Heterogeneous computing: what does it mean for compiler research?

Abstract

The current trend in computer architecture is to increase the number of cores, to create specialized types of cores within a single machine, and to network such machines together in very fluid web/cloud computing arrangements. Compilers have traditionally focused on optimizations to code that improve performance, but is that the right target to speed up real applications? Consider loading a web page (like starting GMAIL) the page is transferred to the client, any JavaScript is compiled, the JavaScript executes, and the page gets displayed. The classic compiler model (which was first developed in the late 50's) was a great fit for single core machines but has fallen behind architecture, and language. For example how do you compile a single program for a machine that has both a CPU and a graphics coprocessor (a GPU) with a very different programming and memory model? Together with the changes in architecture there have been changes in programming languages. Dynamic languages are used more, static languages are used less. How does this effect compiler research? In this talk, I'll review a number of traditional compiler research challenges that have (or will) become burning issues and will describe some new problems areas that were not considered in the past. For example language specifica-tions are large complex technical documents that are difficult for non-experts to follow. Application programmers are often not willing to read these documents; can a compiler bridge the gap?