It’s that time again—we’re pleased to announce the release of our newest version of ArrayFire: ArrayFire v2.1. ArrayFire v2.1 is now bigger, faster, and stronger, thanks to some key function additions, API changes, feature improvements, and bug fixes. ArrayFire is a CUDA and OpenCL library designed for maximum speed without the hassle of writing time-consuming CUDA and OpenCL device code. With ArrayFire’s library functions, developers can maximize productivity and performance. Each of ArrayFire’s functions has been hand-tuned by CUDA and OpenCL experts. Major Updates Support for CUDA 6.0 Support for Mac OS X New language support (available on github) ArrayFire for Java ArrayFire for R! ArrayFire for Fortran* ArrayFire Extras on Github All language wrappers …
New Look, Same Acceleration Gang
We have officially rebranded from AccelerEyes to ArrayFire! Our rebranding includes a website redesign, improved documentation, and–bonus–an upcoming release of a new version of the ArrayFire software library. We have even more innovations waiting in the wings, and we are optimistic of a bright future under our new banner! Please don’t hesitate to contact us if you have any questions about this transition–we’re happy to help you find what you’re looking for and to assist in whatever ways we can. If you want faster code, you’ve come to the right place! -The ArrayFire Gang
ArrayFire-OpenGL Interop using CUDA
A lot of ArrayFire users have been interested in the usage of ArrayFire in partnership with OpenGL for graphics computation. In the long run, we do plan to expand further on the interoperablilty and make it easier through ArrayFire. For now, we have developed a small example to expand on the usage of the CUDA-OpenGL interop API to assist in the interop operations between ArrayFire and OpenGL. Some of the advantage of direct ArrayFire-OpenGL interop are: Faster data transfers: Since the OpenGL buffers as well as ArrayFire data reside on the GPU, we can use a direct device to device copy rather than using the CPU as an intermediate and the relatively slow PCIe interface. Offscreen rendering: It is commonly …
ArrayFire v2.0 Official Release
We are thrilled to announce the official release ArrayFire v2.0, our biggest and best product ever! ArrayFire v2.0 adds full commercial support for OpenCL devices including all AMD APUs and AMD FireProTM graphics, CUDA GPUs from NVIDIA, and other OpenCL devices from Imagination, Freescale, ARM, Intel, and Apple. ArrayFire is a CUDA and OpenCL library designed for maximum speed without the hassle of writing time-consuming CUDA and OpenCL device code. With ArrayFire’s library functions, developers can maximize productivity and performance. Each of ArrayFire’s functions has been hand-tuned by CUDA and OpenCL experts. Announcing ArrayFire for OpenCL Support for all of ArrayFire’s function library (with a few exceptions) Same API as ArrayFire for CUDA enabling seamless interoperability Just-In-Time (JIT) compilation of …
ARM Showcases ArrayFire OpenCL Support for Mali GPU at Supercomputing ’13
ARM showcased ArrayFire support for the Mali GPU at the Supercomputing ’13 conference recently held in Denver. This exciting development caught the attention of many attendees as they viewed the ArrayFire demos running in the ARM and AccelerEyes exhibits. Energy budgets are always constrained, and form an expensive component of any HPC system. ARM Mali GPUs provide the best performance and throughput for a given energy envelope. Partnering with ARM, AccelerEyes further reduces the cost of HPC by minimizing development time and costs. AccelerEyes offers the most productive software solutions for accelerating code using GPUs, coprocessors, and OpenCL devices. AccelerEyes delivers ArrayFire to accelerate C, C++, and Fortran codes on CUDA and OpenCL devices. ArrayFire customers come from a wide range …
Partners Magnify the SC13 Experience
Yesterday, we posted photos from our exhibit. Today was the last day of SC13, and we want to tip our hat to the wonderful partners that magnified our SC13 experience. Creative Consultants, Mellanox, and Allinea Creative Consultants ran an ArrayFire demo across several nodes using Mellanox interconnect. The demo was a multi-node, multi-GPU lattice boltzmann simulation. Allinea also showcased their debugging and profiling tools on the same ArrayFire based code. AMD ArrayFire OpenCL demos were showcased in the AMD exhibit. It was great to see momentum from AMD at SC13 carried over from the previous week’s APU13 conference. Microway In the photo below, you can see ArrayFire running on Microway’s WhisperStation. Microway had prime real estate at the conference and surely every …
Photos from SC13
SC13 was awesome this week! Tomorrow is the last day of the exhibition. For those of you that did not make it to the show, here are some pictures from our exhibit: The AccelerEyes Booth ——————————————————————————————————– ArrayFire OpenCL Demo on ARM Mali ——————————————————————————————————– ArrayFire CUDA Demo on NVIDIA K40 ——————————————————————————————————– ArrayFire OpenCL Demo on Intel Xeon Phi Coprocessor ——————————————————————————————————– ArrayFire OpenCL Demo on AMD FirePro GPU ——————————————————————————————————– It was a great show and wonderful to see so many ArrayFire users in person. If you could not attend and would like to learn more about our CUDA or OpenCL products or services, let us know! Related articles ArrayFire v2.0 Release Candidate Now Available for Download Two Kinds of Exhibits to Watch …
APU 2013 – Day 3 Recap
Big announcement here at #APU13! AMD CTO, Mark Papermaster, just announced 2 additions to the 2014 Mobile APU roadmap http://t.co/sWHMhb9AAe — AMD (@AMD) November 13, 2013 Today was the final day of AMD’s APU 2013 conference. The theme of today was mostly focused on gaming topics, so it was not as relevant to technical computing as yesterday. However, the mobile product announcement from AMD in the tweet above was interesting. OpenCL is just as important in mobile computing as it is in HPC computing. Both ends of the spectrum have a need for speed and can achieve it through great data parallelism. AMD is looking to make better inroads into mobile computing with these APU announcements. Overall, APU 2013 was a fantastic …
APU 2013 – Day 2 Recap
Today was the first full day of AMD’s APU 2013 conference. It was a whirlwind of heterogeneous computing. From the morning keynotes, three particular salient points stuck out to us: Mike Muller, CTO at ARM, talked about heterogeneous computing. He said it nicely with, “Heterogeneous computing is the future. It has also been our past, but we didn’t notice because a few shiny companies overshadowed everything else.” That is a great way to describe it. The future of heterogeneous computing involves the rise in importance of non-x86 processors. Throwing a few more MHz onto a CPU no longer is capable of satiating computational demands. Nandini Ramani, VP at Oracle, talked about the importance of Java for heterogeneous computing. She pointed …
APU 2013 – Day 1 Recap
AMD’s APU 2013 kicked off today with keynotes and a welcome reception. The developer summit is themed as the epicenter of heterogeneous computing. AMD has a world class CPU and a world class GPU and is pushing the industry forward by combining both of those devices into the same chip, the APU. AMD’s APUs are programmable via OpenCL, the industry standard for heterogeneous development. AMD is also leading the way with standards for Heterogeneous System Architecture (HSA). APU13 will have many technical sessions, keynotes, and demos around OpenCL and HSA. We are at the APU conference demoing ArrayFire acceleration on two of AMD’s newest hardware offerings: A machine with the latest AMD Radeon R9 209X discrete GPU A machine with the …