simulation@uflorida.cis.ufl.edu (Moderator: Paul Fishwick) (02/27/90)
Volume: 14, Issue: 4, Mon Feb 26 16:32:34 EST 1990
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| TODAY'S TOPICS |
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(1) RE: High Level Design
(2) TR: Time Warp Method
(3) SmartModel on HP Workstations
* Moderator: Paul Fishwick, Univ. of Florida
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Date: Thu, 22 Feb 90 15:18 MST
From: ROZENBLIT%EVAX2@Arizona.EDU
Subject: IN reply to Wolfgang Mueller----High Level Design
To: simulation@bikini.cis.ufl.EDU
X-Envelope-To: simulation@bikini.cis.ufl.EDU
X-Vms-To: IN::"simulation@bikini.cis.ufl.edu"
SUMMARY OF RESEARCH IN KNOWLEDGE-BASED
SYSTEM DESIGN AND SIMULATION
Our research employs Artificial Intelligence and
Multifacetted Simulation Modelling to unify engineering design
activities and develop a methodology for systematic simulation
model construction and evaluation. The methodology is based on
codifying appropriate decompositions, taxonomic, and coupling
relationships. This constitutes declarative design knowledge
base. Beyond this, we provide the procedural knowledge base in
the form of production rules used to process the elements in a
design domain.
As a step toward a complete knowledge representation scheme,
we have combined the decomposition, taxonomic, and coupling
relationships in a representation scheme called the system entity
structure, a declarative scheme related to frame-theoretic and
object-based representations. The entities of the entity
structure refer to conceptual components of reality for which
models may reside in the model base. Also associated with
entities are slots for attribute knowledge representation. An
entity may have several aspects, each denoting a decomposition,
and therefore having several entities. An entity may also have
several specializations, each representing a classification of
the possible variants of the entity. The generative capability
of the entity structure enables convenient generation and
representation of model attributes at multiple levels of
aggregation and abstraction.
A primary application of the above knowledge representation
scheme is the objectives-driven development of simulation models.
In this approach, a model is synthesized from components
identified through the system entity structure and stored in the
model base. The synthesis process is guided by project's
objectives, requirements, and constraints. The objectives guide a
pruning process which reduces the entity structure to one or more
composition trees from which models may be hierarchically built
up from atomic components. Constraints, expressed in the form of
production rules and placed on the aspects of the entity
structure, restrict the family of possible pruned structures for
more informed search.
Performance of design models is evaluated through computer
simulation in DEVS-Scheme environment. DEVS-Scheme is an object-
oriented simulation environment for modeling and design
that facilitates construction of families of models in a
form easily reusable by retrieval from a model base. Models are
evaluated in respective experimental frames. An experimental
frame defines a set of input, control, output, and summary
variables. Those objects specify conditions under which a model
is simulated and observed. The environment supports construction
of distributed, hierarchical discrete event models and is
written in the PC-Scheme language which runs on IBM compatible
microcomputers and AI Workstations.
We have been validating the above methodology in case
studies involving design and simulation of distributed computer
architectures, local area networks, and more recently, VLSI
packages.
For more information, please contact:
Jerzy W. Rozenblit or Bernard P. Zeigler
Dept. of ECE, Bldg #4
University of Arizona
Tucson, AZ 85721
rozenblit@arizevax.bitnet
zeigler@arizevax.bitnet
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Date: Fri, 23 Feb 90 17:59:41 -0800
From: liny@cs.washington.edu (Yi-Bing Lin)
Return-Path: <liny@cs.washington.edu>
To: fishwick@bikini.cis.ufl.edu
The following technical report can be requested via
e-mail: liny@cs.washington.edu
Reducing the State Saving Overhead For Time Warp Parallel Simulation
Yi-Bing Lin and Edward D. Lazowska
Department of Computer Science and Engineering
University of Washington
Seattle, WA 98195
Abstract
The Time Warp mechanism is the most common ``optimistic'' parallel
simulation protocol. A process executes every message as soon as it
arrives. If a message with a smaller timestamp subsequently arrives,
the process rolls back its state to the time of the earlier message
and re-executes from that point.
Clearly, the state of each process must be saved (checkpointed)
regularly in case rollback is necessary. Although most existing Time
Warp implementations checkpoint after every state transition, this is
not necessary, and the checkpoint interval is in reality a tuning
parameter of the simulation.
In a previous paper, we derived the optimal frequency of checkpointing
in Time Warp simulation based on a specific assumption concerning the
rollback distance distribution. This paper derives distribution-free
bounds for the state saving overhead. Using these bounds, we are able
to select a checkpoint interval which minimizes the state saving
overhead. High accuracy for our approach is shown in an experimental
study.
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Date: Thu, 22 Feb 90 16:32:29 EST
From: mitel!spock!tsuia@uunet.UU.NET (Alan Tsui)
To: uunet!bikini.cis.ufl.edu!simulation@uunet.UU.NET
Subject: SmartModel
I would like to know anyone has used SmartModel with System HILO
(on HP workstation). How easy is it to use? Are they significant
better than HILO models? Why?
Thanks.
Alan
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