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Traffic in parallel

August 8, 2014 at 5:00 am PST

In my last entry, I gave a vehicles-driving-in-a-city analogy for network traffic.

Let’s tie that analogy back to HPC and MPI.

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Still more traffic

August 2, 2014 at 5:00 am PST

I periodically write about network traffic, and how general / datacenter network traffic analysis is related to MPI / HPC.

In my last entry, I mentioned how network traffic has many characteristics in common with distributed computing. Routing decisions, for example, are made independently at each network switch.

Consider if you were looking down at a city from above. Look at all the cars driving around the city streets. It’s chaos: each car/truck/bus/etc. makes its own routing decisions. Each one is a different size. Each one potentially goes in a different direction. Each one continually merges and splits from other traffic.

Yet somehow it all works.

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Traffic (redux)

July 28, 2014 at 10:44 am PST

I’ve written about network traffic before (see this post and this post). It’s the subject of endless blog posts, help forums, and instructional guides across the internet.

In a High Performance Computing (HPC) context, there are some fascinating aspects about network traffic that are fairly different than other types of network traffic.
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More traffic

May 4, 2010 at 12:00 pm PST

Traffic.  I find myself still thinking about my last entry today as I’m riding the blue line CTA from O’Hare airport to downtown Chicago for the MPI Forum meeting this afternoon.  Here I am, being spirited downtown at a steady clip on a commuter train while I see thousands of gridlocked cars on one side of me, and easily flowing motor vehicles on the other.  I will definitely reach downtown before the majority of vehicles that are only a few feet away from me on the Kennedy expressway, despite the fact that I’m quite sure that I left O’Hare long after they did.

Traffic is such a great network metaphor that is gives insight into today’s ramble: it’s well-understood that network packets may be delivered in a different order than which they were sent.  What’s less understood is why.

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Traffic

April 23, 2010 at 12:00 pm PST

Traffic.  It’s a funny thing.  On my daily drive to work, I see (what appear to be) oddities and contradictions frequently.  For example, although the lanes on my side of the highway are running fast and clear, the other side is all jammed up.  But a half mile later, the other side is running fast and clear, and my lanes have been reduced to half-speed.  A short distance further, I’m zipping along again at 55mph (ahem).

Sometimes the reasons behind traffic congestion are obvious.  For example, when you drive through a busy interchange, it’s easy to understand how lots of vehicles entering and exiting the roadway can force you to slow down.  But sometimes the traffic flow issues are quite subtle; congestion may be caused by a non-obvious confluence of second- and third-order effects.

The parallels from highway traffic to networking are quite obvious, but the analogy can go much deeper when you consider that modern computational clusters span multiple different networks — we’re entering an era of Non-Uniform Network Architectures (NUNAs).

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