Improving compiler scalability: optimizing large programs at small price

Compiler scalability is a well known problem: reasoning about the application of useful optimizations over large program scopes consumes too much time and memory during compilation. This problem is exacerbated in polyhedral compilers that use powerful yet costly integer programming algorithms to compose loop optimizations. As a result, the benefits that a polyhedral compiler has to offer to programs such as real scientific applications that contain sequences of loop nests, remain impractical for the common users. In this work, we address this scalability problem in polyhedral compilers. We identify three causes of unscalability, each of which stems from large number of statements and dependences in the program scope. We propose a one-shot solution to the problem by reducing the effective number of statements and dependences as seen by the compiler. We achieve this by representing a sequence of statements in a program by a single super-statement. This set of super-statements exposes ...

• Type: Journal
• Year: 2015
• Where: PLDI
• Authors: Sanyam Mehta, Pen-Chung Yew
• Keywords: PLDI 2015, Programming Languages