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This section provides a brief introduction to high performance computing (HPC) resources and techniques typically used by lab members. This includes tips and tricks for transferring, running and manipulating your files on remote computers such as clusters. You may need high performance computing for running data-analysis code in parallel, performing simulations, or processing large, spatial data sets, among other things. But before getting wrapped up in the technical details of a computationally intensive project, it is often worth considering whether you may achieve your goals with a simpler algorithm which requires few, if any, computational resources. On the other hand, computational resources keep growing and becoming easier to use, so using them may be the best choice. The links below provide an assortment of quick-start guides for routine HPC-related tasks in this lab.
- Getting started using SSH to run commands remotely
- Moving files to and from remote computers
- Connecting to RStudio Server on the high-memory machines
- Installing and removing software on the high-memory machines
- Tips for tear-free HPC
Come here to learn how to install and get started using software for tasks commonly done in the Drake Lab.
Come here when beginning a new project for steps to set up folder directory structure, ease electronic collaboration, and setting up version control, a system for managing projects over time.
Come here to learn about how to manage data from different sources, including how and where to store data in the Drake lab. This also includes information on making data manipulation reproducible through the use of scripts, especially in R.
This covers our lab's approach to syntax and code review. (maybe a list of packages and contact people for each)
Come here for general guidelines for designing figures, from layout to the R code to file formats.
Come here to learn about the tools commonly used in the lab to write manuscripts and other documents. There are also several links to lab specific info on writing content.