Title page for ETD etd-07042009-010717

Type of Document

Dissertation

Author

Kim, Dong Kwan

Author's Email Address

ikek70@vt.edu

URN

etd-07042009-010717

Title

Applying Dynamic Software Updates to Computationally-Intensive Applications

Degree

PhD

Department

Computer Science

Advisory Committee

Advisor Name	Title
Eli Tilevich	Committee Chair
Calvin J. Ribbens	Committee Member
Denis Gracanin	Committee Member
James D. Arthur	Committee Member
Jung-Min Park	Committee Member
Marc Fisher II	Committee Member
Shawn A. Bohner	Committee Member

Keywords

Proxy Pattern
Java Virtual Machine
Binary Rewriting
HPC
Dynamic Software Updates
Computationally-Intensive Applications

Date of Defense

2009-06-22

Availability

unrestricted

Abstract

Dynamic software updates change the code of a computer program while it runs,
thus saving the programmer’s time and using computing resources more productively.
This dissertation establishes the value of and recommends practices for applying dynamic software
updates to computationally-intensive applications—a computing domain characterized
by long-running computations, expensive computing resources, and a tedious deployment
process. This dissertation argues that updating computationally-intensive applications dynamically
can reduce their time-to-discovery metrics—the total time it takes from posing
a problem to arriving at a solution—and, as such, should become an intrinsic part of their
software lifecycle. To support this claim, this dissertation presents the following technical
contributions: (1) a distributed consistency algorithm for synchronizing dynamic software
updates in a parallel HPC application, (2) an implementation of the Proxy design pattern
that is more efficient than the existing implementations, and (3) a dynamic update approach
for Java Virtual Machine (JVM)-based applications using the Proxy pattern to offer flexibility
and efficiency advantages, making it suitable for computationally-intensive applications.
The contributions of this dissertation are validated through performance benchmarks and
case studies involving computationally-intensive applications from the bioinformatics and
molecular dynamics simulation domains.

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