Optimizing Time Series Access

I am looking for advice on dealing with large tables of environmental model
data and looking for alternatives to my current optimization approaches.
Basically, I have about 1 Billion records stored in a table which I access
in groups of roughly 23 Million at a time. Which means that I have
somewhere in the neighborhood of 400-500 sets of 23Mil points.

The 23Mil that I pull at a time are keyed on 3 different columns, it's all
indexed, and retrieval happens in say, 2-3 minutes (my hardware is so-so).
So, my thought is to use some kind of caching and wonder if I can get
advice - here are my thoughts on options, would love to hear others:

* use cached tables for this - since my # of actual data groups is small,
why not just retrieve them once, then keep them around in a specially named
table (I do this with some other stuff, using a 30 day cache expiration)
* Use some sort of stored procedure? I don't even know if such a thing
really exists in PG and how it works.
* Use table partitioning?

Thanks,
/r/b

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