In case you missed it, we recently held a webinar on the ArrayFire GPU Computing Library. This webinar was part of an ongoing series of webinars that will help you learn more about the many applications of ArrayFire, while interacting with AccelerEyes GPU computing experts. ArrayFire is the world’s most comprehensive GPU software library. In this webinar, James Malcolm, who has built many of ArrayFire’s core components, walked us through the basic principles and syntax for ArrayFire. He also provided an overview of existing efforts in GPU software, and compared them to the extensive capabilities of ArrayFire. For example, the same application that takes 26 lines to write in Thrust, can be coded up in just 3 lines in ArrayFire! ArrayFire has supported …
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 …
ArrayFire Examples and Benchmarks Whitepaper
What do you get when you offer the world’s most comprehensive GPU library available for free? Excited users who go the extra mile and give back to the community. Andrzej Chrzȩszczyk from Jan Kochanowski University recently wrote an awesome whitepaper, entitled “Matrix Computations on the GPU with ArrayFire for Python and C/C++.” The whitepaper contains many GPU computing tutorial examples as well as performance timings for each example. Andrzej notes, “The purpose of this document is to make the first steps in using modern graphics cards to general purpose computations simpler.” This document is especially beneficial for programmers looking to accelerate Python or C/C++ codes. We thank Andrzej this fine contribution to the ArrayFire community. His documentation on ArrayFire will be beneficial to all …
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 …
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 …
AccelerEyes Webinar Series
AccelerEyes invites you to participate in series of webinars designed to help you learn more about Jacket for MATLAB® and ArrayFire for C/C++/Fortran/Python, a comprehensive library of GPU-accelerated functions. GPU Programming for Medical Image Segmentation: January 18, 2012 at 3:00 p.m. EST There’s a huge volume of data generated using acquisition modalities like computer tomography (CT), magnetic resonance imaging (MRI), positron emission tomography or nuclear medicine. A common need is to manipulate and transmit this data using compression techniques in as little time as possible. During this webinar we will show Jacket’s superior speed and handling volumes from subscripting to convolutions. Come and learn how to accelerate common medical imaging applications using an easy, powerful programming library with Jacket for MATLAB®. OpenCL and CUDA Trade-Offs and Comparison: February 15, 2012 at …
AccelerEyes Releases ArrayFire GPU Software
A free, fast, and simple GPU library for CUDA and OpenCL devices. AccelerEyes announces the launch of ArrayFire, a freely-available GPU software library supporting CUDA and OpenCL devices. ArrayFire supports C, C++, Fortran, and Python languages on AMD, Intel, and NVIDIA hardware. Learn more by visiting the ArrayFire product page. “ArrayFire is our best software yet and anyone considering GPU computing can benefit,” says James Malcolm, VP Engineering at AccelerEyes. “It is fast, simple, GPU-vendor neutral, full of functions, and free for most users.” Thousands of paying customers currently enjoy AccelerEyes’ GPU software products. With ArrayFire, everyone developing software for GPUs has an opportunity to enjoy these benefits without the upfront expense of a developer license. Reasons to use ArrayFire: …