Time-Based Software Transactional Memory

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

Abstract

Software transactional memory (STM) is a concurrency control mechanism that is widely considered to be easier to use by programmers than other mechanisms such as locking. The first generations of STMs have either relied on visible read designs, which simplify conflict detection while pessimistically ensuring a consistent view of shared data to the application, or optimistic invisible read designs that are significantly more efficient but require incremental validation to preserve consistency, at a cost that increases quadratically with the number of objects read in a transaction. Most of the recent designs now use a “time-based” (or “time stamp-based”) approach to still benefit from the performance advantage of invisible reads without incurring the quadratic overhead of incremental validation. In this paper, we give an overview of the time-based STM approach and discuss its benefits and limitations. We formally introduce the first time-based STM algorithm, the Lazy Snapshot Algorithm (LSA). We study its semantics and the impact of its design parameters, notably multiversioning and dynamic snapshot extension. We compare it against other classical designs and we demonstrate that its performance is highly competitive, both for obstruction-free and lock-based STM designs.

Details

Original languageEnglish
Pages (from-to)1793-1807
Number of pages15
JournalIEEE Transactions on Parallel and Distributed Systems
Publication statusPublished - 2010
Peer-reviewedYes

External IDs

Scopus 78149282821

Keywords

Research priority areas of TU Dresden

DFG Classification of Subject Areas according to Review Boards

Keywords

  • Transactional memory, transactions, concurrency, atomicity, Concurrency control, Programming profession, Object detection, Design optimization, Cost function, Concurrent computing, Multicore processing, Application software, Runtime environment, Algorithm design and analysis