Avoiding consistency exceptions under strong memory models

Abstract

Shared-memory languages and systems generally provide weak or undefined semantics for executions with data races. Prior work has proposed memory consistency models that ensure well-defined, easy-to-understand semantics based on region serializability (RS), but the resulting system may throw a consistency exception in the presence of a data race. Consistency exceptions can occur unexpectedly even in well-tested programs, hurting availability and thus limiting the practicality of RS-based memory models. To our knowledge, this paper is the first to consider the problem of availability for memory consistency models that throw consistency exceptions. We first extend existing approaches that enforce RSx , a memory model based on serializability of synchronization-free regions (SFRs), to avoid region conflicts and thus consistency exceptions. These new approaches demonstrate both the potential for and limitations of avoiding consistency exceptions under RSx. To improve availability further, we introduce (1) a new memory model called RIx based on isolation of SFRs and (2) a new approach called Avalon that provides RIx. We demonstrate two variants of Avalon that offer different performance-availability tradeoffs for RIx. An evaluation on real Java programs shows that this work's novel approaches are able to reduce consistency exceptions, thereby improving the applicability of strong memory consistency models. Furthermore, the approaches provide compelling points in the performance-availability tradeoff space for memory consistency enforcement. RIx and Avalon thus represent a promising direction for tackling the challenge of availability under strong consistency models that throw consistency exceptions.