Why 'Gaming' Chips Are Moving Into the Server Room

Esther Schindler writes "After several years of trying, graphics processing units (GPUs) are beginning to win over the major server vendors. Dell and IBM are the first tier-one server vendors to adopt GPUs as server processors for high-performance computing (HPC). Here's a high level view of the hardware change and what it might mean to your data center. (Hint: faster servers.) The article also addresses what it takes to write software for GPUs: 'Adopting GPU computing is not a drop-in task. You can't just add a few boards and let the processors do the rest, as when you add more CPUs. Some programming work has to be done, and it's not something that can be accomplished with a few libraries and lines of code.'"

Comments

Re:A whole new level of parallelism

[Chris Burke]

Programmers of Server applications are already used to multithreading, and they've been able to make good use of systems with large numbers of processors on them even before the advent of virtualization.

But don't pay too much attention to the word "Server". Yes the machines that they're talking about are in the segment of the market referred to as "servers", as distinct from "desktops" or "mobile". But the target of GPU-based computing isn't "Servers" in the sense of the tasks you normally think of -- web servers, database servers, etc.

The real target is mentioned in the article, and it's HPC, aka scientific computing. Normal server apps are integer code, and depend more on high memory bandwidth and I/O, which GPGPU doesn't really address. HPC wants that stuff too, but they also want floating point performance. As much floating point math performance as you can possibly give them. And GPUs are way beyond what CPUs can provide in that regard. Plus a lot of HPC applications are easier to parallelize than even the traditional server codes, though not all fall in the "embarrassingly parallel" category.

There will be a few growing pains, but once APIs get straightened out and programmers get used to it (which shouldn't take too long for the ones writing HPC code), this is going to be a huge win for scientific computing.