SC12 Home > SC12 Schedule > SC12 Presentation - What Scientific Applications Can Benefit from Hardware Transactional Memory

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

ROOM:355-D

ABSTRACT:
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.

Chair/Author Details:

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

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What Scientific Applications Can Benefit from Hardware Transactional Memory

SESSION: Memory Systems

EVENT TYPE:

TIME: 2:30PM - 3:00PM

SESSION CHAIR: Jaejin Lee

AUTHOR(S):Martin Schindewolf, Martin Schulz, John Gyllenhaal, Barna Bihari, Amy Wang, Wolfgang Karl

ROOM:355-D

ABSTRACT:
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.

Chair/Author Details:

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

Add to iCal  Click here to download .ics calendar file

Add to Outlook  Click here to download .vcs calendar file

Add to Google Calendarss  Click here to add event to your Google Calendar