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This content will become publicly available on May 16, 2017

Title: Program optimizations: The interplay between power, performance, and energy

Practical considerations for future supercomputer designs will impose limits on both instantaneous power consumption and total energy consumption. Working within these constraints while providing the maximum possible performance, application developers will need to optimize their code for speed alongside power and energy concerns. This paper analyzes the effectiveness of several code optimizations including loop fusion, data structure transformations, and global allocations. A per component measurement and analysis of different architectures is performed, enabling the examination of code optimizations on different compute subsystems. Using an explicit hydrodynamics proxy application from the U.S. Department of Energy, LULESH, we show how code optimizations impact different computational phases of the simulation. This provides insight for simulation developers into the best optimizations to use during particular simulation compute phases when optimizing code for future supercomputing platforms. Here, we examine and contrast both x86 and Blue Gene architectures with respect to these optimizations.
 [1] ;  [1] ;  [2] ;  [2]
  1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
  2. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Publication Date:
OSTI Identifier:
Report Number(s):
Journal ID: ISSN 0167-8191; PII: S0167819116300369
Grant/Contract Number:
Accepted Manuscript
Journal Name:
Parallel Computing
Additional Journal Information:
Journal Name: Parallel Computing; Journal ID: ISSN 0167-8191
Research Org:
Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org:
USDOE National Nuclear Security Administration (NNSA)
Country of Publication:
United States
97 MATHEMATICS AND COMPUTING optimization; power; energy; performance