On Correctness of Data Structures under Reads-Write Concurrency

Abstract. We study the correctness of shared data structures under reads-write concurrency. A popular approach to ensuring correctness of read-only operations in the presence of concurrent update, is read-set validation, which checks that all read variables have not changed since they were first read. In practice, this approach is often too conserva-tive, which adversely affects performance. In this paper, we introduce a new framework for reasoning about correctness of data structures under reads-write concurrency, which replaces validation of the entire read-set with more general criteria. Namely, instead of verifying that all read conditions over the shared variables, which we call base conditions. We show that reading values that satisfy some base condition at every point in time implies correctness of read-only operations executing in parallel with updates. Somewhat surprisingly, the resulting correctness guarantee is not equivalent to linearizability, and is instead captured through two new conditions: validity and regularity. Roughly speaking, the former re-quires that a read-only operation never reaches a state unreachable in a sequential execution; the latter generalizes Lamport’s notion of regular-ity for arbitrary data structures, and is weaker than linearizability. We further extend our framework to capture also linearizability. We illus-trate how our framework can be applied for reasoning about correctness of a variety of implementations of data structures such as linked lists.

Fast and scalable rendezvousing

Abstract. In an asymmetric rendezvous system, such as an unfair synchronous queue and an elimination array, threads of two types, consumers and producers, show up and are matched, each with a unique thread of the other type. Here we present a new highly scalable, high throughput asymmetric rendezvous system that outperforms prior synchronous queue and elimination array implementations under both symmetric and asymmetric workloads (more operations of one type than the other). Consequently, we also present a highly scalable elimination-based stack.

Semantically Aware Contention Management for Distributed Applications

Part 1: Full Research PapersInternational audienceDistributed applications that allow replicated state to deviate in favour of increasing throughput still need to ensure such state achieves consistency at some point. This is achieved via compensating conflicting updates or undoing some updates to resolve conflicts. When causal relationships exist across updates that must be maintained then conflicts may result in previous updates also needing to be undone or compensated for. Therefore, an ability to manage contention across the distributed domain to preemptively lower conflicts as a result of causal infringements without hindering the throughput achieved from weaker consistency is desirable. In this paper we present such a system. We exploit the causality inherent in the application domain to improve overall system performance. We demonstrate the effectiveness of our approach with simulated benchmarked performance results