Efficient parallel algorithms and data structures for discrete-event simulation
Abstract
Discrete-event simulation, which is a major tool for analysis, prediction, and training, has been demanding increasingly high computational resources. It has continued to defy an efficient parallel solution. A long-st anding serial bottleneck in parallelizing event-driven simulation ,va.s the shared data structure - event-queue which holds all thP future events. The event-queue is an instance of the abstract data structure~ priority queue. \Ve have developed a noYel parallel data structure called parallel heap for exclusive-read exclusive-write parallel randon1-access 1nachines (ER.EvV PRA11). The parallel heap is the first such data structure to provide an optimal in1plen1entation of the priority quPues. Using p processors, it a.llows deletion of O(p) highest priority items and insertion of O(p) ne,v items, each in O(log n) time, where n is size of the parallel heap. The number of processors can be optimally varied from l through n. Employing th~ parallel heap as the underlying data structure~ we have developed four efficient ERE\\' PR.AN! algorithms for discrete-event simulation. Our three algorithms can sitnula.te O(p) events in O(log n) time using p processors, 1 < p < n, where n is the number of events scheduled in a parallf'l heap. All of our algorithms ensure balanced computational load among the procPssors. Thus .. they are superior to the existing parallel simulation algorith1ns which do not have the advantage of a parallel heap. The parallel h('a.p data structure seems ·applicable in a variety of other application areas also including branch-and-bound algorithms .. nutltiprocessor scheduling, and shortest-pa.th a.lgorithn1s. To explore the experimental aspects of simulation. a parallel time-driven battlefield simulation program has been i1nplemented on an Intel's iPSC-1 simulator. This program is being used to study dynamic sharing of a processor's computational load among its immediate neighbors.
Notes
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Graduation Date
1990
Semester
Summer
Advisor
Deo, Narsingh
Degree
Doctor of Philosophy (Ph.D.)
College
College of Arts and Sciences
Department
Computer Science
Format
Pages
124 p.
Language
English
Length of Campus-only Access
None
Access Status
Doctoral Dissertation (Open Access)
Identifier
DP0027729
Subjects
Arts and Sciences -- Dissertations, Academic; Dissertations, Academic -- Arts and Sciences
STARS Citation
Prasad, Sushil Kumar, "Efficient parallel algorithms and data structures for discrete-event simulation" (1990). Retrospective Theses and Dissertations. 4064.
https://stars.library.ucf.edu/rtd/4064
Accessibility Status
Searchable text