get ncdf values at point locations - efficient method?

Hi,

I'm trying to extract data from point locations in NetCDF files efficiently.
I can do it for small data, but I am moving to scenarios with huge grids and
500,000 points.  For small data, I do one of two things:

1) Read the entire grid into memory and convert it to a raster stack, then
extract cell values at my coordinates.
2) Loop through each point, reading in just the single value from the ncdf.

The problem with #1 is that it is too slow and large to fit all those
extraneous grid cells into memory.  The problem with #2 is that looping
through 500,000 points is too slow.  What I want to do is something like #2,
but without a loop - a single vectorizable call.  Any suggestions?

Here's a simplified version of what my #2 code looks like now:

opened.ncdf <- open.ncdf(test.nc)
lons <- get.var.ncdf(opened.ncdf, 'longitude')
lats <- get.var.ncdf(opened.ncdf, 'latitude')
point.coords <- read.csv('lonlat.csv')
point.coords[,1] <- sapply(point.coords[,1],function(x)which.min(abs(x -
lons)))
point.coords[,2] <- sapply(point.coords[,2],function(x)which.min(abs(x -
lats)))
layer.num <- 3 # this is time, I have seperate ways for handling this, let's
just call it timestep 3 for now
output <- vector('numeric',length(dim(point.coords)[1]))

for(i in 1:(dim(point.coords)[1])){
        output[i] <- get.var.ncdf(opened.ncdf,
start=c(point.coords[i,],layer.num), count=c(1,1,1))
}

Is there a way to vectorize that slow loop???

Thanks!!!
-Noah

---
Noah Charney, PhD
Visiting Assistant Professor of Ecology
School of Natural Science
Hampshire College
304 Cole Science Center
Amherst, MA 01002
413-559-5775