NDLI: Discovering and understanding performance bottlenecks in transactional applications

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Discovering and understanding performance bottlenecks in transactional applications

Content Provider	ACM Digital Library
Author	Cristal, Adrián Harris, Tim Unsal, Osman S. Zyulkyarov, Ferad Hur, Ibrahim Valero, Mateo Stipic, Srdjan
Abstract	Many researchers have developed applications using transactionalmemory (TM) with the purpose of benchmarking different implementations, and studying whether or not TM is easy to use. However, comparatively little has been done to provide general-purpose tools for profiling and tuning programs which use transactions. In this paper we introduce a series of profiling techniques for TM applications that provide in-depth and comprehensive information about the wasted work caused by aborting transactions. We explore three directions: (i) techniques to identify multiple potential conflicts from a single program run, (ii) techniques to identify the data structures involved in conflicts by using a symbolic path through the heap, rather than a machine address, and (iii) visualization techniques to summarize how threads spend their time and which of their transactions conflict most frequently. To examine the effectiveness of the profiling techniques, we provide a series of illustrations from the STAMP TM benchmark suite and from the synthetic WormBench workload. We show how to use our profiling techniques to optimize the performance of the Bayes, Labyrinth and Intruder applications. We discuss the design and implementation of our techniques in the Bartok-STM system. We process data offline or during garbage collection, where possible, in order to minimize the probe effect introduced by profiling.
Starting Page	285
Ending Page	294
Page Count	10
File Format	PDF
ISBN	9781450301787
DOI	10.1145/1854273.1854311
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2010-09-11
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Transaction memory Profiling Applications
Content Type	Text
Resource Type	Article

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