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Why 'Gaming' Chips Are Moving Into the Server Room

Posted by timothy on from the expense-report-manipulation-++ dept.

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.'"

3 of 137 comments (clear)

  1. A whole new level of parallelism by TwiztidK · · Score: 4, Insightful

    I've heard that many programmers have issues coding for 2 and 4 core processors. I'd like to see how they'll addapt to running "run hundreds of threads" in parallel.

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    1. Re:A whole new level of parallelism by Nadaka · · Score: 4, Insightful

      No it isn't. That you think so just shows how much you still have left to learn.

      I am not a high end programmer either. But I have two degrees on the subject and have been working professionally in the field for years, including optimization and parallelization.

      Many algorithms just won't have much improvement with multi-threading.

      Many will even perform more poorly due to data contention and the overhead of context switches and creating threads.

      Many algorithms just can not be converted to a format that will work within the restrictions of GPGPU computing at all.

      The stream architecture of modern GPU's work radically differently than a conventional CPU.

      It is not as simple as scaling conventional multi-threading up to thousands of threads.

      Certain things that you are used to doing on a normal processor have an insane cost in GPU hardware.

      For instance, the if statement. Until recently OpenCL and CUDA didn't allow branching. Now they do, but they incur such a huge penalty in cycles that it just isn't worth it.

    2. Re:A whole new level of parallelism by Dynetrekk · · Score: 5, Insightful

      Believe me, when you change the way you think about how an algorithm works, it doesn't matter if you are using 3 or 10000 processors.

      Have you ever read up on Amdahl's law?