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Princeton Researchers Announce Open Source 25-Core Processor (pcworld.com)

An anonymous reader writes: Researchers at Princeton announced at Hot Chips this week their 25-core Piton Processor. The processor was designed specifically to increase data center efficiency with novel architecture features enabling over 8,000 of these processors to be connected together to build a system with over 200,000 cores. Fabricated on IBM's 32nm process and with over 460 million transistors, Piton is one of the largest and most complex academic processors every built. The Princeton team has opened their design up and released all of the chip source code, tests, and infrastructure as open source in the OpenPiton project, enabling others to build scalable, manycore processors with potentially thousands of cores.

3 of 114 comments (clear)

  1. Re: How does technology sanctions work with this? by johnsmithperson123 · · Score: 4, Insightful

    Relax. In between architectural basis and the relatively low performance, it's insignificant. A few hundred million transistors for a 25 core chip in a day where your stock chip is multibillion in terms of transistor count.

  2. Re:massive parallel processing=limited application by Fwipp · · Score: 3, Insightful

    Chances are you're not content to watch video in 240p anymore.

  3. Re:massive parallel processing=limited application by godrik · · Score: 3, Insightful

    That is not really true. Most workloads can be executed in parallel. Pretty much all the field of scientific computing (would that be physics, chemistry, or biology) are typically quite parallel. If you are looking at database and data analytics, they are very parallel as well, if you are building topic models of the web, or trying to find correlation in twitter post, these things are highly parallel.

    Even on your machine, you are certainly using a fair amount of parallel computing, most likely video decompression is done in parallel (or it should be). It is the old argument that by decreasing frequency you can increase core count in the same power envelop while increasing performance.

    For sure, some applications are not sequential. Most likely, they are not the one we really care about. Otherwise, hire me, and I'll write them in parallel :)