Parallel discrete event simulation: A shared memory approach

With traditional event list techniques, evaluating a detailed discrete event simulation model can often require hours or even days of computation time. Parallel simulation mimics the interacting servers and queues of a real system by assigning each simulated entity to a processor. By eliminating the event list and maintaining only sufficient synchronization to insure causality, parallel simulation can potentially provide speedups that are linear in the number of processors. A set of shared memory experiments is presented using the Chandy-Misra distributed simulation algorithm to simulate networks of queues. Parameters include queueing network topology and routing probabilities, number of processors, and assignment of network nodes to processors. These experiments show that Chandy-Misra distributed simulation is a questionable alternative to sequential simulation of most queueing network models

Synthesis of a simple self-stabilizing system

With the increasing importance of distributed systems as a computing paradigm, a systematic approach to their design is needed. Although the area of formal verification has made enormous advances towards this goal, the resulting functionalities are limited to detecting problems in a particular design. By means of a classical example, we illustrate a simple template-based approach to computer-aided design of distributed systems based on leveraging the well-known technique of bounded model checking to the synthesis setting.Comment: In Proceedings SYNT 2014, arXiv:1407.493

The combinatorics of resource sharing

We discuss general models of resource-sharing computations, with emphasis on the combinatorial structures and concepts that underlie the various deadlock models that have been proposed, the design of algorithms and deadlock-handling policies, and concurrency issues. These structures are mostly graph-theoretic in nature, or partially ordered sets for the establishment of priorities among processes and acquisition orders on resources. We also discuss graph-coloring concepts as they relate to resource sharing.Comment: R. Correa et alii (eds.), Models for Parallel and Distributed Computation, pp. 27-52. Kluwer Academic Publishers, Dordrecht, The Netherlands, 200