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Comment by alain94040 | Hacker News Reader

According to [1], a high-end FPGA can do "AlexNet inference performance: int16 over 2,400 img/s, int8 over 4,500 img/s.". Plug in your favorite nVidia numbers and compare.

[1] http://mipsology.com/zebra.html

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Thank you very much for the link!

Hi Insru - how do you think GPUs would fare taking into consideration alain94040 's metrics?

Please look at this pdf: https://www.nvidia.com/content/tegra/embedded-systems/pdf/je... There is a table on page 9 and it claims, that Titan X can make 3216 img/s while TUL-KU115 FPGA board can make only >1000 img/s. This KU115 chip has a project price of ~$2000. Real time capability is nice, but that’s still expensive.

> This KU115 chip has a project price of ~$2000.

That seems odd - just the XCKU115-2FLVB2104E FPGA goes for $9000 on DigiKey.

Thanks for this PDF :)

Do you think TitanX has real time capability?

I am FPGA developer and have not much knowledge about GPUs. I just can make a guess, that no one can guarantee execution time on GPU. There are all little details well defined in FPGA design and result is always available after defined delay.

Though wouldn't it be far more interesting to compare the latencies at these rates, than the throughput? Roughly similar price and throughput, but very different energy efficiency and possibly latency could be rather significant for quite a few applications.

Xilinx has prepared some marketing material regarding latency: https://forums.xilinx.com/t5/Xcell-Daily-Blog/Xilinx-reVISIO...

For some reasons the Xilinx link is not opening.

Strange. It’s works here. Try this: https://www.xilinx.com/support/documentation/backgrounders/r...

Got it! Thanks :)

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