Programming for different memory consistency models

Kourosh Gharachorloo, Sarita V. Adve, Anoop Gupta, John L. Hennessy, Mark D. Hill

Research output: Contribution to journalArticlepeer-review


The memory consistency model, or memory model, supported by a shared-memory multiprocessor directly affects its performance. The most commonly assumed memory model is sequential consistency (SC). While SC provides a simple model for the programmer, it imposes rigid constraints on the ordering of memory accesses and restricts the use of common hardware and compiler optimizations. To remedy the shortcomings of SC, several relaxed memory models have been proposed in the literature. These include processor consistency (PC), weak ordering (WO), release consistency (RCsc/RCpc), total store ordering (TSO), and partial store ordering (PSO). While the relaxed models provide the potential for higher performance, they present a more complex model for programmers when compared to SC. Our previous research has addressed this tradeoff by taking a programmer-centric approach. We have proposed memory models (DRF0, DRF1, PL) that allow the programmer to reason with SC, but require certain information about the memory accesses. This information is used by the system to relax the ordering among memory accesses while still maintaining SC for the programmer. Our previous models formalized the information that allowed optimizations associated with WO and RCsc to be used. This paper extends the above approach by defining a new model, PLpc, that allows optimizations of the TSO, PSO, PC, and RCpc models as well. Thus, PLpc provides a unified programming model that maintains the ease of reasoning with SC while providing for efficiency and portability across a wide range of proposed system designs.

Original languageEnglish (US)
Pages (from-to)399-407
Number of pages9
JournalJournal of Parallel and Distributed Computing
Issue number4
StatePublished - Aug 1992
Externally publishedYes

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture
  • Computer Networks and Communications
  • Artificial Intelligence


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