Summary: Unified Compilation Techniques for
Shared and Distributed Address Space Machines
Chau­Wen Tseng, Jennifer M. Anderson, Saman P. Amarasinghe and Monica S. Lam
Computer Systems Laboratory
Stanford University
Stanford, CA 94305­4070
Abstract
Parallel machines with shared address spaces are easy to program
because they provide hardware support that allows each processor
to transparently access non­local data. However, obtaining scalable
performance can be difficult due to memory access and synchro­
nization overhead. In this paper, we use profiling and simulation
studies to identify the sources of parallel overhead. We demonstrate
that compilation techniques for distributed address space machines
can be very effective when used in compilers for shared address
space machines. Automatic data decomposition can co­locate data
and computation to improve locality. Data reorganization transfor­
mations can reduce harmful cache effects. Communication analysis
can eliminate barrier synchronization. We present a set of unified
compilation techniques that exemplify this convergence in compil­

Source: Amarasinghe, Saman - Computer Science and Artificial Intelligence Laboratory & Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology (MIT)

Collections: Computer Technologies and Information Sciences