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 …
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 …
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 …
AccelerEyes is Hiring at GTC 2012
Do you want to code GPUs daily? Do you want to build software that actually gets used by real people, solving real problems? Do you want to join the whirlwind of a startup where you own projects and determine success or failure? Then come work at AccelerEyes. AccelerEyes is hiring for 3 positions: Inside Salespersons, Fulltime Engineers, and Remote Contract Developers. Checkout our Careers page or swing by our booth at GTC for more info.
Top 10 List at GTC 2012
It’s going to be hard to sleep tonight. So much GPU goodness awaits the coming 3 days of the GPU Technology Conference. Here are my top 10 things to do at GTC 2012: Sessions to Attend #1: S0287 – Jacket for Multidimensional Scaling in Genomics – This is a great opportunity to learn about accelerating MATLAB® on the GPU. Come learn why thousands of scientists, engineers, and analysts are using Jacket to do more with less coding hassle. (Day: Tuesday, 05/15; Time: 5:30 pm – 5:55 pm; Location: Room K) #2: S0415 – An Accelerated Weeks Method for Numerical Laplace Transform Inversion – Learn how the researchers have been able to utilize Jacket in MATLAB® to more efficiently and robustly implement the Weeks method. (Day: Wednesday, 05/16; Time: 9:30 …
Jacket v2.1 Now Available
Optimization Library, Sparse Functionality, Graphics Library Improvements, CUDA 4.1 Enhancements, and much more… AccelerEyes announces the release of Jacket v2.1, adding GPU computing capabilities for use with MATLAB®. Jacket v2.1 delivers even more speed through a host of new improvements, maximizing GPU device performance and utilization.. Notable new features include an Optimization Library and additional functions to our Graphics Library. With Jacket v2.1, we have also extended support for sparse matrix subscripting and made improvements to host-to-device and device-to-host data transfer speeds for complex data. In addition, we have included various GFOR enhancements. Jacket v2.1 now includes NVIDIA CUDA 4.1 enhancements to provide improved functionality and performance (requires latest drivers). Jacket is the premier GPU software plugin for MATLAB®, better than alternative …
12,288 CUDA Cores in One Computer
Kepler is here. And it’s fantastic! The news came out today that the first Kepler GPU, the GeForce GTX 680, has been launched. A single GPU has 1,536 CUDA Cores. This means that those high-end workstations with 8 PCIe slots will be able to pack 12,288 CUDA cores into a single computer. That’s some serious computational power. Current high-end Fermi cards have 512 cores, so this new Kepler architecture boasts 3X the number of computation cores. Normally we focus on the higher-end Tesla products because those more aptly fit the needs of our science, engineering, and financial computing readers. But we are excited nonetheless by this GeForce GPU. It is a major step forward in GPU technology. And this GeForce card portends …
ArrayFire Support for CUDA 4.1
The question above comes from María (@turbonegra). She follows us @accelereyes. Many of you are wondering when ArrayFire support for new CUDA version 4.1 will be released. The answer: work is currently under way. CUDA 4.1 includes a new Fermi compiler, and many people in the GPU ecosystem have reported slowdowns from upgrading to the new CUDA version. So we’ve delayed releasing ArrayFire and Jacket support for CUDA 4.1 because we want to verify performance and reliability across all our unit tests, performance regressions, and customer code samples. Our tests sweep across various driver versions and everything from mobile GeForce cards through server-grade Tesla and Fermi chips. We are still working through the testing and verification at the moment. While …