Computing and graphics are vital areas of statistical practice, especially important for today’s data-driven practices. The Statistical Computing and Visualisation section of the Statistical Society of Australia proudly presents an Invited Speaker webinar titled “Async and Parallel R: Building the Open Source Tools” delivered by Charlie Gao, Senior Software Engineer at Posit (formerly RStudio).
Read the abstract here.
Simulation studies, bootstrapping, cross-validation, MCMC - statistical computing is full of work that could run in parallel, yet parallel R too often means a blocked session, a copy of your data on every worker, and code rewritten for each new environment. Over several years I’ve built the layers needed to fix this: a messaging substrate for reliable async I/O, a framework for async and parallel computing on top of it, and a way to share R objects across processes without copying. This talk is a practical tour of that stack from laptop to HPC cluster, with patterns you can apply to your own analyses straight away, plus a closing look at where the zero-copy model is headed next.
