Dear List Members Registration is now open for the above course, this is free to all and part-funded by PRACE (and run in conjunction with ARCHER and HPC Wales). After recent upgrades to SPRINT (now also running on Mac multi-cores and compatible with MPI3) we have put this course together to provide guidance for our package and its parallelised R and Bioconductor packages. Registration and information available here: http://www.archer.ac.uk/training/ Who may benefit: Anyone dealing with large data sets (next gen sequencing or microarray data) in R, where computation times or memory issues arise when using machine learning (clustering, classification) or other approaches (bootstrapping, measuring distances between sequences, applying functions for large matrices, other statistics). We will outline some HPC basics and how to access HPC resources, but this course is not intended to introduce or develop parallel programming skills. However, you're more than welcome to join in and/or seek us out for discussion of "Big Data" in R. Pre-requisites: Basic familiarity with using R. Basic familiarity with large biological data sets (not a hard requirement, but our use cases will focus on these types of data). Visit www.r-sprint.org to get an overview of the parallelised functionality SPRINT currently provides. SPRINT Project sprint at ed.ac.uk www.r-sprint.org The University of Edinburgh -- The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336. Dr. Thorsten Forster Division of Pathway Medicine (DPM) University of Edinburgh Medical School Chancellor's Building 49 Little France Crescent Edinburgh Scotland, UK EH16 4SB 0131 242 6287 www.pathwaymedicine.ed.ac.uk -- The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336.