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GPU: HPC Friend or Foe?

October 8, 2009 at 12:00 pm PST

General purpose computing with GPUs looks like a great concept on paper.  Indeed, SC’08 was dominated by GPUs — it was impossible not to be (technically) impressed with some of the results that were being cited and shown on the exhibit floor.  But despite that, GPGPUs have failed to become a “must have” HPC technology over the past year.  Last week’s announcements from NVIDIA look really great for the HPC crowd (aside from some embarrissing PR blunders) — they seem to address many of the shortcomings of prior generation GPU usage in an HPC environment: more memory, more cores, ECC memory, better / cheaper memory management, etc.  Will GPUs become the new hotness in HPC?

The obvious question here is “Why is Jeff discussing GPUs on an MPI blog?”

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Attaining High Performance Communications: A Vertical Approach

September 30, 2009 at 12:00 pm PST

It’s finally been published! 

I wrote a chapter on MPI in the book Attaining High Performance Communications: A Vertical Approach, edited by Dr. Ada Gavrilovska from the Georgia Institute of Technology.

 

Book picture: Attaining High Performance Communications: A Vertical Approach

The chapter author list reads like a who’s-who in high performance computing: several of my colleagues from the MPI Forum wrote pieces of this book, as well as many bright graduate students and other noted dignitaries in HPC.

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What is MPI?

September 25, 2009 at 12:00 pm PST

As I think most readers of this blog already know, when I say “MPI”, I mean “Message Passing Interface.”

I saw an confusing-and-amusing blog entry today over at insideHPC (and HPCwire): GigaSpaces and MPI Europe partner on financial messaging overseas

“MPI Europe?”, I thought.  “What’s that?  Is that some MPI-based ISV that I’ve never heard of?”

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Lies, damn lies, and statistics

September 15, 2009 at 12:00 pm PST

I’m a fan of InsideHPC; I read it every day.  I like John’s commentary; he does a great job of rounding up various newsworthy HPC-related articles.  But that doesn’t always mean that I agree with every posted item.  Case in point: I saw this article the other day, purportedly a primer on InfiniBand (referring to this HPCprojects article).  I actually know a bit about IB; I used to work in the IB group at Cisco.  Indeed, I’ve written a lot of OpenFabrics verbs-based code for MPI implementations.

There’s good information in that article, but also some fantastically unfounded and misleading marketing quotes:

  •  ”With large data transfers, Ethernet consumes as much as 50 per cent of the CPU cycles; the average for InfiniBand is a loss of less than 10 to 20 per cent.”  He’s referring to software TCP overhead, not Ethernet overhead.  There’s an enormous difference — there’s plenty of Ethernet-based technologies that are in the 10-20% overhead range.
  • “There are also power savings to be had, and this is critical when HPC facilities are confronting major issues with power supplies, cooling and costs. The same study indicates that InfiniBand cuts power costs considerably to finish the same number of Fluent jobs compared to Gigabit Ethernet; as cluster size increases, more power can be saved.”  Wow.  Other than generating warm fuzzies for customers (“My network products are green!”), what exactly does that paragraph mean?  And how exactly was it quantified?
  • …I’ll stop with just those 2.  :-)

These quotes are classic marketing spin to make IB products look the better than the competition.

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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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