R: mgcv function bam: use multiple kernels from jupyter notebook

Question

I use R in a jupyter notebook as described in this article. It work's perfectly fine. However, when I fit a GAM using the mgcv library and bam, e.g.:

dat <- gamSim(1,n=25000,dist="normal",scale=20)
bs <- "cr"; k <- 12
b <- bam(y ~ s(x0,bs=bs)+s(x1,bs=bs)+s(x2,bs=bs,k=k)+
           s(x3,bs=bs), data=dat, discrete=TRUE, nthreads=4)

the jupyter notebook does not utilize multiple cpu's at once. This is problematic as work with big data. Any ideas how to fix this?

Gavin Simpson · Accepted Answer · 2022-03-04 18:25:00Z

0

You need to use discrete = TRUE to be able to use the nthreads argument. Read ?bam for ways to do the computation in parallel if you don’t want to use the discretisation option.

edited Mar 4, 2022 at 18:25

answered Mar 4, 2022 at 17:21

Gavin Simpson

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2 Comments

hyhno01 Over a year ago

Thanks for the reply. My fault. I use discrete=True in the notebook but forgot to include it in my question

Gavin Simpson Over a year ago

@hyhno01 it's TRUE not True. Try running the code outside of a Jupyter notebook as that may be causing a problem. I believe nthreads requires the package to have been compiled with openMP support, so perhaps check that too?

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