New Product Updates - Jacket v1.8, LibJacket v1.1

John Melonakos Announcements, CUDA, Jacket Leave a Comment

Announcements Jacket v1.8 for MATLAB® now available LibJacket v1.1 for C/C++/Python/Fortran now available Request a FREE GPU computing consultation Introduction Enhance your code with the fastest, most comprehensive library for GPU computing: Jacket - the best GPU computing in MATLAB®.  Take a tour and compare! LibJacket - the best way to kick start your CUDA development.  Take a tour! Both products enable: Manipulating vectors, matrices, and ND arrays Support for single- and double-precision, boolean, real, and complex numbers Hundreds of routines for arithmetic, linear algebra, statistics, imaging, signal processing, and more (full list: Jacket, LibJacket) Thousands of lines of optimized code for any CUDA-capable GPU New Product Features Expanded support for the Signal Processing, Image Processing, and Statistics Libraries included with ...

Jacket Lectures - Learn and Teach GPU computing

John Melonakos Announcements, CUDA, Jacket Leave a Comment

We are pleased to share 6 in-depth Jacket lectures, helpful both in learning and teaching Jacket.  Download the lectures (PDF format), here: Jacket is used in course instruction at many universities around the world. Professors and course instructors use Jacket to provide engineering students with GPU acceleration of MATLAB® algorithms and to bring HPC to MATLAB courses. The six lectures are entitled "Parallel High Performance Computing with Emphasis on Jacket Based GPU Computing" and have topics including: Parallel computing introduction Jacket introduction Basic programming with Jacket Advanced programming with Jacket Multiple GPU programming Benchmarking If you are looking at accelerating MATLAB code or parallel computing with MATLAB, you definitely will want to add these lectures to your arsenal of ...

Getting More out of GPU Computing with LIBJACKET v1.0

John Melonakos Announcements, CUDA Leave a Comment

LIBJACKET v1.0 is here! It is the Matrix Companion to CUDA, providing a high-productivity performance layer for GPU computing. Download now to start a free 15-day trial. It integrates seamlessly with any CUDA code, but can also be used to avoid writing complicated GPU kernels yourself via its matrix interface. Soak up its features, here. We're celebrating this launch by offering two big promotions, one for existing Jacket programmers and one for the broader GPU computing community: Existing Jacket customers get 50% off libJacket. Buy a Tesla, Get a Free libJacket subscription. Learn more about these offers. Here are some other links of interest to this launch: Tour Documentation Function benchmarks Press release Over the years, we've been thrilled to ...

CUDA over Remote Desktop now available for Tesla GPUs

John Melonakos Announcements, CUDA 5 Comments

Update: Jacket over Remote Desktop is now available for Quadro devices too! Read this post. Jacket over Remote Connections is also documented extensively on the AccelerEyes Wiki. Over the past several years, many Jacket programmers have requested support for Remote Desktop in Windows.  We are pleased to report that recent NVIDIA drivers now enable Jacket to run over Remote Desktop, for some system configurations. Specifically, the requirements to make this work include: Windows Vista, Windows 7, Windows HPC Server 2008, or Windows HPC Server 2008 R2 The latest NVIDIA driver (as required by Jacket) Tesla GPU TCC-mode enabled on at least one (Tesla) GPU To enable TCC, the Tesla cannot be connected to a display. This means you need to ...

Jacket for MATLAB now available for NVIDIA Fermi!

ArrayFire Announcements 2 Comments

We are pleased to announce Jacket 1.4, with support for the latest NVIDIA graphics processing units based on the Fermi architecture (Tesla 20-series and GeForce GTX 4xx-series). NVIDIA's release of the Fermi architecture brings with it 448 computational cores, increased IEEE-754 floating-point arithmetic precision, error-correcting memory for reliable computation, and enhanced memory caching mechanisms. Highlights for Jacket 1.4 are as follows: Added support for the NVIDIA Fermi architecture (GTX400 and Tesla C2000 series) Jacket DLA support for Fermi Dramatically improved the performance of Jacket's JIT (Just-In-Time) compilation technology Operations involving random scalar constants do not incur a recompile Removed dependencies on MINGW and NVCC Logical indexing now supported for SUBSREF and SUBSASGN, e.g. B = A(A > x) MTIMES supports ...

Jacket accelerating life science and defense applications

John Melonakos Announcements, Case Studies Leave a Comment

With IBM’s decision this week to integrate Tesla technology into it’s high performance computing line, there should be no doubt that GP-GPU computing is more than a fad, organizations solving technical problems are able to do them more productively and efficiently than ever before with GPUs.  AccelerEyes’ customers are experiencing this first hand with the Jacket product family as they are able to quickly and easily implement new or existing algorithms for GPUs and accomplish their technical needs much faster with substantial speed improvements. Case in point, this week, AccelerEyes has released two case studies from customers that have used Jacket to transform their applications to GPU Computing with compelling results. System Planning Corporation has implemented two different radar processing ...

Torben's Corner

Gallagher Pryor Announcements Leave a Comment

We work very closely with our customers and really appreciate the feedback we receive and value the insight provided.  One Jacket programmer has started to post fantastic content on the Jacket Documentation Wiki under Torben's Corner. This content is maintained by Torben Larsen's team at AAU focusing primarily on outlining performance observations between GPUs and CPUs.  This information is not only of great value to our technical team but also valuable to the entire Jacket community.  Thanks Torben for this great resource!

New Website Launch

John Melonakos Announcements Leave a Comment

We are pleased to have released a new version of the AccelerEyes website today.  This new website delivers a richer level of content and is the result of the hard work by nearly everyone at AccelerEyes. And more is to come.  In the near future, we will be uploading new screencasts and demos showing Jacket in action.  We are also working on a comprehensive FAQ set of pages for product documentation.  Finally, we are receiving great demos and codes from current Jacket customers and will make these stories and examples available to you on the website. If you have suggestions for information that you'd like to see presented on our website, please let us know.  You can email these suggestions ...

Commentary on Jacket v1.1

John Melonakos Announcements Leave a Comment

I'm pleased to announce the release of Jacket v1.1!  This release represents a major milestone in Jacket's development and a great boost in functionality for Jacket customers.  The major feature of this release is the inclusion of new GPU datatypes, most notably double-precision.  We are very pleased with the performance we've seen for double-precision computations. At the time of this writing, the NVIDIA Tesla T10 series is the newest GPU on the market and NVIDIA's first in what will become a great line of double-precision enabled GPUs.  Even on this first double-precision generation card, we are seeing ~20x speedups for a lot of our examples and test cases. Of course, GPUs still give higher speedups when comparing single-precision GPU to ...


John Melonakos Announcements Leave a Comment

In an effort to keep people up-to-date with Jacket-related stuff, we are pleased to launch this new blog.  This blog will serve a few purposes: it is a place for things that don't really belong in the documentation, but still need a good explanation it is a place for announcements and updates Other sources of information include: The Jacket User Guide - Official Jacket documentation The Jacket Wiki - Online Jacket documentation The Jacket Forums - Online forums where users can post questions, bugs, experiences, feature requests, etc. We look forward to the launch of this blog and working with they community to make GPU MATLAB computing a valuable addition to your projects.