@jhamman can you help with providing an example for how to use DASK to handle computationally expensive jobs. I got the for loop to calculated SVD in the script below (on my fork), but it's pretty slow for a single variable and single model. Is there a slick way to use DASK to speed this up?
notebook also available in /home/wwieder/python/ctsm_py/notebooks/.
https://github.com/wwieder/ctsm_py/blob/master/notebooks/MonthlySVD.ipynb
P.S., if the notebook renders can you find out why it's printing so much output to the screen?
Finally, also good to mask out grids w/ zero GPP (e.g. Antarctic)?
@jhamman can you help with providing an example for how to use DASK to handle computationally expensive jobs. I got the for loop to calculated SVD in the script below (on my fork), but it's pretty slow for a single variable and single model. Is there a slick way to use DASK to speed this up?
notebook also available in /home/wwieder/python/ctsm_py/notebooks/.
https://github.com/wwieder/ctsm_py/blob/master/notebooks/MonthlySVD.ipynb
P.S., if the notebook renders can you find out why it's printing so much output to the screen?
Finally, also good to mask out grids w/ zero GPP (e.g. Antarctic)?