[Beowulf] NUMA info request

[kyron at neuralbs.com]

>
>
> Eric Thibodeau wrote:
>> Mark,
>>
>>    NUMA is an acronym meaning Non Uniform Memory Access. This is a
>> hardware constraint and is not a "performance" switch you turn on. Under
>> the Linux kernel there is an option that is meant to tell the kernel to
>> be conscious about that hardware fact and attempt to help it optimize
>> the way it maps the memory allocation to a task Vs the processor the
>> given task will be using (processor affinity, check out taskset (in
>> recent util-linux implementations, ie: 2.13+).
>>
>>    In your specific case, you would have 4Gigs per CPU and would want to
>> make sure each task (assuming one per CPU) stays on the same CPU all the
>> time and would want to make sure each task fits within the "local" 4Gig.
>>
>> Here is a link that should help you out with that respect:
>>
>> http://www.nic.uoregon.edu/tau-wiki/Guide:Opteron_NUMA_Analysis
>>
>
> For a more general (and detailed) discussion of NUMA,  you might be able
> for find some computer architecture books at the library where you are a
> grad student. Might be a little *too* much info, though.
>
> This text book is a popular comp. architecture text book. you might even
> say it's the "gold standard" I'm pretty sure it discusses NUMA somewhere
> in between it's covers.
>
> http://www.amazon.com/Computer-Architecture-Quantitative-Approach-Kaufmann/dp/1558605967

Indeed an excellent book but note that the 4th edition is out. I would
only recommend reading it if you need to decide between buying Intel
Itanium, Sun T1/2, Opteron , IBM P5, etc., processors and need to know the
the detailed architecture of your systems. You'll learn that Sun T1 is
incredibly fast...but only for integer use, not for floating point.

If you're only starting in HPC and want to do some parallel coding without
having the luxury of choosing your hardware, I strongly recommend
"Software Optimization for High Performance Computing: Creating Faster
Applications (HP Professional Series)". Even if it is a little dated
(2000), I find it to be an excellent reference for anyone getting into
HPC.

http://www.amazon.com/Software-Optimization-High-Performance-Computing/dp/0130170089

>
> Prentice Bisbal
> Linux Software Support Specialist/System Administrator
> School of Natural Sciences
> Institute for Advanced Study
> Princeton, NJ

Eric Thibodeau