Automatic Parallel Program Generation and Optimization from Data Decompositions
Edwin M. Paalvast, Henk J. Sips, Arjan J. van Gemund · Data Archiving and Networked Services (DANS) · 1991
Data decomposition is probably the most successful method for generating parallel programs.In this paper a general framework is described for the automatic generation of parallel programs based on a separately specified decomposition of the data.To this purpose, programs and data decompositions are expressed in a calculus, called Vcal.It is shown that by rewriting calculus expressions, Single Program Multiple Data (SPMD) code can be generated for shared-memory as well as distributed-memory parallel processors.Optimizations are derived for certain classes of access functions to data structures, subject to block, scatter, and block/scatter decompositions.The presented calculus and transformations are language independent. 1.