Modelling Hardware and Software for Fast Serial Interprocessor

Modelling Hardware and Software for Fast Serial

Interprocessor Communication

Wolfgang Fengler, Bernd Dä[email protected]

tu-ilmenau.de/ra

Ilmenau Technical University

Modelling Hardware and Software for Fast Serial Interprocessor Communication 2

Topics

1. Introduction

2. The Project

3. The Model

4. Comparison of Results

5. Conclusion

This work is supported by German Research Council (DFG) under SFB 622.Some figures are taken from: MLDesigner, Copyright (C) 2006 MLDesign Technologies, Inc. All rights reserved.


1. Introduction

Efficiency of model based design depends on availibility of accurate models for all system components

Off-the-shelf components often provide functio-nal descriptions but no formal models

Design model must combine parts derived from different sources

Case study will investigate modelling process within a real project


2. The Project: Hardware Platform

Multiprocessor DSP system:• TMS320C67x family (Texas Instruments)• Up to six processing nodes• Controls high precision measurement machines

McBSP (Multichannel Buffered Serial Port):• Fast inter-node communication (ca. 83 Mbit/s)• Communication hardware included in processors• Special protocol and wiring needed when connecting

more then two units


Modelling Tool

Modelling tool under consideration:MLDesigner ® from MLDesign Technologies, Inc.

Hierarchical multi domain modelling framework

Covers module, system and strategy levels

Capabilities for simulation, design check, export

Derived from well-known Ptolemy tool (University of Berkeley)


MLDesigner Sample Workspace


Design Goal

Add serial communication functionality to actual system:• Medium shared: up to five participants

• Software solution (protocol implementation, API)

Case study for modelling:• Combine overall model from parts contributed differently

• Compare results of modelling and implementation processes


3. The Model

Covers hardware functions, interconnections, protocols, software strategies

Combines information derived from different sources and represented differently

Models for hardware functions derived from documentation and experiments

Models for protocols and software functions derived from actual design process

Model partly shown in top-down manner


Top Level of Model

Slave nodes next slideMaster node


Structure of Slave NodeBehavioral software model

DMA modules

McBSP modules

next slide

Standard element


Structure of McBSP ModuleTransmit circuitry

Receive circuitry

Sample rate generator

next slide


Structure of Sample Rate Generator

Configuration register(parametrized constant)

Synchronizationcircuitry

Frame pulse generatornext slide


Structure of Frame Pulse Generator

Bottom level

Standard elements only


Modelling Software Functions

Software functions modelled by behaviour

Implement communication protocols and test transfers

Interrupt sequences included

Hardware blocks controlled by configura-tion registers


Top Level Software Model for Slave Node


4. Comparison of Results

Model evaluated by simulation

Actual system evaluated by measurement

Comparisons:• Qualitative (e.g. signal sequences)

• Quantitative (e.g. data rates)

Good matching found


Simulation Result in Multichannel Mode


Signals Measured in Multichannel Mode


Data Rates: Simulation vs. Measurement

Configuration Data Rates [Mbit/s]

Device # Channels Block Size Simulated Measured

32 Byte 51.6 50.7

64 kByte 52.9 52.8

32 Byte 12.7 12.4

64 kByte 13.1 12.9

32 Byte 68.7 67.2

64 kByte 71.1 71.2

32 Byte 17.0 16.3

64 kByte 17.8 17.64

1TMS320C6713

300 MHz

4

1TMS320C6701

167 MHz


Hardware Setup


5. Conclusion

Method developed for combined modelling:• Hardware: off-the-shelf, own• Software

Method applied to real design project

Design model combined parts derived from different sources

In case study modelling process validated by comparison of results


Further Work

Combine several functional aspects of the DSP system into one model

Include controlled process and its environ-ment into the model

Generate software from the model

Develop methodical framework for model-ling processes

Modelling Hardware and Software for Fast Serial Interprocessor

Documents

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