NVIDIA Fall Driver Update (rel 180) and Other Treats

Tesla, CUDA, and the Future

We haven't been super excited about the applicability of CUDA on the desktop. Sure, NVIDIA has made wondrous promises and bold claims, but the applications for end users just aren't there yet (and the ones that are are rather limited in scope and applicability). But the same has not been true for CUDA in the workstation and HPC markets.

Tesla, NVIDIA's workstation level GPU computing version of its graphics cards (it has no display output and is spec'd a bit differently) has been around for a while, but we are seeing more momentum in that area lately. As of yesterday, NVIDIA has announced partnerships with Dell, Lenovo, Penguin Computing and others to bring desktop boxes featuring 4 way Tesla action. These 4-Tesla desktop systems, called Tesla Personal Supercomputers, will cost less than $10k US. This is an important number to come in under (says NVIDIA) because this is below the limit for discretionary spending at many major universities. Rather than needing to follow in the footsteps of Harvard, MIT, UIUC, and others who have built their own GPU computing boxes and clusters, universities and businesses can now trust in a reliable computing vendor to deliver and support the required hardware.

We don't have any solid specs on the new boxes yet. Different vendors may do things slightly differently and we aren't sure if NVIDIA is pushing for a heavily standardized box or will give these guys complete flexibility. But regardless of the rest of the box, the Tesla cards themselves are the same cards that have been available since earlier this year.

These personal supercomputers aren't going to end up in homes anytime soon, as they are squarely targeted at workstation and higher level computing. But that doesn't mean this development won't have an impact on the end user. By targeting universities through the retail support of their new partners in this effort, NVIDIA is making it much more attractive (and possible) for universities to teach GPU computing and massively parallel programming using their hardware. Getting CUDA into the minds of future developers will go a long way, not just for the HPC market, but for every market touched by these future graduates.

It's also much easier for an engineer to sell a PHB on picking up "that new Dell system" rather than a laundry list of expensive components to be built and supported either by IT staff or by the engineer himself. Making in roads into industry (no matter the industry) will start getting parts moving, expose more developers to the CUDA environment, and create demand for more CUDA developers. This will also help gently nudge students and universities towards CUDA, and even if the initial target is HPC research and engineering, increased availability of hardware and programs will attract students who are interested in applying the knowledge to other areas.

It's all about indoctrination really. Having a good product or a good API does nothing without having developers and support. The more people NVIDIA can convince that CUDA is the greatest thing since sliced bread, the closer to the greatest thing since sliced bread CUDA will become (in the lab and on the desktop). Yes, they've still got a long long way to go, but the announcement of partners in providing Tesla Personal Supercomputer systems is a major development and not something the industry (and especially AMD) should under appreciate.