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

Transcription

1 ID 024C: Auto Code Generation: The Shortest Distance From Idea to Implementation Christopher Myers Director of Software Development 12 October 2010 Version: 1.1

2 Christopher Myers 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 Production automotive and consumer electronics experience at Motorola since 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 2

3 Renesas Technology and Solution Portfolio Microcontrollers & Microprocessors #1 Market share worldwide * ASIC, ASSP & Memory Advanced and proven technologies Solutions for Innovation Analog and Power Devices #1 Market share in low-voltage MOSFET** * 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). 3

4 Renesas Technology and Solution Portfolio Microcontrollers & Microprocessors #1 Market share worldwide * ASIC, ASSP & Memory Advanced and proven technologies Solutions for Innovation Analog and Power Devices #1 Market share in low-voltage MOSFET** * 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). 4

5 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 High Performance CPU, Low Power Up to 500 DMIPS, 150 & 90nm process 600uA/MHz, 1.5 ua standby Medical, Automotive & Industrial High Performance CPU, FPU, DSC Up to 165 DMIPS, 90nm process 500uA/MHz, 2.5 ua standby Ethernet, CAN, USB, Motor Control, TFT Display Legacy Cores Next-generation migration to RX General Purpose Up to 10 DMIPS, 130nm process 350 ua/mhz, 1uA standby Capacitive touch Ultra Low Power Up to 25 DMIPS, 150nm process 190 ua/mhz, 0.3uA standby Application-specific integration Embedded Security Up to 25 DMIPS, 180, 90nm process 1mA/MHz, 100uA standby Crypto engine, Hardware security 5

6 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 High Performance CPU, Low Power Up to 500 DMIPS, 150 & 90nm process 600uA/MHz, 1.5 ua standby Medical, Automotive & Industrial High Performance CPU, FPU, DSC Up to 165 DMIPS, 90nm process 500uA/MHz, 2.5 ua standby Ethernet, CAN, USB, Motor Control, TFT Display Legacy Cores Next-generation migration to RX General Purpose Up to 10 DMIPS, 130nm process 350 ua/mhz, 1uA standby Capacitive touch Ultra Low Power Up to 25 DMIPS, 150nm process 190 ua/mhz, 0.3uA standby Application-specific integration Embedded Security Up to 25 DMIPS, 180, 90nm process 1mA/MHz, 100uA standby Crypto engine, Hardware security 6

7 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

8 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. 8

9 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 9

10 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 10

11 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 11

12 Auto-Code Generation: Why Controls Perspective Software Perspective 12

13 Modeling: A Software Perspective Controls Perspective Software Perspective 13

14 Typical Project Effort Kick-Off Time Delivery 14

15 Ideal Project Effort Kick-Off Time Delivery 15

16 Dollars and Cents Advantage SOFTWARE DEFECT COSTS 16

17 Why Typical Approaches Don t Work! Req 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 Or Use Case 1 Use Case n 17

18 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 18

19 Modeling: A Controls Perspective Controls Perspective Software Perspective 19

20 20 Why Auto-Code Generation: R&D

21 Modeling: Auto-Coding Controls Perspective Software Perspective 21

22 Our Auto-Coding Toolbox MATLAB Base computing platform Simulink & Stateflow Modeling platform RTW Embedded Coder Auto-code generation QuantiPhi Provides MCU configuration and device drivers. 22

23 Building Block: The Feature Determine a set point Compute value for an actuator Detect a fault Condition a user input triggers inputs Feature outputs 23

24 An Example Feature Model [In Simulink] 24

25 What About Integrating the Code? New Concerns! Feature Data Types Target Variables File Naming Legacy Code 25

26 What About Integrating the Code? Feature Data Types Target Variables File Naming Legacy Code 26

27 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 fixedpoint types available 27

28 Data Types: Floating and Fixed Point float my_var = 3.57; float my_var = 3.57; FPU No FPU 28

29 Data Types: Floating and Fixed Point Value to represent: 3.57 float* ( ) uint ufix16_en4 Artificial binary point uint ufix16_sp01 *IEEE754 Artificial decimal point (understood that number is 100x higher than real value) 29

30 Data Types (+Fixed Point) in Simulink [In Simulink] 30

31 Auto-Coding for Different-Sized Targets Feature Data Types Target Variables File Naming Legacy Code 31

32 More Control Over Generated Code Feature Data Types Target Variables File Naming Legacy Code 32

33 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 33

34 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 34

35 Legacy Code Feature Data Types Target Variables File Naming Legacy Code 35

36 Legacy Code triggers inputs Feature Backed By Legacy Code outputs Step 1: Simulation Behavior Step 2: Code Generation Behavior [Go to Simulink] 36

37 Typical Auto-Coding Methodologies Feature Effort = 37

38 Typical Auto-Coding Methodologies Application Layer Feature 1 Effort = Feature n 38

39 Typical Auto-Coding Methodologies Feature 1 Feature n Effort = Hardware Interface 39

40 40 Convinced?

41 The Next Step Feature 1 Feature n Hardware Interface 41

42 Interfacing With Hardware A B C 42

43 Interfacing With Hardware pwm0 A B C PA0 QuantiPhi RPM 43

44 Hardware Abstraction Layer Example of a digital debounce: 44

45 Another Hardware Abstraction Layer Example Example of analog counts to engineering units: 45

46 A One Touch Example Using QuantiPhi [In Simulink] 46

47 47 Innovation: Innovate Faster

48 Related Lab 021L: Model Based Control Design and Auto Code Generation using the R8C [In Simulink] 48

49 49 Questions?

50 50 Thank You!

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