This round's TOP500 has an NVIDIA based machine -- a first. Here's a Gigaom posting on the topic. But is this news? I'm sure the folks at NVIDIA are happy about it.
I'm writing this posting after the opening evening of Supercomputing 2008. As usual, the TOP500 list has a way of grabbing attention and headlines, but I think the real news is the growing number of users that are actively considering production use of accelerators.
We are watching this carefully. Star-P is an excellent way for an organization to get started with accelerators as it provides a level of abstraction for the programmer. As one customer pointed out to me, 'the fastest accelerator crown is going to change often and may vary by application, we're going to want an easy way to port codes as the hardware changes.' What better way than to write the code in a very high level language like Matlab or Python and then place the accelerator specific code in function libraries?