence, biomedical, financial, research, and academic applications. Additional information is available at


source: ArrayFire

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