AccelerEyes, today, announced the latest revision of their Jacket GPU programming platform for Matlab. Version 1.5 includes an expanded image processing library, additional core functionality [thanks to requests from the user community], enhancements to Jackets’ GFOR capability, performance enhancements across the platform, new digs for profiling apps and the ability to compile full M-code functions into individual GPU kernels.
“With this release of Jacket, AccelerEyes continues to demonstrate our leadership and focus on providing productivity and performance to MATLAB users interested in leveraging GPU technology,” said John Melonakos, CEO of AccelerEyes. “Since the initial introduction of Jacket in 2008, AccelerEyes has developed close working relationships with GPU programmers enabling us to continue to deliver the broadest and fastest function library,
advanced just-in-time compilation, and advanced memory management functionality. The MathWorks entering the GPU computing space validates the AccelerEyes decision to deliver solutions for MATLAB users. As this community evaluates the various solutions on the market, we are confident that all organizations will see the vast technical advantages of the Jacket platform over other alternatives.”
Two of the main features included in this release are as follows:
- GPROFILE: facilitates GPU and CPU profiling from the MATLAB console. GPROFILE records and reports on the time spent in MATLAB functions on the GPU and compares those results against comparable CPU timings. The results indicate sections of code that should or should not be run on the GPU as well as those that could benefit from vectorization or refactoring.
- GCOMPILE [et.al. ARRAYFUN]: enables Jacket programmers to define GPU kernels using M-code. Through this mechanism, Jacket is able to perform various additional optimizations, which it is otherwise unable to do in standard dynamic MATLAB mode.
For more info on the new goodies from AccelerEyes, check out their product docs here.