Hello,
I've implemented dynamic programming for aligning spectral data (usually 100 to
200 peaks in one spectrum, but some spectra contain > 5k peaks) entirely in R.
As François Pinard pointed out, the memory usage should be proportional to the
n x n dynamic programming matrix, and I've not yet had any problems on my
machine (R2.2.0 win2k, 1GB mem, 2GHz Intel PV), CPU seems to be the more
problematic issue.
I guess it all depends on how much data you have. You could split the dynamic
programming matrix into chunks and calculate them in parallel on different
machines (but the implementatino of finding the optiomal trace will probably
get a bit difficult).
kind regards,
Arne
-----Original Message-----
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] Behalf Of Arnab mukherji
Sent: Thursday, January 19, 2006 22:55
To: [email protected]
Subject: [R] Dynamic Programming in R
Hi R users,
I am looking to numerically solve a dynamic program in the R environment. I was
wondering if there were people out there who had expereinced success at using R
for such applications. I'd rather continue in R than learn Mathlab.
A concern that has been cited that may discourage R use for solving dynamic
programs is its memory handling abilities. A senior researcher had a lot of
trouble with R becuase on any given run it would eat up all the computers
memory and need to start using the hard disk. Yet, the memory needed was not
substantial - saving the worksapce, exiting and recalling would noticebly start
of tthe progam at a much lower memory use, level and a quick deteroration in a
few thousand iterations.
Is this a problem other people have come across? Perhaps, its a problem already
fixed, since the researcher was working on this in 2002 (he claimed he had
tried it on windows, mac, and unix versions to check).
Thanks.
Arnab
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