Intermediate-level R users.
Data Circles, Vancouver and PDX R-Ladies
Why is this important?
Analyzing very large data sets and/or needing to run a computationally demanding analysis many times can be very slow.
What should be covered?
@bbarker505 has volunteered to demo use of the "parallel", "foreach", and "doParallel" packages. The demo will anlayze raster (gridded) data, specifically climate rasters.
Suggested speakers or contributors
@bbarker505
if others want to give talks (same day or another lunchtime meetup in same month), some suggested related topics are:
1) working with raster data (or other spatial features) in R
2) other ways to parallel process in R, such as using the "multidplyr" package
3) alternatives to parallel processing for some applications, such as using "data.table" or other package that can manipulate/analyze data relatively fast
Introduction to parallel processing in R
Who is the audience?
Intermediate-level R users. Data Circles, Vancouver and PDX R-Ladies
Why is this important?
Analyzing very large data sets and/or needing to run a computationally demanding analysis many times can be very slow.
What should be covered?
@bbarker505 has volunteered to demo use of the "parallel", "foreach", and "doParallel" packages. The demo will anlayze raster (gridded) data, specifically climate rasters.
Suggested speakers or contributors
@bbarker505
if others want to give talks (same day or another lunchtime meetup in same month), some suggested related topics are: 1) working with raster data (or other spatial features) in R 2) other ways to parallel process in R, such as using the "multidplyr" package 3) alternatives to parallel processing for some applications, such as using "data.table" or other package that can manipulate/analyze data relatively fast
Resources you would recommend to the audience
Demo here: https://github.com/bbarker505/parallel_demo