parallel discrete event simulation of manufacturing systems using parsec n.
Skip this Video
Loading SlideShow in 5 Seconds..
Parallel Discrete Event Simulation of Manufacturing Systems using PARSEC PowerPoint Presentation
Download Presentation
Parallel Discrete Event Simulation of Manufacturing Systems using PARSEC

Loading in 2 Seconds...

play fullscreen
1 / 15

Parallel Discrete Event Simulation of Manufacturing Systems using PARSEC - PowerPoint PPT Presentation

  • Updated on

Parallel Discrete Event Simulation of Manufacturing Systems using PARSEC. Ye ZHANG, Wentong CAI & Stephen J. TURNER School of Applied Science, Nanyang Technological University, Singapore 639798 Structure of the Talk. Introduction & Research Aims

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
Download Presentation

Parallel Discrete Event Simulation of Manufacturing Systems using PARSEC

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
parallel discrete event simulation of manufacturing systems using parsec

Parallel Discrete Event Simulationof Manufacturing Systemsusing PARSEC

Ye ZHANG, Wentong CAI & Stephen J. TURNER

School of Applied Science,

Nanyang Technological University,

Singapore 639798

structure of the talk
Structure of the Talk
  • Introduction & Research Aims
  • PARSEC Simulation Language
  • Manufacturing Simulation
    • Setup Rule
    • Implementation using PARSEC
  • Performance Results
    • Overhead Comparison
    • Speed Up
  • Conclusions and Future Work
    • POMSim
  • Parallel Discrete Event Simulation (PDES) Languages
    • A number of PDES languages have been developed in recent years, e.g. PARSEC, TeD, APOSTLE.
    • Most of these languages are general purpose languages and lack features to support special models, such as those found in manufacturing simulation.
  • Semiconductor Manufacturing Simulation
    • Our study focuses on the simulation of wafer fabrication processes.
    • One feature that complicates the simulation is the implementation of dispatching and setup rules to determine the scheduling of products.
research aims
Research Aims
  • Research Aims
    • The aim of this paper is to study how such scheduling rules may be implemented in a general purpose parallel simulation language, such as PARSEC.
    • PARSEC was chosen for its availability, simplicity and efficient event scheduling mechanism.
    • The performance of different implementation alternatives of a wafer fabrication simulation are compared.
    • A further aim is to determine what features should be provided in a parallel simulation language designed specifically for manufacturing simulation.
parsec simulation language
PARSEC Simulation Language
  • Buffered Message Passing
    • Developed at UCLA, PARSEC separates the simulation model from the underlying simulation protocol (e.g. sequential, parallel conservative, parallel optimistic).
    • Simulation entities communicate with each other using buffered message passing and guards.

message Request {int count;}

Entity E0:

send Request {2} to E1

after T;

Entity E1:

receive (Request req)

when (req.count <= units)

{ … … }

or timeout in (delay_time);


manufacturing simulation
Manufacturing Simulation
  • Semiconductor Manufacturing
    • The wafer fabrication simulation model is based on the Sematech Data Modeling Standard (DMS).
    • Wafer fabrication is described by a product route consisting of a number of processing steps.
    • Each step specifies a machine set, where each machine set consists of a number of identical machines.
    • Machines may have a setup that can be changed and may be used in different steps.
    • In each step, a free machine with matching setup will be chosen where possible.
scheduling rules
Scheduling Rules
  • Setup Rule
    • This is implemented by a guard in the receive clause for the LotArrive message which calls setuprule:
    • Lot processing is delayed until setuprule returns 1.

int setuprule(LOT lot, int curTime) {

... ...

if ( numfreemachine() != 0 ) {

if ( matchingsetup(lot) ) return 1;


if ( (curTime - lot.simClock) >= MAXWAIT )

return 1;

else return 0;

else return 0;


implementation using parsec
Implementation using PARSEC
  • Design Issues
    • How are machine sets mapped to PARSEC entities?
    • How is simulation time advanced so that the setup of the machine is changed when MAXWAIT is reached?
  • Implementation Alternatives
    • Versions 1, 2 and 3: each machine set is mapped to its own PARSEC entity.
    • Versions 4, 5 and 6: multiple machine sets are mapped to a single PARSEC entity using partitioning that aims to balance the workload and maximize lookahead.
    • PARSEC maps entities to physical processors using a round robin policy.
implementation using parsec1
Implementation using PARSEC
  • Advancing Simulation Time
    • Versions 1 & 4: use timeout(1) to advance simulation time when no receive clause is enabled (note that we cannot use timeout(MAXWAIT) as a lot may already have spent some time in the message buffer).
    • Versions 2 & 5: use a Sync message in addition to the LotArrive message to schedule a TimeOut message that is received when the setup should be changed.
    • Versions 3 & 6: use a user-defined lot queue to hold the waiting lots instead of PARSEC’s message buffer, together with a TimeOut message (note that the lots are now received without a guard and the setuprule is applied to the lots in the internal queue)
performance results
Performance Results
  • Simulation Experiments
    • A number of experiments were carried out to compare the performance of the different implementation alternatives.
    • The dataset used is provided by Sematech and comes from an actual manufacturing system.
    • Experiments were carried out on a 4-CPU (250 MHz) Sun Enterprise 3000.
    • For the parallel execution, the conservative null-message protocol was used.
    • Spin-loops were used to investigate the effect of the granularity of event processing on performance.
overhead comparison

Version Event Execution Over- Percentage

Time Time head %

(secs) (secs) (secs)

1 0.156 26.18 26.02 99

2 0.198 2.44 2.242 91

3 0.150 5.40 5.25 97

4/4 Partitions 0.120 10.11 9.98 99

4/8 Partitions 0.117 9.92 9.80 99

4/16 Partitions 0.118 12.38 12.26 99

5/4 Partitions 0.164 5.20 5.03 97

5/8 Partitions 0.154 3.12 2.97 95

5/16 Partitions 0.162 3.04 2.88 95

6/4 Partitions 0.130 5.29 5.16 98

6/8 Partitions 0.112 5.37 5.26 98

6/16 Partitions 0.120 6.40 6.28 98

Overhead Comparison

sequential, spin loop = 0

conclusions and future work
Conclusions and Future Work
  • Conclusions
    • The different implementation versions have different degrees of impact on the performance.
    • The versions using user-defined TimeOut messages give better results than the versions using timeout(1).
    • For the versions that map multiple machine sets to a single PARSEC entity, using 8 partitions generally gives the best performance.
  • Future Work
    • To develop extensions to PARSEC for the easy specification of dispatching and setup rules.
    • POMSim - a Parallel Object-oriented Manufacturing Simulation Language.