Adaptive locks: Combining transactions and locks for efficient concurrency

  • Authors:

  • Takayuki Usui;Reimer Behrends;Jacob Evans;Yannis Smaragdakis

  • Affiliations:

  • Department of Computer and Information Science, University of Oregon, Eugene, OR 97403, USA;Department of Computer and Information Science, University of Oregon, Eugene, OR 97403, USA;Department of Computer Science, University of Massachusetts, Amherst, MA 01003, USA;Department of Computer Science, University of Massachusetts, Amherst, MA 01003, USA

  • Venue:
  • Journal of Parallel and Distributed Computing
  • Year:
  • 2010

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Abstract

Transactional memory is being advanced as an alternative to traditional lock-based synchronization for concurrent programming. Transactional memory simplifies the programming model and maximizes concurrency. At the same time, transactions can suffer from interference that causes them to often abort, from heavy overheads for memory accesses, and from expressiveness limitations (e.g., for I/O operations). In this paper we propose an adaptive locking technique that dynamically observes whether a critical section would be best executed transactionally or while holding a mutex lock. The critical new elements of our approach include the adaptivity logic and cost-benefit analysis, a low-overhead implementation of statistics collection and adaptive locking in a full C compiler, and an exposition of the effects on the programming model. In experiments with both micro and macrobenchmarks we found adaptive locks to consistently match or outperform the better of the two component mechanisms (mutexes or transactions). Compared to either mechanism alone, adaptive locks often provide 3-to-10x speedups. Additionally, adaptive locks simplify the programming model by reducing the need for fine-grained locking: with adaptive locks, the programmer can specify coarse-grained locking annotations and often achieve fine-grained locking performance due to the transactional memory mechanisms.