CES Public Seminar China Sept 2008

8/13/2019 CES Public Seminar China Sept 2008

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Model-Based Design ofEmbedded Signal Processing Systems

with Simulink

2008TheMathWorks,

Inc.

September, 2008

Neil Ding,Zhenggao Xu

Zhiqiang Wang

Stella Sun

The MathWorks, Inc.


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Agenda Introduction to Model Based Design

A WiMAX Communications System Design Example

Embedded MATLAB Extend the flexibility and the text programming capability of

MATLAB into Simulink

Build System Models Using Simulink Build an OFDM System a Step by Step Illustration Using Embedded MATLAB Blocks in Simulink Using Existing C Codes in Simulink

Implementation & Verification Fixed Point Design in Simulink C Code Generation and Hardware-in-the-Loop Testing HDL Code Generation and Co-Simulation with ModelSim

Summary


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System Design Challenges

Analyze data, explore ideas, develop algorithms Manage timing and concurrency issues

Understand the system-wide context

Incorporate hardware constraints Test and verify design without final hardware

Iterate back to modify algorithm


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System design requires integration of multipledisciplines, languages, and modeling approaches

Block Diagrams

MATLAB Code

State Machines

C/C++ Code

Modeling Interactions

System Level Effects

Architecture Exploration

System Design

Model BasedDesign Using

MATLAB

&

Simulink


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Requirements and

Specifications

Implementation

Test andVerification

Traditional Development Process

Design


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SpecDesign

ImplementTest

Introduced

Detected

8%

15%

22%

55%

60%

21%

12%

7%0%

10%

20%

30%

40%

50%

60%

70%

Where Errors Are Introduced... and Detected

Source: Migration from Simulation to Verification withModelSim by Paul Yanik. EDA Tech Forum, 2004 Mar 11,Newton MA

Challenge: How to catch errors early?

each delay in thedetection and

correction of a

design error makesit an order ofmagnitude more

expensive to fixClive Maxfield and Kuhoo Goyal

EDA: Where Electronics BeginsTechBites Interactive, October 1, 2001

ISBN: 0971406308


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Requirements and

Specifications Design

Implementation

Test andVerification

Adopting Model-Based Design

AlgorithmsAlgorithms

C, C++C, C++

MCUMCU DSPDSP FPGAFPGA ASICASIC

VHDL, VerilogVHDL, Verilog

Automatic codegeneration- Reduces time, effort

- Enables code reuse- Minimizes coding errors

Generate

Generate Ge

nerate

Generate

System Behavior modelsSystem Behavior models

Environment modelsEnvironment models

Executable models- Unambiguous,

one truth- Links to textual

requirements

Physical

Components models

Physical

Components models



Simulation- Reduces need for

physical prototypes- Enables systematic

what-if analysis


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TestEnvironments

ContinuousT&V

Requirements

Model Based Design Workflow

MCU DSP FPGA ASIC

Embedded

Software

Digital

ElectronicsC, C++ VHDL, Verilog

Implement

Integration

Design

Physical Components

Environment

Algorithms

Generate

Generate


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TestEnvironments

ContinuousT&V

Requirements

MCU DSP FPGA ASIC

EmbeddedSoftware

DigitalElectronics

C, C++ VHDL, Verilog

Implement

Integration

Design

Physical Components

Environment

Algorithms

Generate

Generate


Implementation

with AutomaticCode Generation

Design withSimulation

Executable

Specificationsfrom Models

ContinuousTest and

Verification


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C, C++C, C++

MCUMCU DSPDSP FPGAFPGA ASICASIC

VHDL, VerilogVHDL, Verilog

Automatic codegeneration- Reduces time, effort- Enables code reuse- Minimizes coding errors

Generate

Generate Ge

nerate

Generate

Requirements and

Specifications Design

Implementation


Physical

Components models

Physical

Components models



Simulation- Reduces need for

physical prototypes- Enables systematic

what-if analysis

System Behavior modelsSystem Behavior models


Executable models- Unambiguous,

one truth- Links to textual

requirementsTest andVerification


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A WiMAX Communications System


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Summary


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Embedded MATLAB is the subset of MATLAB language

MATLABEmbedded

cellarrays

dynamically-sized arrays

objects

java

visualization

analysis

arrays

struct

numericfixed-point

dynamic data types

functions

nested functionscomplex

sparse

What is Embedded MATLAB?

Two main purposes

Efficient codegeneration fordeployment in

embedded systems

Acceleration of fixed-point algorithms

Two associatedMATLAB commands:

emlc

emlmex


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Supported MATLAB Features N-dimensional arrays Matrix operations

Subscripting Complex numbers Numeric classes Double-precision, single-precision, and integer math Fixed-point arithmetic If, switch, while, and for statements Sub-functions Persistent variables Structures

Characters Function handles Frames Variable length input and output argument lists

Subset of MATLAB functions Ability to call MATLAB functions


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Unsupported MATLAB Features

Cell arrays

Command/function duality Dynamic variables/Dynamic memory allocations Global variables Java Matrix deletion

Nested functions Objects Sparse matrices Try/catch statements

Other restrictions- For fixed point arithmetic, the word length is limited to32 bits in current release


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Two Main Commands

EMLC

Check for embedded MATLAB compliance Generate C code

Compile to MEX file

Compile to external library

EMLMEX

Check for embedded MATLAB compliance Generate C executable

Compile to MEX file


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EMLC: Generating C-Code from M-Files

1. Examine the original M-code and understand the algorithm

2. Modify the M-code so that it complies with EmbeddedMATLAB

3. Generate C-code using the emlccommand

4. Evaluate the C-code for memory and speed

5. Optimize the compliant M-code as required6. Generate optimized C-code

OriginalM-Code

CompliantM-Code

GenerateC-Code

C-Code

Optimize the M-Code


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EMLMEX: Generating C-MEX Filesfrom M-Files

1. Examine the original M-code and understand the algorithm

2. Modify the M-code so that it complies with Embedded

MATLAB3. Generate C-MEX file using the emlmexcommand

Original

M-Code

Compliant

M-Code

Generate

C-MEX File

Faster

M-Code


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EMLMEX: Two Intended Usages

1. Accelerate fixed-point calculation in MATLAB

Original

M-Code

Compliant

Fixed-Point

M-Code

Generate

C-MEX File

100-1000s

Times

Faster

M-Code

2. Run m-code in Simulink (generate embedded MATLAB block)

- Extend MATLAB functions into Simulink


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MEX vs. EMLMEX

Faster M-codeand

Block in Simulink

Faster M-codePurpose

MATLAB callable

functions

MATLAB callable

functionsResult in

M-filesC filesOperate on

emlmexmexCommand


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Where does Embedded MATLAB fitin MathWorks flow?


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Summary


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Introduction to Simulink

Block-diagram environment Accurately design, implement,

and test:

Control systems

Signal processing systems

Communications systems

Other dynamic systems

Platform for Model-BasedDesign


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Simulink Product KeyFeatures

Extensive and expandablelibraries of predefinedblocks

Hierarchical, component-

based modeling Model/simulate systems Linear & Nonlinear

Hybrid (mixed-signal)/Multi-domain

Multi-rate Multi-tasking

Full MATLAB integration


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Simulink Blocksets

Simulink

Sources Sinks

Continuous

Discrete

Math

Other

Signal Processing

Communications Video and Image Processing

RF


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Signal Processing Blockset Statistics

Multi-rate systems Transforms

Filtering

Estimation


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Communications Blockset

http://www.mathworks.com/products/commblockset/

Comm sources

Comm sinks Source coding

Channel coding

Modulations RF impairments

Comm filters

Equalizers


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Video and Image Processing Blockset

http://www.mathworks.com/products/viprocessing/

Video/image sources

Video/Image sinks 2-D filters

2-D conversions

Geometric transforms 2-D transforms

Motion estimation

I/O techniques


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Other Behavioral Level ModelingPerformance ofcommunications systems are

also significantly impacted byother factors:

RF Effects

State Control


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RF Blockset

Access networks

parameter files of RFcomponents

Intra-cascade

reflections are modeled Frequency response Noise Phase noise

Non-linearity

http://www.mathworks.com/products/rfblockset/


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Stateflow Overview Extend Simulink with a design environment for

developing state machines and flow charts

Design systems containing control, supervisory, andmode logic

Describe logic in a natural and understandable form

with deterministic execution semantic


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Build an OFDM System Model

Understand Simulink blocks

Learning by examples

Art vs. technique

Use Embedded MATLAB blocks

Use existing models, codes and programs

Simulink models

M-code

C-code

Build your own libraries


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Demos: Use Embedded MATLAB Blocksin Simulink

Space-time encoding and decoding in WiMAXcommunication system

Integration of digital pre-distortion into wirelesscommunications systems

From MATLAB to Simulink


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Legacy Code Tool Build SimulinkBlocks Using Existing C Codes

Two Examples A First Order IIR Filter

FFT


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Break (15 minutes)


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Build System Models Using Simulink

Build an OFDM System a Step by Step Illustration

Using Embedded MATLAB Blocks in Simulink

Using Existing C Codes in Simulink

Implementation & Verification

Fixed Point Design in Simulink

C Code Generation and Hardware-in-the-Loop Testing

HDL Code Generation and Co-Simulation with ModelSim

Summary


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Fixed Point Design

Architecture considerations

Implementability

Complexity

Power consumption

Cost Determination of word lengths

Precision

Dynamic range

Resources

Design optimization

Meet requirements at minimum cost


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Fixed Point Design Work Flow

Build Golden Reference

Floating point implementation

Test platform

Perform Fixed Point Design

Architecture

Word lengths

Optimization

Verify the Design Hardware-in-the-loop testing


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Design Example: 16-QAM Transmitter


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Architecture Consideration


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Word Length Determination

Compare BER vs. Eb/No for different word lengths

Log internal min/max signal

values to determine

binary point location


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C Code GenerationImplementation and Verification on General Processors and DSPs

Compile& Link

C/ASM

Code3rd Party

IntegratedDevelopment

Environment

Download

Debug

DSP

MathWorks

Modeling Environment

MATLAB Simulink Comms/VIP

ImplementVerify

Implement and Verify

Embedded IDE Link

Real Time WorkshopEmbedded Coder

Target Support

Package


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16QAM Transmitter:

Behavioral floating-point model Fixed-point model using LUT

Generate C code with

Real-Time WorkshopEmbedded Coder

Verify using Processor-In-Loopsimulation with Embedded IDELink CCfor Code ComposerStudio

Demo - 16QAM Transmitter


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Code Generation: Generated CCS Project

Source Files

Generated Code SuccessfullyBuilt within CCS

Processor Specific Interrupt

Handler and Timer Code


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Processor-In-Loop (PIL) Simulation:TI C6416 DSP


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Simulink HDL Coder Product Features

Generates synthesizable VHDL or Verilog from

subsets of

Simulink models

Simulink Embedded MATLAB blocks

Stateflow

Automatic Test-bench generation


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What Blocks are Supported? Most supported

blocks are low-

level blockstoday

Support forhigher-levelblocks will comein future releases

Use hdllib tobuild a librarywith supported

blocks


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EDA Simulator LinksLink for ModelSim

Link for Cadence Incisive

EDA Simulator Linkis a fast, bidirectional co-

simulation interface

System-level functional verification

Reuse system model as test environment

Modeling

and Simulation

Modeling

and SimulationCosimulation and

Verification

Cosimulation and

Verification HDL SimulationHDL Simulation

MATLABor

Simulink

MATLABor

SimulinkEDA Simulation Link

EDA Simulation LinkEDA SimulatorEDA Simulator


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EDA Simulator LinkBrings Together Leading Tools ForModeling and HDL Simulation

SynthesisSynthesis

Digital

Simulator

Digital

Simulator

HDL Code

Modeling

and Simulation

Modeling

and SimulationCosimulation and

Verification

Cosimulation and

Verification HDL SimulationHDL Simulation

MATLABor

Simulink

MATLABor

Simulink

EDA Simulator LinkEDA Simulator Link

HDL Creation:

IP

Hand-coded

Auto-generated

HDL Creation:

IP

Hand-coded

Auto-generated

Stimulus

TestBench

Response


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Three Viterbi Decoder implementations:

Behavioral floating point model Elaborated fixed point design

HDL implementation code

Verify system BER metricsare being met

Generate HDL code

with Simulink HDL Coder

Co-simulate HDL code with

Link for ModelSimfor ModelSim

Viterbi Decoder Demonstration


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Build System Models Using Simulink

Build an OFDM System a Step by Step Illustration Using Embedded MATLAB Blocks in Simulink

Using Existing C Codes in Simulink

Implementation & Verification

Fixed Point Design in Simulink C Code Generation and Hardware-in-the-Loop Testing

HDL Code Generation and Co-Simulation with ModelSim

Summary


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Summary

Model based design (MBD) is a new concept or approachfor system modeling, design, implementation, test andverification

Simulink is the platform for MBD

Key features of the Simulink are

Hierarchical, component-based modeling Multi-domain, multi-rate

Non-linear and linear

Full MATLAB integration

C and HDL codes can be automatically generated fromSimulink models

Continuous verification can be achieved via processor-in-the-loop, hardware-in-the-loop or co-simulation


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Advantages of Simulink andModel-Based Design

Model elaboration:fixed-point andRF/analog effects

System-levelverification by

reuse of themodels testenvironment

Hierarchical blockdiagrams clearly

convey: Architecture

Interfaces

Concurrency Multirate

Fasterimplementationand fewer codingerrors


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Support and Community


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Consulting from The MathWorks

Engineering expertise and deep product knowledge,

specializing in: Application development using MATLAB technical computing

software

Model-Based Design using Simulink and Stateflowsoftware

Embedded-system development Enterprise-wide integration of MathWorks products into

engineering process and systems

Jumpstart services

Project-based services for a growing number ofindustries, including aerospace and defense, automotive,communications, power and marine, and financial

serviceswww.mathworks.com/consulting


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Training from The MathWorks

Three ways to get training

Public training Offered throughout the world

Schedule and course information at www.mathworks.com/training

Onsite training

Bring training to your site, with course customization available Web-based training

Instructor-led e-learning

Train at work or at home, with flexible dates and times

Example course topics Introductory and intermediate training on MATLAB, Simulink,

and Stateflow

Specialized courses in control design, signal processing, test andmeasurement, communications, financial analysis, and other areas

www.mathworks.com/training


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1. Capture challenges

2. Identify business case*

3. Schedule resources

4. Execute evaluation plan

5. Post-evaluation review

Best Practice: Five-Step Evaluation ofModel-Based Design The MathWorks China

2 C 3

301 : 100190

Tel: +86-10-5982-7000

www.mathworks.cn [email protected]

* See ROI spreadsheet: http://www.edac.org/resources_add_roi.jsp

Seminarend!

Thank you!


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Thank You for Attending!

CES Public Seminar China Sept 2008

Documents

Transcript of CES Public Seminar China Sept 2008