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Parallella: Low-Cost Linux Multi-Core Computing

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  • Parallella: Low-Cost Linux Multi-Core Computing

    Phoronix: Parallella: Low-Cost Linux Multi-Core Computing

    Parallella is an attempt to make Linux parallel computing easier and is advertised as a "supercomputer for everyone", but will it come to fruition?..

    http://www.phoronix.com/vr.php?view=MTIxNTQ

  • #2
    Sounds very interesting. I'd really like to try this as my NAS server which will also transcode some videos

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    • #3
      Thanks for the heads up.

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      • #4
        You keep using that word...

        Yeah... "Expected to be on the Parallella computer is a Zynq-7010 Dual-core ARM A9 CPU, an Epiphany Multi-core Accelerator, 1GB of RAM, USB 2.0 support, Gigabit Ethernet,"

        Supercomputing... you keep using that word. I do not think it means what you think it means.

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        • #5
          I imagine the readers here will like the detailed reference manuals.
          http://www.kickstarter.com/projects/...e/posts/323691

          There is also this which is a bit lighter to read http://www.adapteva.com/news/adaptev...ps-less-watts/

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          • #6
            Anyone tested galium3d on that thing?

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            • #7
              Originally posted by chuckula View Post
              Yeah... "Expected to be on the Parallella computer is a Zynq-7010 Dual-core ARM A9 CPU, an Epiphany Multi-core Accelerator, 1GB of RAM, USB 2.0 support, Gigabit Ethernet,"

              Supercomputing... you keep using that word. I do not think it means what you think it means.
              It is certainly a moving target. I remember Apple marketing some PowerPC computers with the term as well, but likely the best comparison we can bring up is in flops/W to actual current day supercomputers. Those seem to hover about 2.1Gflops/W (and that model is #1 of top500 as well). The Epiphany IV 64-core processor is advertised as 100Gflops (peak) with 2W power consumption (max), placing it at nearly 50Gflops/W; but obviously you need a power supply, memory and so on, so it's more appropriate to check the whole board. That has a quoted typical consumption of 5W, so if we bump that up by 2W, and then factor in a pessimistic 80% efficient power supply, we get 11.4Gflops/W. It's certainly in the ballpark, though you'd need thousands of them to make a true supercomputer. The base model (16 cores) has the same power consumption, so just divide by 4.

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              • #8
                I predict failure

                I don't see what this product is good for. Is it parallel computing just for the sake of it? 90 GFLOPS @ 5 watts is good I suppose, but it's not enough if you really need to do heavy calculations. In that case the 5 watts doesn't matter that much. Also, the 1 GB of RAM is a joke for anything but the most trivial tasks. Then what good is 64 cores?
                Speaking of 64 cores, few problems scale linearly with cores. This means that the actual performance will be way less than the theoretical 90 GFLOPS.
                This is a solution in search of a problem.

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                • #9
                  I guess you're going to be able to mine bitcoins with it quite efficiently.

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                  • #10
                    Originally posted by Staffan View Post
                    I don't see what this product is good for. Is it parallel computing just for the sake of it? 90 GFLOPS @ 5 watts is good I suppose, but it's not enough if you really need to do heavy calculations. In that case the 5 watts doesn't matter that much. Also, the 1 GB of RAM is a joke for anything but the most trivial tasks. Then what good is 64 cores?
                    Speaking of 64 cores, few problems scale linearly with cores. This means that the actual performance will be way less than the theoretical 90 GFLOPS.
                    This is a solution in search of a problem.
                    Something I can agree on; it is in search of problems. That's why we want it priced at a point where people start thinking about using it.

                    You're here apparently stating that there is a class "heavy calculations" consistently requiring more than 1GB RAM and where power is not an issue. I disagree with the implicit claim that this is the only set where a considerably parallel processor is an advantage; for instance, it rules out real-time low-latency video processing.

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