Researcher Shows How GPUs Make Terrific Network Monitors

alphadogg writes "A network researcher at the U.S. Department of Energy's Fermi National Accelerator Laboratory has found a potential new use for graphics processing units — capturing data about network traffic in real time. GPU-based network monitors could be uniquely qualified to keep pace with all the traffic flowing through networks running at 10Gbps or more, said Fermilab's Wenji Wu. Wenji presented his work as part of a poster series of new research at the SC 2013 supercomputing conference this week in Denver."

Comments

That's it?

[drcheap]

So in violation of /. convention, I went ahead and read TFA in hopes that were would actually be something more than "we solved yet another parallel computing problem with GPUs." Nope, nothing. Not even some useless eye candy of a graph showing two columns of before/after processing times.

And the article just *had* to be split into two pages because it would have killed them to include that tiny boilerplate footer on page one. What a fail...at least it wasn't a blatant slashvertisement!

Re:That's it?

[NothingMore]

I saw this poster at the conference and I was not impressed and in fact it was one of the weaker posters that I saw at the conference (it was light on details and had some of the information on the poster when talking about GPU's in general was not entirely accurate). It is really a poster that should not have been at SC at all. While it is interesting in the network sense the amount of data they can process is not anywhere close to the amount that is actually flowing through these large scale machines (up to 10 GB/sec per node) and there was no information about scaling this data collection (which would be needed at extreme scales) to obtain meaningful information to allow for tuning of network performance.

This poster should have been at a networking conference where the results would have been much more interesting to the crowd attending. Also of note, IIRC the author was using a traditional GPU programming model for computation that is not efficient for this style of computation. The speedup numbers would have been greatly improved by using a RPC style model of programming for the GPU (persistent kernel with tasking from pinned pages). However this is not something I totally fault the author for not using since it is a rather obscure programming technique for GPU's at this time.

Re:That's it?

[TeXMaster]

Yeah but with this kind of applications the real bottleneck is the fact that the discrete GPU needs to access data through the high-latency, low-bandwidth PCIe bus. For this kind of application, an IGP, even with the lower core counts, is often a much better solution, unless you manage to fully cover the host-device-host transfers with computations.

I'd be really curious to see this thing done in OpenCL on a recent AMD APU, exploting all the CPU cores and the IGP cores concurrently.