Abstract not found

In the last three decades a considerable amount of research has been pursued in the efficient implementation of the pending event set (PES) associated with discrete-event simulation. The reason is simple: a fast event management has a very crucial impact in the total running time of both sequential and parallel simulations. This report focuses on this problem by studying the empirical performance of a number of solutions to the PES implementation in which we include a complete binary tree described in [26], 1 Introduction The PES is defined as the set of all the events generated during a discrete-event simulation and whose occurrence have not been simulated yet. In order to determine the next event to take place, it is necessary to extract the event with the least time from the PES. We call this operation extract-min. On the other hand, the occurrence of any event during the simulation can produce the insertion of new pending or future events in the PES; insert operation. These two b...

this paper we study the performance of the very first tournament based complete binary tree. We focus on discrete-event simulation and our results show that this unknown predecessor of heaps can be a more efficient alternative to the fastest pending event set implementations reported in the literature. We also extend the idea of binary tournaments to a (2; L)-tournament structure which exhibits the property of delaying the processing of events with larger timestamps whilst it keeps similar theoretical performance bounds to the native (2; 1)-structure or CBT. This property can be certainly useful in systems where many pending events are expected to be deleted or rescheduled during the simulation. 2 Tournament trees

Low run-time overhead, self-adapting storage policies for priority queues called Smart Priority Queue (SPQ) techniques are developed and evaluated. The proposed SPQ policies employ a low-complexity linear queue for near-head activities and a rapid-indexing variable bin-width calendar queue for distant events. The SPQ configuration is determined by monitoring queue access behavior using cost-scoring factors and then applying heuristics to adjust the organization of the underlying data structures. We show that optimizing storage to the spatial distribution of queue access can decrease HOLD operation cost between 25 % and 250 % over existing algorithms such as calendar queues. An SPQ-based scheduler for discrete event simulation has been implemented and was used to evaluate the resulting efficiency, components of access time, and queue usage distributions of the existing and proposed algorithms.

The bulk-synchronous parallel (BSP) model of computing has been proposed to enable the development of portable software which achieves scalable performance across diverse parallel architectures. A number of applications of computing science have been demonstrated to be efficiently supported by the BSP model in practice.

Abstract not found