The 2013 GPU Technology Conference is just two weeks away. We’re super excited. We’re spending a lot of time preparing for our tutorial on CUDA Accelerated Image Processing Libraries. We think it will be well worth your while to attend. This is an 80-minute share all about CUDA image processing from James Malcolm, an AccelerEyes co-founder and lead engineer. You will walk away from the tutorial much better prepared to build fast computer vision and image processing codes. The session abstract is as follows: Image processing has consistently proven to benefit greatly from GPU acceleration. A number of libraries available from NVIDIA and AccelerEyes make image processing development efficient and lead to big speedups. Using these libraries can often significantly shorten …
Upcoming CUDA & OpenCL Training Courses
We’re pleased to announce upcoming CUDA and OpenCL training courses. Over the past couple of years, we’ve received numerous requests from around the world to be trained by AccelerEyes engineers. We finally got our act together and now have a nice schedule of CUDA and OpenCL training courses for 2013 within the United States: CUDA Feb 25-26, Houston, TX Mar 4-5, Baltimore/Washington D.C. Mar 25-26, Los Angeles, CA Apr 9-10, Seattle, WA Apr 15-16, San Francisco, CA May 6-7, Austin, TX May 27-28, Atlanta, GA Jun 10-11, Baltimore/Washington D.C. Jul 8-9, San Jose, CA Sep 2-3, Boston, MA Sep 23-24, Baltimore/Washington, D.C. Oct 7-8, Houston, TX Oct 21-22, Atlanta, GA Nov 4-5, Baltimore/Washington, D.C. Dec 2-3, New York, NY OpenCL …
ArrayFire Reception in France
As an engineers company, we spend a lot of time wrestling in the weeds of low-level GPU and accelerator codes. This is our battleground, and it can often be dizzying in its complexity. Our whole purpose is to hide that mess and tame those low-level beasts so that ArrayFire users get better performance than anyone else. The joy of ArrayFire comes when we get feedback from ArrayFire users, often from different parts of the world. For instance, the week I share excerpts from two recent emails we received in France: 1) From Barep, a French manufacturing company: “I think ArrayFire is a ‘must have’ library. It’s very easy to use and can be used under Linux and Windows. Personally, I’m happy …
Exciting Updates from AccelerEyes
We are pleased to announce today that MathWorks and AccelerEyes have started working together to provide the best overall solution for GPU computing in MATLAB® through the Parallel Computing Toolbox™ and MATLAB Distributed Computing Server™ from MathWorks. This new relationship will result in great product updates for end users of the Parallel Computing Toolbox™ and MATLAB Distributed Computing Server™. Since 2007, AccelerEyes has been a leader in developing GPU software, including Jacket. AccelerEyes has sold Jacket as a 3rd-party add-on to the MathWorks MATLAB® product. Effective today, AccelerEyes will discontinue new Jacket product sales. All existing Jacket license holders will continue to receive support and maintenance from AccelerEyes for 1 year. All existing Jacket licenses are perpetual and will not expire. Future GPU computing updates …
Jacket v2.3 Now Available
We are pleased to announce the new release of Jacket v2.3. This new version of Jacket brings even greater performance improvements through GPU computing for MATLAB® codes. (Click here to download v2.3) With v2.3, new support has been added for CUDA 5.0. This newer version of CUDA enables computation on the latest Kepler K20 GPUs of the NVIDIA Tesla product line. This morning we received an email from a Jacket user who said, “V2.3 + CUDA 5 = wow. Just upgraded and re-ran one of the routines that previously took just under 4 minutes – now less than 2 minutes!” This is a must-have release for all Jacket users. The performance improvements are generally felt across the board. Existing Jacket …
Image Processing with ArrayFire and OpenCV on the GPU
ArrayFire is a great way to supplement OpenCV for faster processing on the GPU. Mcclanahoochie recently posted an interactive demo showing the use of OpenCV with ArrayFire for computing Local Contrast Enhancement on the GPU from webcam video. Mcclanahoochie also shows how easy it is to convert OpenCV Mat images into ArrayFire GPU array images, as seen in the code snippit below: All the source code is available on Google Code, linked to from his website. Simply download ArrayFire and OpenCV and try it out for yourself!
Powering Mars Research
The Curiosity Mars rover landing reminded us of a recent talk by Brendan Babb of NASA and UAA in Anchorage about Jacket-accelerated Mars research. The talk was given at GTC 2012 in May. The main thrust of this research is improving mars rover image compression via GPUs and genetic algorithms. With Jacket and GPUs, the researchers were able to achieve 5X speedups on the larger data sizes. The algorithm works by pairing neighboring pixels with a random one and then adjusting the random pixel based on whether it incrementally improves the original image. Babb described the algorithm as an “embarrassingly” parallel process, ideally suited to GPU acceleration. He estimates he has been able to achieve a 20 to 30 percent error …
Parallelized Gene Predictors with Jacket
Researchers at the University of Quebec have developed high-performance gene predictors using Jacket to accelerated their MATLAB® code. This work has been published in BMC Research Notes and is freely available here. Computerized approaches to studying the human genome are challenged by the exploding amount of data, which doubles roughly every 6 months. In order to deal with this burgeoning datasets, demands for faster processing power continue to arise. This work focuses on predicting genes using frequency analysis with FFTs and with an equivalent technique known as Goertzel’s algorithm. In these applications, the emphasis of this paper is to propose tools to geneticists and molecular biologists for the prediction or identification of new genes using existing complementary strategies. The criteria for these …
AccelerEyes Celebrates 5 Years with New Product Releases
AccelerEyes just marked its 5th year in business. What better way to celebrate than by releasing new products! We are pleased to present ArrayFire v1.2 and Jacket v2.2 for NVIDIA CUDA-based GPUs. These new products support the latest Kepler architecture and include an array of new features and performance boosts, especially for image processing functions. Learn more in the ArrayFire release notes and Jacket release notes. AccelerEyes started up in 2007 with the mission to make productive performance accessible to engineers, scientists, and financial analysts. Our core leadership has been to provide great libraries that are easy-to-use and faster than alternative approaches. The coolest part about working at AccelerEyes is getting to play a part in the awesome projects of our …
Hiring Tons
Join the hottest GPU software company. We’re rapidly expanding and looking for talented developers who are passionate about making the programming world more efficient. The things we work on at AccelerEyes provide orders of magnitude more productivity for other developers, greatly increasing the amount of science, engineering, and analytics which are produced each year, across the globe, and across every technical computing industry. Specifically, we are looking to hire many developers in the following two roles: Application Engineering – the most vital job. It requires an ability to produce applications in a variety of disciplines, such as healthcare, finance, oil & gas, defense, etc). You will be the most expert users of ArrayFire and Jacket, and will spread your understanding …