2 research outputs found
A Graph-Based Semantics Workbench for Concurrent Asynchronous Programs
A number of novel programming languages and libraries have been proposed that
offer simpler-to-use models of concurrency than threads. It is challenging,
however, to devise execution models that successfully realise their
abstractions without forfeiting performance or introducing unintended
behaviours. This is exemplified by SCOOP---a concurrent object-oriented
message-passing language---which has seen multiple semantics proposed and
implemented over its evolution. We propose a "semantics workbench" with fully
and semi-automatic tools for SCOOP, that can be used to analyse and compare
programs with respect to different execution models. We demonstrate its use in
checking the consistency of semantics by applying it to a set of representative
programs, and highlighting a deadlock-related discrepancy between the principal
execution models of the language. Our workbench is based on a modular and
parameterisable graph transformation semantics implemented in the GROOVE tool.
We discuss how graph transformations are leveraged to atomically model
intricate language abstractions, and how the visual yet algebraic nature of the
model can be used to ascertain soundness.Comment: Accepted for publication in the proceedings of FASE 2016 (to appear
Safe and Efficient Data Sharing for Message-Passing Concurrency
International audienceMessage passing provides a powerful communication abstraction in both distributed and shared memory environments. It is particularly successful at preventing problems arising from shared state, such as data races, as it avoids sharing in general. Message passing is less effective when concurrent access to large amounts of data is needed, as the overhead of messaging may be prohibitive. In shared memory environments, this issue could be alleviated by supporting direct access to shared data; but then ensuring proper synchronization becomes again the dominant problem. This paper proposes a safe and efficient approach to data sharing in message-passing concurrency models based on the idea of distinguishing active and passive computational units. Passive units do not have execution capabilities but offer to active units exclusive and direct access to the data they encapsulate. The access is transparent due to a single primitive for both data access and message passing. By distinguishing active and passive units, no additional infrastructure for shared data is necessary. The concept is applied to SCOOP, an object-oriented concurrency model, where it reduces execution time by several orders of magnitude on data-intensive parallel programs