CISE Postdoctoral Research and Training in Advanced Compiler Optimizations (Operating Systems and Compilers Program/CCR/CISE)

Louisiana State University, Baton Rouge LA

Investigators

Abstract

0103933 Ramanujam, Jagannathan Louisiana State University & Agricultural and Mechanical College CISE Postdoctoral Associates in Experimental Computer Science: CISE Postdoctoral Research and Training in Advanced Compiler Optimization Modern processors extensively use memory hierarchies with multiple levels of caches in order to cope with the widening gap between processor and memory speeds. As a result, the performance of programs depend critically on their memory access characteristics and how these are matched to the memory hierarchy of the processors. While several compiler transformations have been proposed towards enhancing locality, even for programs with regular memory access patterns such as those in dense linear algebra computations, the best compiler-optimized codes do not match the performance of library implementations. One goal of this research is to train a postdoctoral research associate in the area of developing compiler transformations (either data or computation or a combination of the two) to handle a larger class of programming constructs than perfect nests and regular memory accesses. Initially, the associate will build on data shackling, which has been recently proposed as a data-centric approach to the problem of optimizing locality. To accomplish this goal, the associate will be trained to design an optimization strategy that will integrate data shackling (a data-centric approach) and tiling (a control-centric approach), and implement it in a compiler and evaluate its effectiveness. The associate will: 1) Study a large collection of applications with both regular and irregular memory access patterns, including scientific computing codes and multimedia applications, 2) Design heuristics for improving the effectiveness and applicability of data shackling, develop methods to integrate data shackling and tiling, and implement these in a compiler, and 3) Perform extensive experimental evaluation of the techniques on several benchmarking applications.