Re: [igraph] memory limitation

[Alisa Coffin]

Thanks for your help Gabor.  Indeed I was able to work the 3rd
(smaller) graph object after I removed all other graph objects from the
.rdata file and saved it as a new .rdata file with only the one graph
object.  I'll have to add more memory to get that last, larger one done.

On Thu, Jun 12, 2008 at 1:35 PM, Gabor Csardi <address@hidden> wrote:

Alisa, try calculating the shortest paths in two (or more) steps,
e.g. if you have 10000 vertices, first calculate the sortest distance
from the first 5000 to all others and then the second 5000.

As for whether 2Gb is enough, igraph uses 32 bytes per edge and
16 bytes per vertex to store a network. So your network only takes
a small amount of the memory.

The shortest paths matrix for your graph takes about 570Mb of memory
(8 bytes for each element) and it is copied once, so you need two
times 570Mb. 2Gb is likely to be enough, but i cannot say for
sure, as i don't have intimate knowledge about R's memory management
on Windows.

For your smaller network, only two times 335Mb is needed.

Hope this helps,
Gabor

On Thu, Jun 12, 2008 at 01:23:31PM -0400, Alisa Coffin wrote:
> Dear igraph developers and users,
>
> I have 4 connected, simple, undirected graph objects for which I am trying to
> discover the shortest paths using igraph in R.  When I ran the "shortest.paths"
> routine on the first two, I had no problem, but for the last two, I come up
> against what appears to be a memory limitation.  I have tried the analysis on
> both my laptop and my desktop, both of which have 1Gb RAM on a Windows
> platform.  For both of these datasets, I get the message: "Error: cannot
> allocate vector of size ...".  The first problem graph has 6593 vertices and
> 8268 edges.  The second one has 8613 vertices and 10649 edges.  These do not
> strike me as inordinately large, but the first two graphs were a bit smaller
> and the routine worked just fine for them.
>
> Please forgive the basic nature of this question, but will this problem be
> resolved if I try the analysis on a 2Gb machine? Are there other possible
> solutions?  I have scoured the R manual for information on how to resolve this
> problem and think that the memory issue may be the problem, but I can't see any
> other possibilities.
>
> Your help is GREATLY appreciated!
>
> Alisa.
>
> p.s. I can send the .rdata file if anyone is interested in trying it out on
> their machine.
>
> --
> Alisa Coffin, PhD. Candidate
> Department of Geography
> University of Florida
> Gainesville, FL 32611

> _______________________________________________
> igraph-help mailing list
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--
Csardi Gabor <address@hidden>    UNIL DGM


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-- 
Alisa Coffin, PhD. Candidate
Department of Geography
University of Florida
Gainesville, FL 32611