by Douglas Eadline, Ph.D.
I was particularly impressed at how fast CUDA has gained traction in HPC and other areas. The CUDA wave has definitely hit the beach and I’ll have more on nVidia as the Fermi GPU begins to filter into the HPC trenches. In this column I want to talk about the other GPU language: OpenCL.

Before I launch into OpenCL background, I want make a prediction. I believe OpenCL will gain acceptance in much the same way nVidia CUDA has. Like CUDA, OpenCL has a freely available SDK (Software Development Kit), is based on the C language, and can be explored using low cost video hardware. OpenCL brings two other features to the table, however. These are open standard compliance and support for data-parallelism (GP-GPU) and task-parallelism (CPU) methods. I’ll take a closer look at these below, but first some background will be helpful.

Currently the GP-GPU competition is between AMD/ATI and nVidia. HPC at IBM was making some inroads with Cell, but has decided to switch to an OpenCL platform and presumably use AMD/ATI hardware. In addition, the much discussed Intel Larrabee never really made it out of the gate and now we are left with two main contenders, both of which have a strong desktop market to support development and production costs.

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