R is a highly dynamic language that employs a unique combination of data type immutability, lazy evaluation, argument matching, large amount of built-in functionality, and interaction with C and Fortran code. While these are straightforward to implement in an interpreter, it is hard to compile R functions to efficient bytecode or machine code. Consequently, applications that spend a lot of time in R code often have performance problems. Common solutions are to try to apply primitives to large amounts of data at once and to convert R code to a native language like C. FastR is a novel approach to solving R’s performance problem. It makes extensive use of the dynamic optimization features provided by the Truffle framework to remove the abstractions that the R language introduces, and can use the Graal compiler to create optimized machine code on the fly. This talk introduces FastR and the basic concepts behind Truffle’s optimization features. It provides examples of the language constructs that are particularly hard to implement using traditional compiler techniques, and shows how to use FastR to improve performance without compromising on language features.
