Capacity and speed requirements keep increasing for networking, but going from where are now to 100G networking isn’t a trivial matter, as Christopher Lameter and Fernando Garcia discussed recently in their LinuxCon Europe talk about the world of 100G networking. It may not be easy, but with recently developed machine learning algorithms combined with new, more powerful servers, the idea of 100G networking is becoming feasible and cost effective.
Lameter talked about the challenge of processing the massive amount of data generated by a 100G network. He says that “a 1500 bit packet takes 115 nanoseconds. There is no time for you to process that. You can get 60 of those maximum packets within the 10 microsecond window. You will never be able to process this stuff at full speed, so this means the existing mechanism that can compensate for this in the 10G timeframe must either become more sophisticated or you must find other ways to process this data.”
One thing making 100G possible now is hardware with processors like Intel Skylake and IBM Power8 that are capable of sustaining 100G to memory. In addition to server resources, Lameter mentioned that we have also development of a large amount of machine learning, artificial intelligence, and algorithms that can help process the data more quickly. There is also funding from the U.S. Department of Education for new developments in the computer industry with the intent to build a much more powerful supercomputer that can do an extra petaflop of computation.
Moving forward, 100G is maturing, but the software, including the operating system network stack needs to mature to handle these speeds. In particular, Lameter said that in addition to memory throughput, ongoing issues like proper APIs and deeper integration of cpu, memory, and IO are required to make 100G networking a reality.
For all of the technical details, including Garcia’s section on testing and measurement, watch the entire video of the talk.
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