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
  • Malleable
  • Resizable
  • Rigid
  • Thread
Date of Defense 2011-06-16
Availability unrestricted
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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