Compiler techniques for optimizing communication and data distribution for distributed-memory multicomputers

Distributed-memory multicomputers, such as the Intel iPSC/860, the Intel Paragon, the IBM SP-1 /SP-2, the NCUBE/2, and the Thinking Machines CM-5, offer significant advantages over shared-memory multiprocessors in terms of cost and scalability. However, lacking a global address space, they present a very difficult programming model in which the user must specify how data and computation are to be distributed across processors and determine those sections of data to be communicated to specific processors. To overcome this difficulty, significant research effort has been aimed at source-to-source parallelizing compilers for multicomputers that relieve the programmer from the task of program partitioning and communication generation, while the specification of data distributions has remained a responsibility of the programmer.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Electrical Engineering

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2011

Author dc:creator

• Palermo, Daniel Joseph

Contributors dc:contributor

• Banerjee, Prithviraj

• Engineering, Electronics and Electrical
• Computer Science

Statement dc:rights

• Copyright 1996 Palermo, Daniel Joseph

Language dc:language

eng

Identifier

9780591198485
AAI9712391
(UMI)AAI9712391

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/19722