Today’s blog post is by Nathan Hjelm, a Research Scientist at Los Alamos National Laboratory, and a core developer on the Open MPI project. The latest version of the “vader” shared memory Byte Transport Layer (BTL) in the upcoming Open MPI v1.8.4 release is bringing better small message latency and improved support for “zero-copy” transfers. NOTE: “zero copy” […]
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.
Today’s blog post is written by Joshua Ladd, Open MPI developer and HPC Algorithms Engineer at Mellanox Technologies. At some point in the process of pondering this blog post I noticed that my subconscious had, much to my annoyance, registered a snippet of the chorus to Paul Simon’s timeless classic “50 Ways to Leave Your […]
After years of discussion, the upcoming release of Open MPI 1.7.4 will change how processes are laid out (“mapped”) and bound by default. Here’s the specifics: If the number of processes is <= 2, processes will be mapped by core If the number of processes is > 2, processes will be mapped by socket Processes […]
The slides below are from my presentation at EuroMPI’13 about Open MPI’s flexible process affinity interface (in OMPI 1.7.2 and later). I described this system in a prior blog entries (one, two, three), but many people keep asking me about it. Josh Hursey from U. Wisconsin, LaCrosse, wrote this IMUDI paper about the interface (IMUDI […]
If you’re a bargain basement HPC user, you might well scoff at the idea of having more than one network interface for your MPI traffic. “I’ve got (insert your favorite high bandwidth network name here)! That’s plenty to serve all my cores! Why would I need more than that?” I can think of (at least) […]
In a prior blog post, I talked about latency analogies. I compared levels of latencies to your home, your neighborhood, a far-away neighborhood, and another city. I talked about these localities in terms of communication. Let’s extend that analogy to talk about data locality.
Multiple readers have told me that it is difficult for them to understand and/or visualize the effects of latency on their HPC applications, particularly in modern NUMA (non-uniform memory access) and NUNA (non-uniform network access) environments. Let’s breaks down the different levels of latency in a typical modern server and network computing environments.
