Introduction to High-Performance R - UseR! 2008 Tutorial

Motivation Measuring Speedup Parallel Out of Mem AutomationIntroduction to High-Performance RUseR! 2008 TutorialDirk EddelbuettelTU DortmundAugust 11, 2008Dirk Eddelbuettel Intro to High-Performance R / UseR! 2008 TutorialMotivation Measuring Speedup Parallel Out of Mem AutomationMotivationWhat describes our current situation?I Moore’s Law: Computers keep getting faster and faster.I But at the same time out datasets get bigger and bigger.I And our research ambitions get bigger and bigger too.I So we’re still waiting and waiting . . .Hence: A need for higher / faster / further / ... computing with R.Dirk Eddelbuettel Intro to High-Performance R / UseR! 2008 TutorialMotivation Measuring Speedup Parallel Out of Mem AutomationMotivation cont.Roadmap: We will start by measuring how we are doing beforelooking at ways to improve our computing performance.We will look at vectorisation, a key method for speed improvements,as well as various ways to compile code.We will discuss ways to get more things done at the same time byusing simple parallel computing approaches.Next, we look at ways to compute with R beyond the memory limitsimposed by the R engine.Last but not least we look at ways to automate running R code.Dirk Eddelbuettel Intro to High-Performance R / UseR! 2008 TutorialMotivation Measuring Speedup Parallel Out of Mem AutomationOutlineMotivationMeasuring and profilingFaster: Vectorisation and Compiled CodeParallel execution: Explicitly and ...