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Sockets, cores, and hyperthreads… oh my!

October 15, 2010 at 5:00 am PST

Core counts are going up.  Cisco’s C460 rack-mount server series, for example, can have up to 32 Nehalem EX cores.  As a direct result, we may well be returning to the era of running more than one MPI process per server.  This has long been true in “big iron” parallel resources, but commodity Linux HPC clusters have tended towards the one-MPI-job-per-server model in recent history.

Because of this trend, I have an open-ended question for MPI users and cluster administrators: how do you want to bind MPI processes to processors?  For example: what kinds of binding patterns do you want?  How many hyperthreads / cores / sockets do you want each process to bind to?  How do you want to specify what process binds where?  What level of granularity of control do you want / need?  (…and so on)

We are finding that every user we ask seems to have slightly different answers.  What do you think?  Let me know in the comments, below.

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hwloc 1.0 released!

May 18, 2010 at 12:00 pm PST

At long last, we have released a stable, production-quality version of Hardware Locality (hwloc).  Yay!

If you’ve missed all my prior discussions about hwloc, hwloc provides command line tools and a C API to obtain the hierarchical map of key computing elements, such as: NUMA memory nodes, shared caches, processor sockets, processor cores, and processing units (logical processors or “threads”). hwloc also gathers various attributes such as cache and memory information, and is portable across a variety of different operating systems and platforms.

In an increasing NUMA (and NUNA!) world, hwloc is a valuable tool for high performance.

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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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SGE debuts topology-aware scheduling

January 23, 2010 at 12:00 pm PST

I just ran across a great blog entry about SGE debuting topology-aware scheduling.  Dan Templeton does a great job of describing the need for processor topology-aware job scheduling within a server.  Many MPI jobs fit exactly within his description of applications that have “serious resource needs” — they typically require lots of CPU and/or network (or other I/O).  Hence, scheduling an MPI job intelligently across not only the network, but also across the network and resources inside the server, is pretty darn important.  It’s all about location, location, location!

Particularly as core counts in individual server are going up. 

Particularly as networks get more complicated inside individual servers. 

Particularly if heterogeneous computing inside a single server becomes popular.

Particularly as resources are now pretty much guaranteed to be non-uniform within an individual server.

These are exactly the reasons that, even though I’m a network middleware developer, I spend time with server-specific projects like hwloc — you really have to take a holistic approach in order to maximize performance.

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Announcing hwloc: portable hardware locality open source software

September 13, 2009 at 12:00 pm PST

(this blog entry co-written by Brice Goglin and Samuel Thibault from the INRIA Runtime Team)

We’re pleased to announce a new open source software project: Hardware Locality (or “hwloc“, for short).  The hwloc software discovers and maps the NUMA nodes, shared caches, and processor sockets, cores, and threads of Linux/Unix and Windows servers.  The resulting topological information can be displayed graphically or conveyed programatically though a C language API.  Applications (and middleware) that use this information can optimize their performance in a variety of ways, including tuning computational cores to fit cache sizes and utilizing data locality-aware algorithms.

hwloc actually represents the merger of two prior open source software projects:

  • libtopology, a package for discovering and reporting the internal processor and cache topology in Unix and Windows servers.
  • Portable Linux Processor Affinity (PLPA), a package for solving Linux topological processor binding compatibility issues

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