Here are some resources mentioned during the "Parallel Computing in R" talk I'm giving at the co-hosted meeting of the San Diego R User Group and the PACE Tech Talk Series on September 10, 2013.

The slides presented during this talk are available on the PACE website (login required)

Alternatively, you can send me an email (glock at sdsc dot edu) and I'd be happy to send you the slides myself.

Examples Codes

Here are download links for the scripts and the text of Moby Dick used in the Hadoop examples. You can copy+paste the kmeans examples straight from GitHub into your laptop's R installation to try out the multicore examples.



If you are interested in getting compute time on Gordon, you can quickly get a startup allocation through the National Science Foundation's XSEDE program for up to 100,000 core-hours by writing up an abstract of the work you would like to do. For more information, either check out the XSEDE allocations webpage or send us an email at Gordon (and this presentation) is funded under NSF award OCI-0910847.


If you are interested in attending PACE's Data Mining Boot Camp, you can register via the PACE Boot Camps webpage. The first Boot Camp will be held September 12 and 13th and members of the San Diego R User Group get a 10% discount on the $1295 registration fee (contact me for the promo code). People with academic affiliations (a .edu email address) are eligible for a $600 discount.

As a personal testimonial (note: I am not funded by PACE), these workshops are a really great way to get both conceptual and hands-on training in a lot of the principles that are key to predictive analytics. The sessions are led by very high-caliber individuals, and even if nothing else, are an exceptional way to connect with local experts in the field of predictive analytics. PACE also hosts monthly Tech Talks which are free to the public and may be of interest to members of the San Diego R User Group. This talk of mine is being cross-promoted as a Tech Talk, and I'm hoping that hosting the September meeting at SDSC opens the doors to future cross-collaboration between PACE and the R User Group.

More Info

Here are a few guides we have created at SDSC that are relevant to this particular talk:

External Links