Title page for ETD etd-06292011-130247

Type of Document

Master's Thesis

Author

McFarland, Daniel James

Author's Email Address

dmcfarl@vt.edu

URN

etd-06292011-130247

Title

Exploiting Malleable Parallelism on Multicore Systems

Degree

Master of Science

Department

Computer Science

Advisory Committee

Advisor Name	Title
Ribbens, Calvin J.	Committee Chair
Back, Godmar V.	Committee Member
Butt, Ali R. A.	Committee Member

Keywords

Malleable
Resizable
Rigid
Thread

Date of Defense

2011-06-16

Availability

unrestricted

Abstract

As shared memory platforms continue to grow in core counts, the need for context-aware
scheduling continues to grow. Context-aware scheduling takes into account characteristics of
the system and application performance when making decisions. Traditionally applications
run on a static thread count that is set at compile-time or at job start time, without taking
into account the dynamic context of the system, other running applications, and potentially
the performance of the application itself. However, many shared memory applications can
easily be converted to malleable applications, that is, applications that can run with an
arbitrary number of threads and can change thread counts during execution. Many new
and intelligent scheduling decisions can be made when applications become context-aware,
including expanding to ll an empty system or shrinking to accommodate a more parallelizable
job. This thesis describes a prototype system called Resizing for Shared Memory
(RSM), which supports OpenMP applications on shared memory platforms. RSM includes a
main daemon that records performance information and makes resizing decisions as well as a
communication library to allow applications to contact the RSM daemon and enact resizing
decisions. Experimental results show that RSM can improve turn-around time and system
utilization even using very simple heuristics and resizing policies.

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