Abstract

Compile-time type information should be valuable in efficient compilation of statically typed functional languages such as Standard ML. But how should typedirected compilation work in real compilers, and how much performance gain will type-based optimizations yield? In order to support more efficient data representations and gain more experience about type-directed compilation, we have implemented a new type-based middle end and back end for the Standard ML of New Jersey compiler. We describe the basic design of the new compiler, identify a number of practical issues, and then compare the performance of our new compiler with the old non-type-based compiler. Our measurement shows that a combination of several simple type-based optimizations reduces heap allocation by 36%; and improves the already-efficient code generated by the old non-typebased compiler by about 19% on a DECstation 5000. Address: Department of Computer Science, Yale University, 51 Prospect Street, New Haven, CT 06520...

Citations