AccelerEyes invites you to participate in series of webinars designed to help you learn more about Jacket for MATLAB® and LibJacket for C/C++/Fortran/Python, a comprehensive library of GPU-accelerated functions. Joint Webinar With NVIDIA: LibJacket CUDA Library On October 20th we co-hosted a joint webinar with NVIDIA. During this well-attended event, our GPU computing experts provided a general product overview and usage of the LibJacket CUDA library. Several impressive demos of LibJacket in action were provided as well. LibJacket supports hundreds of GPU computing functions and programmers in numerous industries have been able to speedup applications. Be sure to check out the Q&A session included in the recorded webinar posted on NVIDIA’s Developer Zone. Thanks again to NVIDIA for co-hosting this informative webinar! GPU Programming for …
Filtering Benchmarks – OpenCV GPU vs LibJacket
OpenCV is one of the most popular computer vision toolkits, and over the last year they’ve been integrating more GPU processing into the core. One of the most common image processing tasks is convolution. Since LibJacket and OpenCV both support this, one of my coworkers rolled up his sleeves and benchmarked the latest versions from both libraries: OpenCV/CPU, OpenCV/GPU, LibJacket. Jump over to his personal website for the full benchmark results and source code. From the graphs, the GPU implementations from OpenCV and LibJacket both easily outperform the default CPU version in OpenCV, but notice that LibJacket pushes performance even further and dominates OpenCV’s GPU implementation, especially when using separable filters. We’ve worked really hard the last few years to …
Fast Computer Vision with OpenCV and ArrayFire
Update: While the post below discusses LibJacket (no longer a product), you can do the same thing in the newer, but different, ArrayFire library. Improved performance benchmarks and a simpler API are the results of moving from LibJacket to ArrayFire. Mcclanahoochie just posted some code and instructions for pairing OpenCV with LibJacket to get accelerated computer vision. You can do really fast image processing on video cam feeds too, see picture below: Really cool stuff. Computer vision is really hot with applications emerging in defense, radiology, games, automotive, and other consumer applications. Computer vision algorithms like these are also going mobile. For instance, we have started to build LibJacket for Mobile applications, which runs on Tegra, PowerVR, and other mobile …
New Product Updates – Jacket v1.8, LibJacket v1.1
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 …
Getting More out of GPU Computing with LIBJACKET v1.0
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 …
LIBJACKET on Amazon EC2 GPU Cloud Instances
Amazon recently added GPUs to their Elastic Compute Cloud. We decided to throw LIBJACKET into this GPU cloud to see how it would fare. The $2/hr pay-on-demand pricing is a great option for many Jacket programmers. This post is full of screenshots detailing the steps we took to get going with GPU computing in Amazon’s cloud: Sign up with Amazon EC2 Launch a GPU instance Login to the instance using ssh Setup the environment Download, build, and test LIBJACKET! Everything in this post applies equally well to running Jacket for MATLAB® on EC2. Simply install MATLAB + Jacket in your Amazon GPU instance and start working over ssh.