Title page for ETD etd-08222006-002829

Type of Document

Dissertation

Author

Mukherjee, Joy

Author's Email Address

jmukherj@vt.edu

URN

etd-08222006-002829

Title

A Runtime Framework for Parallel Programs

Degree

PhD

Department

Computer Science

Advisory Committee

Advisor Name	Title
Varadarajan, Srinidhi	Committee Chair
Arthur, James D.	Committee Member
Midkiff, Scott F.	Committee Member
Ramakrishnan, Naren	Committee Member
Ribbens, Calvin J.	Committee Member

Keywords

Dynamic Adaptation
Runtime Linking and Loading
Lightweight Threads
Component Composition
Parallel Programs
Legacy Procedural codes

Date of Defense

2006-08-16

Availability

unrestricted

Abstract

This dissertation proposes the Weaves runtime framework for the execution of large scale
parallel programs over lightweight intra-process threads. The goal of the Weaves framework
is to help process-based legacy parallel programs exploit the scalability of threads without any
modifications. The framework separates global variables used by identical, but independent,
threads of legacy parallel programs without resorting to thread-based re-programming. At
the same time, it also facilitates low-overhead collaboration among threads of a legacy parallel
program through multi-granular selective sharing of global variables.

Applications that follow the tenets of the Weaves framework can load multiple identical, but
independent, copies of arbitrary object files within a single process. They can compose the
runtime images of these object files in graph-like ways and run intra-process threads through
them to realize various degrees of multi-granular selective sharing or separation of global
variables among the threads. Using direct runtime control over the resolution of individual
references to functions and variables, they can also manipulate program composition at fine
granularities. Most importantly, the Weaves framework does not entail any modifications to
either the source codes or the native codes of the object files. The framework is completely
transparent.

Results from experiments with a real-world process-based parallel application show that
the framework can correctly execute a thousand parallel threads containing non-threadsafe
global variables on a single machine - nearly twice as many as the traditional process-based
approach can - without any code modifications. On increasing the number of machines, the
application experiences super-linear speedup, which illustrates scalability. Results from another similar application, chosen from a different software area to emphasize the breadth
of this research, show that the framework's facilities for low-overhead collaboration among
parallel threads allows for significantly greater scales of achievable parallelism than technologies
for inter-process collaboration allow. Ultimately, larger scales of parallelism enable
more accurate software modeling of real-world parallel systems, such as computer networks
and multi-physics natural phenomena.

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