Holistic run-time parallelism management for time and energy efficiency

  • Authors:
  • Srinath Sridharan;Gagan Gupta;Gurindar S. Sohi

  • Affiliations:
  • University of Wisconsin-Madison, Madison, WI, USA;University of Wisconsin-Madison, Madison, WI, USA;University of Wisconsin-Madison, Madison, WI, USA

  • Venue:
  • Proceedings of the 27th international ACM conference on International conference on supercomputing
  • Year:
  • 2013

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Abstract

The ubiquity of parallel machines will necessitate time- and energy-efficient parallel execution of a program in a wide range of hardware and software environments. Prevalent parallel execution models can fail to be efficient. Unable to account for dynamic changes in operating conditions, they may create non-optimum parallelism, leading to underutilization or contention of resources. We propose ParallelismDial (PD), a model to dynamically, continuously and judiciously adapt a program's degree of parallelism to a given dynamic operating environment. PD uses a holistic metric to measure system-efficiency. The metric is used to systematically optimize the program's execution. We apply PD to two diverse parallel programming models: Intel TBB, an industry standard, and Prometheus, a recent research effort. Two prototypes of PD have been implemented. The prototypes are evaluated on two stock multicore workstations. Dedicated and multiprogrammed environments were considered. Experimental results show that the prototypes outperform the state-of-the-art approaches, on average, by 15% on time and 31% on energy efficiency, in the dedicated environment. In the multiprogrammed environment, the savings are to the tune of 19% and 21% in time and energy, respectively.