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Xilinx Moving Ahead With Plans To Upstream Their Alveo PCIe Accelerator Driver

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  • Xilinx Moving Ahead With Plans To Upstream Their Alveo PCIe Accelerator Driver

    Phoronix: Xilinx Moving Ahead With Plans To Upstream Their Alveo PCIe Accelerator Driver

    A few weeks back I wrote about Xilinx looking at contributing their Alveo FPGA accelerator drivers to the mainline Linux kernel. They are continuing to work on that goal and pushed out their latest kernel driver patches this week for these Alveo PCIe accelerator cards...

    http://www.phoronix.com/scan.php?pag...Driver-Patches

  • #2
    Cool, any perf numbers for these cards?

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    • #3
      At $13k for the 280, I'm not sure how it stacks against a bunch of GPUs in total performance.
      < 50TOPS for INT8 is lower than a Volta V100 doing FP16 in tensor units.
      Either way, It is an interesting solution when transforming data from from the QSFP:s directly to PCIe4.0 or vice versa.

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      • #4
        Originally posted by andrei_me View Post
        Cool, any perf numbers for these cards?
        What performance numbers are you looking for?
        Quantifying the performance of an FPGA is at best ballpark figures...
        Hard numbers are easier. 2*100G QSFP-interfaces, Ultra fast HBM2 or DDR4 memory.
        Very fast internal SRAM-access. A lot of LUTs to play with. ~200W power envelope.

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        • #5
          Originally posted by milkylainen View Post

          What performance numbers are you looking for?
          Quantifying the performance of an FPGA is at best ballpark figures...
          Hard numbers are easier. 2*100G QSFP-interfaces, Ultra fast HBM2 or DDR4 memory.
          Very fast internal SRAM-access. A lot of LUTs to play with. ~200W power envelope.
          I think I can speak for everyone when I say it, Crysis.

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          • #6
            Originally posted by andrei_me View Post
            Cool, any perf numbers for these cards?
            Performance of FPGA depends from how good the configuration of the FPGA is for your specific workload as that's the whole point of this hardware, reconfiguring the hardware itself to make an "hardware accelerator" for your specific task.

            So it's very situational, but they are a thing in computing as they can do usually better than GPUs, while being more expensive and requiring someone to write a configuration for the thing first.

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