NDLI: Scheduling critical channels in conservative parallel discrete event simulation

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Foreword

Committees

Reviewers

List of Past Chairs

Beyond speedup: PADS, the HLA and Web-based simulation

Path lookahead: a data flow view of PDES models

Scheduling critical channels in conservative parallel discrete event simulation

Case study: parallelizing a sequential simulation model

On event ordering in parallel discrete event simulation

Exploiting temporal uncertainty in parallel and distributed simulations

GVT and scheduling in space time memory based techniques

The high level architecture and beyond: technology challenges

Experience in retrofiting a large sequential Ada simulator to two versions of Time Warp

An auto-adaptive dead reckoning algorithm for distributed interactive simulation

Shock resistant Time Warp

On learning algorithms and balancing loads in Time Warp

Combining periodic and probabilistic checkpointing in optimistic simulation

Fast-software-checkpointing in optimistic simulation: embedding state saving into the event routine instructions

Efficient optimistic parallel simulations using reverse computation

Optimism: not just for event execution anymore

Performance prediction tools for parallel discrete-event simulation

Performance prediction of a parallel simulator

Exploiting model independence for parallel PCS network simulation

Time Warp simulation on clumps

Active virtual network management protocol

Author Index

Scheduling critical channels in conservative parallel discrete event simulation

Content Provider	ACM Digital Library
Author	Simmonds, R. Unger, B. Xiao, Z. Cleary, J.
Abstract	This paper introduces the Critical Channel Traversing (CCT) algorithm, a new scheduling algorithm for both sequential and parallel discrete event simulation. CCT is a general conservative algorithm that is aimed at the simulation of low-granularity network models on shared-memory multi-processor computers.An implementation of the CCT algorithm within a kernel called TasKit has demonstrated excellent performance for large ATM network simulations when compared to previous sequential, optimistic and conservative kernels. TasKit has achieved two to three times speedup on a single processor with respect to a splay tree central-event-list based sequential kernel. On a 16 processor (R8000) Silicon Graphics PowerChallenge, TasKit has achieved an event-rate of 1.2 million events per second and a speedup of 26 relative to the sequential kernel for a large ATM network model.Performance is achieved through a multi-level scheduling scheme that supports the scheduling of large grains of computation even with low-granularity events. Performance is also enhanced by supporting good cache behavior and automatic load balancing.The paper describes the algorithm and its motivation, proves its correctness and briefly presents performance results for TasKit.
Starting Page	20
Ending Page	28
Page Count	9
File Format	PDF
ISBN	0769501559
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	1999-05-01
Access Restriction	Subscribed
Subject Keyword	Atm network modeling parallel simulation conservative pdes optimistic pdes chandy-misra-bryant algorithm time parallelism critical channel traversing algorithm.
Content Type	Text
Resource Type	Article

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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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