Using ModelSim, Matlab/Simulink and NS for Simulation of ...publications.eas.iis.fraunhofer.de/papers/2004/021/slides.pdf · IIS Fraunhofer Institut Integrierte Schaltungen U. Hatnik,

IIS

Fraunhofer InstitutIntegrierte Schaltungen

U. Hatnik, S. Altmann

Fraunhofer Gesellschaft EAS/IIS

SDA 20048. September 2004

Using ModelSim, Matlab/Simulink and NS forSimulation of Distributed Systems

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Outline

• Motivation

• Requirements

• Object Oriented Simulation

• Objects and Object Structure

• Open Model Interface

• Object Communication Versions

• Conclusions

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Motivation

Analysis of communication systems through abstract network simulation

• Analysis of workload, bottlenecks,

reserves and configurations

• Guarantee of the Quality of Service

• Effects of distributed services

• Development of new protocols

• Error simulation

Server

Network(WAN, LAN)

Clients

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z−1 +

0 k

z−1 +

1k kk 0 1

+ +

Motivation

Detailed simulation of single components of a distributed system

• Development of new soft- and hardware

e.g. network adapter, protocol accelerator,

signal processing algorithms

• Exploration of existing components

e.g. with hardware debugger

• Simplification of the design process

• Validation and test

• Fault diagnostics

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Motivation

Network Simulator NS-2:

• Based on abstract models, without real reference data

• Provided with extensive libraries (e.g. protocols, transmission lines)

• Not well suited for circuit simulation (absence of libraries, languages, tools)

VHDL/Verilog Simulator ModelSim:

• Modelling with low abstraction level possible

• Provided with extensive circuit libraries

• Not well suited to simulate communication networks

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Motivation

Matlab/Simulink

• Models mainly based on differential and difference equations

• More and more libraries and toolboxes available (e. g. for signal processing)

• Not well suited to simulate circuits or for protocol development

Real system components, e. g. User-Mode Linux:

• If no model available

• If real stimuli data necessary

• For validation and test (comparison of real components and models)

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Requirements for a Suitable Simulation Environment

• Combination of models with different abstraction levels

• Less restrictions in terms of modelling languages

• Good extensibility (models, simulation algorithms)

• High flexibility at low complexity of the framework

• Integration of soft- und hardware components

• Distributed simulation

=> Coupling of Simulators

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Obj. 2.2Obj. 2.1

Obj. 3.2Obj. 3.1

Obj. 1

Interface

Sim. Algorithm

Object

other Objects

Model

The Object Oriented Approach

• Partitioning of the system

• Object is equivalent to subsystem

• Object = Model + Simulator + Interface

• Object can use further objects

• Object encapsules implementation details

=> Simple replacement of objects

=> Object implementation can be changed easily

=> Integration of real soft- and hardware possible

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Top Level View

Network Model

Server

Network(WAN, LAN)

Clients

S SS

C CC

Server Models

Client Models

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The Network Simulator NS Version 2

• LAN, WAN, mobile- and satellit networks

• Simulator- and model implementation with oTcl and C++

• Library and examples (protocols, network types etc.)

• Dynamic scenarios

• Animation tool NAM

• Free software, source code available

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The Network Simulator NS Version 2

NetworkSimulatorNS-2

C C C

S S S

Top Level System Model

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Top Level Object

Interface

NetworkSimulator


NS-2

C C C

S S S

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Detailed Simulation of a single Component

I1I2

I3

I4I5

O1

O2

Network Model

S SS

C CC

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ModelSim Object

E1E2

E3

E4E5

A1

A2

VHDL / VerilogSimulatorModelSim

hardwarecomponent

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ModelSim Object

Interface

VHDL / VerilogSimulatorModelSim

E1E2

E3

E4E5

A1

A2

hardwarecomponent

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Matlab/Simulink Object

Matlab/Simulink

signal processing

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Matlab/Simulink Object

Matlab/Simulink

signal processing

Interface

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Applications

User Mode LinuxSystem 1

Virtual Network Module

Applications


Linux System

User Mode Linux Object

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User Mode Linux Object

Interface

Applications


Virtual Network Module

Applications


Linux System

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Object StructureInterface



C C C

S S S

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Object Structure

Interface

E1E2

E3

E4E5

A1

A2ModelSim HardwareComponent

Interface



C C C

S S S

Interface

E1E2

E3

E4E5

A1


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Object Structure

Interface

E1E2

E3

E4E5

A1


Interface



C C C

S S S

Interface

E1E2

E3

E4E5

A1


Interface

System

Applications

User Mode LinuxSystems

Software

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Object Structure

Interface

E1E2

E3

E4E5

A1

A2ModelSim

Interface

Matlab/Simulink Signal Processing

Hardware

Algorithm

Component

Interface



C C C

S S S

Interface

E1E2

E3

E4E5

A1


Interface

System

Applications


Software

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Object Structure

Interface

E1E2

E3

E4E5

A1

A2ModelSim

Interface


Hardware

Algorithm

Component

Interface



C C C

S S S

Interface

E1E2

E3

E4E5

A1


Interface

System

Applications


Software

Interface

System Hardware FPGA

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Object Structure

Interface

E1E2

E3

E4E5

A1

A2ModelSim

Interface


Hardware

Algorithm

Component

Interface



C C C

S S S

Interface

E1E2

E3

E4E5

A1


Interface

System

Applications


Software

Interface

System Hardware FPGA

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Open Model Interface (OMI)

• IEEE standard

• Object oriented approach

• Open and independent interface

• Dynamic simulation control

• Intellectual property (IP) protection

• Visibility of intern signals

• Licence and version management

• Flexible model creation

• Model query functions

Properties:

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Basic Structure of the Open Model Interface

Model Manager

OMILibrary

Model 1

Model 2

Instance 1 Instance 2 Instance 3

Application

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Model Manager

OMILibrary

Model 1

Model 2

Instance 1 Instance 2 Instance 3

Interface



C C C

S S S

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Model Manager

OMI

E1E2

E3

E4E5

A1


System

Applications


SoftwareMatlab/Simulink Signal Processing

Algorithm

Interface



C C C

S S S

Library

Model 1

Model 2

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Model Manager

OMI

E1E2

E3

E4E5

A1


System

Applications



Algorithm

Interface



C C C

S S S

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Model Manager

OMI

TCP/IP-Sockets

E1E2

E3

E4E5

A1


System

Applications



Algorithm

Interface



C C C

S S S

(PVM, CORBA, HLA)

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Object Communication Versions

• TCP/IP-Sockets(high effort, dependent on platform)

• Parallel Virtual Machine (PVM)(low effort, independent of platform)

• High Level Architecture (HLA)(developed especially for simulator coupling, mechanism for synchronisation)

• Common Object Request Broker Architecture (CORBA)(transparent coupling of distributed objects, client server architectur)

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Conclusions

• Simulation of distributed systems via simulator coupling

=> Combination of suitable simulators (abstraction level,

modelling language, available libraries)

• OOS approach (autonomous objects, optimale adaption on requirements,

integration of real soft- and hardware components possible)

• OMI (interface standard for object coupling)

• Object communication via TCP/IP-Sockets

=> distributed simulation is easily possible

• Further coupling methods possible (PVM, CORBA, HLA)

• Very flexible and user comfortable simulation environment

Documents

Using ModelSim, Matlab/Simulink and NS for Simulation of ...publications.eas.iis.fraunhofer.de/papers/2004/021/slides.pdf · IIS Fraunhofer Institut Integrierte Schaltungen U. Hatnik,