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SCHEDULE: NOV 16-21, 2014
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Optimizing Data Locality for Fork/Join Programs Using Constrained Work Stealing
SESSION: Data Locality and Load Balancing
EVENT TYPE: Papers
TIME: 2:00PM - 2:30PM
SESSION CHAIR: Didem Unat
AUTHOR(S):Jonathan Lifflander, Sriram Krishnamoorthy, Laxmikant V. Kale
ROOM:388-89-90
ABSTRACT:
We present an approach to improving data locality across different phases of fork/join programs scheduled using work stealing. The approach consists of: (1) user-specified and automated approaches to constructing a steal tree, the schedule of steal operations and (2) constrained work stealing algorithms that constrain the actions of the scheduler to mirror a given steal tree. These are combined to construct work stealing schedules that maximize data locality across computation phases while ensuring load balance within each phase. These algorithms are also used to demonstrate dynamic coarsening, an optimization to improve spatial locality and sequential overheads by combining many finer-grained tasks into coarser tasks while ensuring sufficient concurrency for locality-optimized load balance. Implementation and evaluation in Cilk demonstrate performance improvements of up to 2.5x on 80 cores. We also demonstrate that dynamic coarsening can combine the performance benefits of coarse task specification with the adaptability of finer tasks.
Chair/Author Details:
Didem Unat (Chair) - Koç University
Jonathan Lifflander - University of Illinois at Urbana-Champaign
Sriram Krishnamoorthy - Pacific Northwest National Laboratory
Laxmikant V. Kale - University of Illinois at Urbana-Champaign
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