Message-ID: <4DA676BB.4050501@2ndquadrant.com>
Date: Wed, 13 Apr 2011 21:23:23 -0700
From: Greg Smith <greg@2ndquadrant.com>
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To: Scott Carey <scott@richrelevance.com>
CC: Glyn Astill <glynastill@yahoo.co.uk>,
	Kevin Grittner <Kevin.Grittner@wicourts.gov>,
	"david@lang.hm" <david@lang.hm>, Steve Clark <sclark@netwolves.com>,
	"Joshua D. Drake" <jd@commandprompt.com>,
	Scott Marlowe <scott.marlowe@gmail.com>,
	"pgsql-performance@postgresql.org" <pgsql-performance@postgresql.org>
Subject: Re: Linux: more cores = less concurrency.
References: <C9CB1C26.30643%scott@richrelevance.com>
In-Reply-To: <C9CB1C26.30643%scott@richrelevance.com>
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Scott Carey wrote:
> If postgres is memory bandwidth constrained, what can be done to reduce
> its bandwidth use?
>
> Huge Pages could help some, by reducing page table lookups and making
> overall access more efficient.
> Compressed pages (speedy / lzo) in memory can help trade CPU cycles for
> memory usage for certain memory segments/pages -- this could potentially
> save a lot of I/O too if more pages fit in RAM as a result, and also make
> caches more effective.
>   

The problem with a lot of these ideas is that they trade the memory 
problem for increased disruption to the CPU L1 and L2 caches.  I don't 
know how much that moves the bottleneck forward.  And not every workload 
is memory constrained, either, so those that aren't might suffer from 
the same optimizations that help in this situation.

I just posted my slides from my MySQL conference talk today at 
http://projects.2ndquadrant.com/talks , and those include some graphs of 
recent data collected with stream-scaling.  The current situation is 
really strange in both Intel and AMD's memory architectures.  I'm even 
seeing situations where lightly loaded big servers are actually 
outperformed by small ones running the same workload.  The 32 and 48 
core systems using server-class DDR3/1333 just don't have the bandwidth 
to a single core that, say, an i7 desktop using triple-channel DDR3-1600 
does.  The trade-offs here are extremely hardware and workload 
dependent, and it's very easy to tune for one combination while slowing 
another.

-- 
Greg Smith   2ndQuadrant US    greg@2ndQuadrant.com   Baltimore, MD
PostgreSQL Training, Services, and 24x7 Support  www.2ndQuadrant.us
"PostgreSQL 9.0 High Performance": http://www.2ndQuadrant.com/books