SCHEDULE: NOV 10-16, 2012
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What Scientific Applications Can Benefit from Hardware Transactional Memory
SESSION: Memory Systems
EVENT TYPE: Papers
TIME: 2:30PM - 3:00PM
SESSION CHAIR: Jaejin Lee
AUTHOR(S):Martin Schindewolf, Martin Schulz, John Gyllenhaal, Barna Bihari, Amy Wang, Wolfgang Karl
Achieving efficient and correct synchronization of multiple threads is a difficult and error-prone task at small scale and, as we march towards extreme scale computing, will be even more challenging when the resulting application is supposed to utilize millions of cores efficiently. Transactional Memory (TM) is a promising technique to ease the burden on the programmer, but only recently has become available on commercial hardware in the new Blue Gene/Q system and hence the real benefit for scientific applications has not been studied yet. This paper presents the first performance results of TM embedded into OpenMP on a prototype system of BG/Q and characterizes code properties that will likely lead to benefits when augmented with TM primitives. Finally, we condense our findings into a set of best practices and apply them to a Monte Carlo Benchmark and a Smoothed Particle Hydrodynamics method to optimize the performance.
Jaejin Lee (Chair) - Seoul National University
Martin Schindewolf - Karlsruhe Institute of Technology
Martin Schulz - Lawrence Livermore National Laboratory
John Gyllenhaal - Lawrence Livermore National Laboratory
Barna Bihari - Lawrence Livermore National Laboratory
Amy Wang - IBM Toronto Lab
Wolfgang Karl - Karlsruhe Institute of Technology