Do you want to learn more about Linux, running jobs on an HPC research cluster, or about web applications? You’ve come to the right place!
We are putting together tutorials and templates for researchers, right now manifested as a collection of simple application templates. Please stay tuned for updates, and reach out if you are looking for consulting for a site or application.
While the material may initially seem daunting, don’t be discouraged. If you’ve been able to pick up R or SAS to do any work, you’ll be able to easily figure out how to use Linux. Here we have provided a list of resources that may suite your needs.
A code editor is a personal, sensitive decision for the most wordly of geeks. You might try a few, and decide which one that you like.
vimRead the “Best Practices for Scientific Computing” a paper written by biologists for biologists in 2014
git is here.For both scientific computing and general machine learning, you will likely want to run an analysis massively in parallel, or perhaps concept to a machine that has significantly more memory than your laptop. To aid with the tasks of getting many users connected to these machines, we have job managers.
What in the world is a job scheduler? When you go on a cluster like Sherlock, you will likely want to run an analysis massively in parallel, or perhaps concept to a machine that has significantly more memory than your laptop. To aid with the tasks of getting many users connected to these machines, we have job managers.
Stanford offers several on and off campus options for Stanford Researchers to do scientific computing, including Sherlock and Farmshare. You should consult each of the respective sites for full documentation.
XSEDE is an “Extreme Science and Engineering Discovery Environment”, an amazing resource that offers a set of courses to learn about everything from MPI programming to Apache Spark.