Summary: 1
This research was supported in part by DARPA contract DABT63­91­K­
0003, an NSF Young Investigator Award and a fellowship from Intel Cor­
poration.
Communication Optimization and Code Generation
for Distributed Memory Machines
Saman P. Amarasinghe and Monica S. Lam
Computer Systems Laboratory
Stanford University, CA 94305
Abstract
This paper presents several algorithms to solve code generation
and optimization problems specific to machines with distributed
address spaces. Given a description of how the computation is to
be partitioned across the processors in a machine, our algorithms
produce an SPMD (single program multiple data) program to be
run on each processor. Our compiler generates the necessary
receive and send instructions, optimizes the communication by
eliminating redundant communication and aggregating small mes­
sages into large messages, allocates space locally on each proces­
sor, and translates global data addresses to local addresses.

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