Relaxed Data Types as Consistency Conditions †

Modeling Relaxed Memory Consistency Protocols

This paper presents a modeling approach based on deterministic and stochastic Petri nets (DSPN's) for analyzing memory consistency protocols for multiprocessors with Distributed Shared Memory (DSM). DSPN's are a numerically solvable modeling formalism with a graphical representation. The modeling approach addresses in particular the performance degradation due to the amount of message exchange,...

Quiescent Consistency: Defining and Verifying Relaxed Linearizability

Concurrent data structures like stacks, sets or queues need to be highly optimized to provide large degrees of parallelism with reduced contention. Linearizability, a key consistency condition for concurrent objects, sometimes limits the potential for optimization. Hence algorithm designers have started to build concurrent data structures that are not linearizable but only satisfy relaxed consi...

Quasi-Linearizability: Relaxed Consistency for Improved Concurrency

Linearizability, the key correctness condition that most optimized concurrent object implementations comply with, imposes tight synchronization between the object concurrent operations. This tight synchronization usually comes with a performance and scalability price. Yet, these implementations are often employed in an environment where a more relaxed linearizability condition suffices, where s...

Hiding Relaxed Memory Consistency with a Compiler

Data Types as Algorithms

— This paper présents a simplified construction of an algorithm space. The intuitive notion ofan algorithm collection goes back to Nolin 1974. Our goal is her e to formalize and simplify this présentation of algorithm theory. The introduction of a computability notion was induced by the utilization of bundie theory. We build an enumerable algorithm space where ever y object is computable. Résum...