Despite developer hassle, this is a great problem from the perspective of companies who are finding ways to tailor clean layers around complex code for heterogeneous computing. Take, for example, Atlanta-based AccelerEyes, which is seeing booming business because of the demand for GPU acceleration and interest in kicking the Xeon Phi co-processor tires.
<img style=”float: left;” src=”http://media2.hpcwire.com/hpcwire/OpenCL_logo.png” alt=”” width=”80″ height=”76″ />As the two major programming frameworks for GPU computing, OpenCL and CUDA have been competing for mindshare in the developer community for the past few years. Until recently, CUDA has attracted most of the attention from developers, especially in the high performance computing realm. But OpenCL software has now matured to the point where HPC practitioners are taking a second look.
The nascent GPGPU computing world received another boost today with the commercial release of Jacket 1.0, a GPU engine designed to accelerate computing and visualization for MATLAB users.