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    WMTrace - A Lightweight Memory Allocation Tracker and Analysis Framework

    Perks, O.F.J., Hammond, S.D., Pennycook, S.J. and Jarvis, S.A. (2011) WMTrace - A Lightweight Memory Allocation Tracker and Analysis Framework. In: Proceedings of the UK Performance Engineering Workshop (UKPEW'11), 7-8th July, 2011, Bradford, United Kingdom.

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      Abstract

      The diverging gap between processor and memory performance has been a well discussed aspect of computer architecture literature for some years. The use of multi-core processor designs has, however, brought new problems to the design of memory architectures - increased core density without matched improvement in memory capacity is reduc- ing the available memory per parallel process. Multiple cores accessing memory simultaneously degrades performance as a result of resource con- tention for memory channels and physical DIMMs. These issues combine to ensure that memory remains an on-going challenge in the design of parallel algorithms which scale.

      In this paper we present WMTrace, a lightweight tool to trace and analyse memory allocation events in parallel applications. This tool is able to dynamically link to pre-existing application binaries requiring no source code modification or recompilation. A post-execution analysis stage enables in-depth analysis of traces to be performed allowing memory allocations to be analysed by time, size or function.

      The second half of this paper features a case study in which we apply WMTrace to five parallel scientific applications and benchmarks, demonstrating its effectiveness at recording high-water mark memory consumption as well as memory use per-function over time. An in-depth analysis is provided for an unstructured mesh benchmark which reveals significant memory allocation imbalance across its participating processes.

      Item Type: Conference or Workshop Item (Paper)
      Uncontrolled Keywords: pcav hpsg tracing memory profiling
      Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
      Q Science > QA Mathematics > QA76 Computer software
      Q Science > QA Mathematics > QA76.73 Computer algorithms. Data structures.
      Divisions: Faculty of Science > Computer Science
      Depositing User: Simon Hammond
      Date Deposited: 31 May 2011 19:42
      Last Modified: 23 Feb 2012 09:08
      URI: http://eprints.dcs.warwick.ac.uk/id/eprint/727

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