In case you missed it, we recently held an ArrayFire Webinar, focused on exploring the tradeoffs of OpenCL vs CUDA. This webinar is part of an ongoing series of webinars held each month to present new GPU software topics as well as programming techniques with Jacket and ArrayFire. For those of you who missed it, we provide a recap here. Lots of questions were fielded by our team, so it’s a must-watch. We hope to see you at the next one! Recap Download the slides. Here is a transcript of the content portion of the webinar: AccelerEyes is pleased to present today’s ArrayFire webinar looking at OpenCL and CUDA Trade-offs and Comparisons. Everyday, we interact with many programmers in various stages of GPU …
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 …
Jacket v2.0 Now Available
New Multi-GPU functionality , added support for OpenCL devices, and much more… AccelerEyes announces the release of Jacket version 2.0, adding GPU computing capabilities for use with MATLAB®. Version 2.0 delivers even more speed through a host of new improvements, maximizing GPU device performance and utilization. Notable new features include a multi-GPU interface and support for OpenCL devices. With Jacket v2.0, your M-code is now portable across all major GPU devices, including AMD/ATI, Intel, and NVIDIA chips. Jacket is the premier GPU software plugin for MATLAB®, better than alternative solutions. It is relied upon by thousands of organizations for rapid prototyping and problem solving across a range of government, manufacturing, energy, media, biomedical, financial, and scientific research applications. Multi-GPU Details: …
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: …
NVIDIA Fermi with CUDA and OpenCL
In December of 2008, we did a blog post answering questions from customers and prospects about the use of OpenCL for Jacket. If you have not reviewed that blog post to gain some insight into our progress you can access it here – http://blog.accelereyes.com/blog/2008/12/30/opencl/. Some things have changed since that original post. For example, NVIDIA now provides an OpenCL driver, toolkit, programming guide, and SDK examples. Given the new tools available and the new Fermi hardware, we ran some tests on the Tesla c2050 to compare OpenCL performance to CUDA performance. The Tesla C2050 is an amazing beast of a card, providing upto 512 Gigaflops of double precision arithmetic (at peak). Before we present the benchmarks, we should comment on …
OpenCL
We often get questions such as the one we just received via email: 1) Any idea if you will be supporting AMD/ATI cards in future ? 2) Have you considered OpenCL as a potential pathway for the future ? I can see an advantage there for you (if it takes off) in that you’re not tied to a single vendor any more and potentially you’d be able to take advantage of other accelerators that may support it. It’s very early days yet but certainly from our point of view the current paradigm of code to a single vendors card doesn’t seem sustainable.. OpenCL is a community effort to create a standard for parallel computing, with early emphasis on GPGPU computing, …