id 024c: auto code generation: the shortest distance from · pdf fileshortest distance from...

ID 024C: Auto Code Generation: The Shortest Distance From Idea to Implementation

Christopher Myers

Director of Software Development

12 October 2010

Version: 1.1

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Christopher Myers cmyers@simuquest.com

� Director of Software Development

� Responsible for designing and managing development

of SimuQuest product lines

� Lead Developer of QuantiPhi, a line of code generation

tools that bring a hardware interface into the Simulink

modeling environment.

PREVIOUS EXPERIENCE:

� Working in the area of model-based development

using MATLAB / Simulink since 2003.

� Production automotive and consumer electronics

experience at Motorola since 2000.

� Designed high-performance network appliances

designed to provide unparalleled visibility into

network usage while at Arbor Networks, Inc.

� MS, BS from the University of Michigan

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Renesas Technology and Solution Portfolio

Microcontrollers

& Microprocessors#1 Market share

worldwide *

Analog and

Power Devices#1 Market share

in low-voltage

MOSFET**

Solutions

for

Innovation

Solutions

for

InnovationASIC, ASSP

& MemoryAdvanced and

proven technologies

* MCU: 31% revenue

basis from Gartner

"Semiconductor

Applications Worldwide

Annual Market Share:

Database" 25

March 2010

** Power MOSFET: 17.1%

on unit basis from

Marketing Eye 2009

(17.1% on unit basis).

44

Renesas Technology and Solution Portfolio

Microcontrollers

& Microprocessors#1 Market share

worldwide *

Analog and

Power Devices#1 Market share

in low-voltage

MOSFET**

ASIC, ASSP

& MemoryAdvanced and

proven technologies

* MCU: 31% revenue

basis from Gartner

"Semiconductor

Applications Worldwide

Annual Market Share:

Database" 25

March 2010

** Power MOSFET: 17.1%

on unit basis from

Marketing Eye 2009

(17.1% on unit basis).

Solutions

for

Innovation

Solutions

for

Innovation

55

Microcontroller and Microprocessor Line-up

Superscalar, MMU, Multimedia� Up to 1200 DMIPS, 45, 65 & 90nm process

� Video and audio processing on Linux

� Server, Industrial & Automotive

� Up to 500 DMIPS, 150 & 90nm process

� 600uA/MHz, 1.5 uA standby

� Medical, Automotive & Industrial

� Legacy Cores

� Next-generation migration to RX

High Performance CPU, FPU, DSC

Embedded Security

� Up to 10 DMIPS, 130nm process

� 350 uA/MHz, 1uA standby

� Capacitive touch

� Up to 25 DMIPS, 150nm process

� 190 uA/MHz, 0.3uA standby

� Application-specific integration

� Up to 25 DMIPS, 180, 90nm process

� 1mA/MHz, 100uA standby

� Crypto engine, Hardware security

� Up to 165 DMIPS, 90nm process

� 500uA/MHz, 2.5 uA standby

� Ethernet, CAN, USB, Motor Control, TFT Display

High Performance CPU, Low Power

Ultra Low PowerGeneral Purpose

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Microcontroller and Microprocessor Line-up

Superscalar, MMU, Multimedia� Up to 1200 DMIPS, 45, 65 & 90nm process

� Video and audio processing on Linux

� Server, Industrial & Automotive

� Up to 500 DMIPS, 150 & 90nm process

� 600uA/MHz, 1.5 uA standby

� Medical, Automotive & Industrial

� Legacy Cores

� Next-generation migration to RX

High Performance CPU, FPU, DSC

Embedded Security

� Up to 10 DMIPS, 130nm process

� 350 uA/MHz, 1uA standby

� Capacitive touch

� Up to 25 DMIPS, 150nm process

� 190 uA/MHz, 0.3uA standby

� Application-specific integration

� Up to 25 DMIPS, 180, 90nm process

� 1mA/MHz, 100uA standby

� Crypto engine, Hardware security

� Up to 165 DMIPS, 90nm process

� 500uA/MHz, 2.5 uA standby

� Ethernet, CAN, USB, Motor Control, TFT Display

High Performance CPU, Low Power

Ultra Low PowerGeneral Purpose

7

I n n o v a t i o n : I n n o v a t e F a s t e r

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Model-Based Design

Model-Based Design and Automatic Code Generation is the

future of embedded controls. SimuQuest believes that as

companies across all industries realize the innovation

advantage that it provides, it will play a part in the design of

nearly all embedded systems worldwide.

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Agenda

� Introduction to modeling and auto-code

� Examples of Simulink / Stateflow

� Exploration of design concerns

� Fixed-point vs. floating point

� Integrating hand code with auto-code

� Modeling an entire application: One-Touch code generation

� Q&A

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Agenda (in other words)

� Make the case for modeling and auto-code

� Show you what modeling and auto-code is all about

� Show you just how far it can be taken

� Answer questions

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Key Takeaways

� Models helps define requirements

� Models can be auto-coded

� You can use that C code flexibly

� Auto-coding is powerful

� Auto-coding saves you time

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Auto-Code Generation: Why

Software PerspectiveControls Perspective

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Modeling: A Software Perspective

Software PerspectiveControls Perspective

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Typical Project

Kick-Off Delivery

Effort

Time

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Ideal Project

Kick-Off Delivery

Effort

Time

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Dollars and Cents Advantage

SOFTWARE DEFECT COSTS

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Why Typical Approaches Don’t Work!

Req 1.6.5.9.1.2.3 - Lorem ipsum dolor sit amet, consectetur adipiscing elit. Praesent ut orci nulla. Aenean nulla metus, blandit eget blandit vitae, commodo sit amet metus. Mauris lacinia varius dui, quis dictum nisi aliquet vitae. Lorem ipsum dolor sit amet, consectetur adipiscing elit. Integer nisi nunc, blandit vitae porta vitae, faucibus sit amet neque…

Use Case 1

Use Case n

Or…

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A Model-Based Approach

� Understand the system we’ll be interacting with. Model it.

� Develop executable models of system requirements

� Integrate early and often

� Bring pre-tested hardware drivers into the modeling environment

� Auto-generate code

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Modeling: A Controls Perspective

Software PerspectiveControls Perspective

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Why Auto-Code Generation: R&D

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Modeling: Auto-Coding

Software PerspectiveControls Perspective

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Our Auto-Coding Toolbox

MATLAB

QuantiPhiRTW Embedded Coder

Simulink & Stateflow

Base computing platform

Modeling platform

Auto-code generation Provides MCU configuration

and device drivers.

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Building Block: The Feature

Feature

Determine a set point

Condition a user input

Detect a faultDetect a fault

Compute value for an actuator

inputs outputs

triggers

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An Example Feature Model

[In Simulink]

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What About Integrating the Code?

FeatureData Types

Variables

File Naming

Legacy Code

Target

New Concerns!

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What About Integrating the Code?

FeatureData Types

Variables

File Naming

Legacy Code

Target

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C to Simulink Mappings

C Types

unsigned char

unsigned char

char

unsigned short int

short int

unsigned long int

long int

float

double

Simulink Types

boolean

uint8

int8

uint16

int16

uint32

int32

single

double

+ additional fixed-point types available

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Data Types: Floating and Fixed Point

float my_var = 3.57; float my_var = 3.57;

FPU No FPU

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Data Types: Floating and Fixed Point

*IEEE754

1

float*

uint16 0 0 1110000000000

Artificial binary point

ufix16_En4

1 1 0 01010111100011 1 0 0 10

00000001

0

0

Value to represent: 3.57

uint16 3 57

Artificial decimal point

(understood that number is 100x higher than real value)

ufix16_Sp01

3 . (0.5 + 0.0625)

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Data Types (+Fixed Point) in Simulink

[In Simulink]

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Auto-Coding for Different-Sized Targets

FeatureData Types

Variables

File Naming

Legacy Code

Target

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More Control Over Generated Code

FeatureData Types

Variables

File Naming

Legacy Code

Target

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More Control Over Generated Code

� Simple: Can control variable’s:

� Placement in RAM / ROM

� Class (const, volatile, etc)

� Naming

� Scope (global vs. local)

� Advanced: Can control variable’s:

� Declaration

� Definition

� Code needed to read

� Code needed to write

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More Control Over Generated Code (Cont’d)

� Simple: Can control subsystem’s:

� Name of the file containing its code

� Name of the generated function

� Advanced: Can control subsystem’s:

� Placement in memory (near vs. far for example)

� RAM / ROM variable placement in memory

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Legacy Code

FeatureData Types

Variables

File Naming

Legacy Code

Target

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Legacy Code

Feature Backed

By Legacy Codeinputs outputs

triggers

[Go to Simulink]

Step 1:

Simulation Behavior

Step 2:

Code Generation Behavior

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Typical Auto-Coding Methodologies

Feature Effort =

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Typical Auto-Coding Methodologies

Feature 1

Feature n

“Application Layer”

Effort =

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Typical Auto-Coding Methodologies

Feature 1

Feature n

Hardware

Interface

Effort =

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Convinced?

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The Next Step

Feature 1

Feature n

Hardware

Interface

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A

B C

Interfacing With Hardware

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Interfacing With Hardware

A

B C

PA0

RPM

pwm0

QuantiPhi

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Hardware Abstraction Layer

� Example of a digital debounce:

45

Another Hardware Abstraction Layer Example

� Example of analog counts to engineering units:

46

A “One Touch” Example Using QuantiPhi

[In Simulink]

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Innovation: Innovate Faster

48

Related Lab

[In Simulink]

021L: Model Based Control Design

and Auto Code Generation using the R8C

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Questions?

50

Thank You!