SCHEDULE: NOV 10-16, 2012
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Characterizing and Mitigating Work Time Inflation in Task Parallel Programs
SESSION: Locality in Programming Models and Runtimes
EVENT TYPE: Papers, Best Student Paper Finalists
TIME: 3:30PM - 4:00PM
SESSION CHAIR: Milind Kulkarni
AUTHOR(S):Stephen L. Olivier, Bronis R. de Supinski, Martin Schulz, Jan F. Prins
ROOM:255-EF
ABSTRACT:
Task parallelism raises the level of abstraction in shared memory parallel programming to simplify the development of complex applications. However, task parallel applications can exhibit poor performance due to thread idleness, scheduling overheads, and work time inflation -- additional time spent by threads in a multithreaded computation beyond the time required to perform the same work in a sequential computation. We identify the contributions of each factor to lost efficiency in various task parallel OpenMP applications and diagnose the causes of work time inflation in those applications.
A major cause of work time inflation in NUMA systems is increased latency to access data for computations. To mitigate this source of work time inflation in some applications, we propose a locality framework for task parallel OpenMP programs. As implemented in our extensions to the Qthreads library, locality-aware scheduling demonstrates up to 3X improvement compared to the Intel OpenMP task scheduler.
Chair/Author Details:
Milind Kulkarni (Chair) - Purdue University
Stephen L. Olivier - University of North Carolina at Chapel Hill
Bronis R. de Supinski - Lawrence Livermore National Laboratory
Martin Schulz - Lawrence Livermore National Laboratory
Jan F. Prins - University of North Carolina at Chapel Hill
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Characterizing and Mitigating Work Time Inflation in Task Parallel Programs
SESSION: Locality in Programming Models and Runtimes
EVENT TYPE: , Best Student Paper Finalists
TIME: 3:30PM - 4:00PM
SESSION CHAIR: Milind Kulkarni
AUTHOR(S):Stephen L. Olivier, Bronis R. de Supinski, Martin Schulz, Jan F. Prins
ROOM:255-EF
ABSTRACT:
Task parallelism raises the level of abstraction in shared memory parallel programming to simplify the development of complex applications. However, task parallel applications can exhibit poor performance due to thread idleness, scheduling overheads, and work time inflation -- additional time spent by threads in a multithreaded computation beyond the time required to perform the same work in a sequential computation. We identify the contributions of each factor to lost efficiency in various task parallel OpenMP applications and diagnose the causes of work time inflation in those applications.
A major cause of work time inflation in NUMA systems is increased latency to access data for computations. To mitigate this source of work time inflation in some applications, we propose a locality framework for task parallel OpenMP programs. As implemented in our extensions to the Qthreads library, locality-aware scheduling demonstrates up to 3X improvement compared to the Intel OpenMP task scheduler.
Chair/Author Details:
Milind Kulkarni (Chair) - Purdue University
Stephen L. Olivier - University of North Carolina at Chapel Hill
Bronis R. de Supinski - Lawrence Livermore National Laboratory
Martin Schulz - Lawrence Livermore National Laboratory
Jan F. Prins - University of North Carolina at Chapel Hill
Click here to download .ics calendar file