Re:Graphics Chips Help Process Big Data Sets in Milliseconds
by digitailor on Sunday October 20, 2013 @01:28AM
(#6579025)
As you talk about your background more I'm getting where you're coming from. GPUs are obviously more powerful and capable for high-end graphics disregarding power efficiency. And if you're doing Hadoop big data your perspective makes more sense to me, because storage-centric applications really have no use for FPGAs. Maybe they'll be useful for querying one day, but they sure can't store large datasets. I get your point that FPGAs are not a universal panacea, but in the case of GPUs for supercomputing, and not graphics tasks, I think they are.
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Re:Graphics Chips Help Process Big Data Sets in Milliseconds
by cmccabe on Sunday October 20, 2013 @03:19AM
(#6579198)
In the past, GPUs weren't that practical for big data, since they offered a lot of CPU power, but not much in the way of I/O. It's possible that PCI-e 3.0 and 4.0 will change that, since they supposedly offer up to 15 GB/s and 31 GB/s bandwidth.
Big data is more than just querying. There are people running fancy machine learning algorithms. Those are the people most likely to use the flexibility of having a Java (or other programming language) interface.
I'm curious why you think FPGAs will win over GPUs in HPC. I struggle to imagine academics writing Verilog or VHDL. I can just barely see them sending in legions of grad students to try to write CUDA or OpenCL, but RTL design seems a bridge too far. I also haven't heard of any of the big FPGA companies trying to make a splash in HPC, whereas NVIDIA has been very active with Tesla and its other high-end offerings.