Embedded SystemsIntroduction

L1

References

1. Embedded Systems Design, Steve Heath, Elsevier

2. Embedded Systems Design, Frank Vahid & Tony Givargis, John wiley

3. Fundamentals of embedded software, Daniel W lewis, Pearson education

4. Embedded Microcomputer Systems, Jonathan W Valavano, Brooks/cole, Thomson Learning

5. Embedded Systems Design, Oliver Bailey, Dreamtech

6. Embedded Real-time Systems, K V K K Prasad, Dreamtech

Outline

• Embedded systems overview– What are they?

• Design challenge – optimizing design metrics

• Technologies– Processor technologies

– IC technologies

– Design technologies

Embedded systems overview

• When we talk of microprocessors we think of computers as they are everywhere

• Computers often mean – Desktop PC’s– Laptops– Mainframes– Servers

• But there’s yet another type of computing system– Far more common...

Embedded systems overview

• Embedded computing systems– (Micro)processors are

embedded within electronic devices, equipment, appliances

– Hard to define - any computing system other than a desktop computer

– Billions of units produced yearly, versus millions of desktop units

– Perhaps 50 per household and per automobile

Computers/ microprocessors are in here...

Many times more processors used in

each of them , though they cost

much lessThese processors make these devices

sophisticated, versatile and inexpensive

Toys, mobile phones, kitchen appliances,

even pens

A “short list” of embedded systems

And the list goes on and on

Anti-lock brakesAuto-focus camerasAutomatic teller machinesAutomatic toll systemsAutomatic transmissionAvionic systemsBattery chargersCamcordersCell phonesCell-phone base stationsCordless phonesCruise controlCurbside check-in systemsDigital camerasDisk drivesElectronic card readersElectronic instrumentsElectronic toys/gamesFactory controlFax machinesFingerprint identifiersHome security systemsLife-support systemsMedical testing systems

ModemsMPEG decodersNetwork cardsNetwork switches/routersOn-board navigationPagersPhotocopiersPoint-of-sale systemsPortable video gamesPrintersSatellite phonesScannersSmart ovens/dishwashersSpeech recognizersStereo systemsTeleconferencing systemsTelevisionsTemperature controllersTheft tracking systemsTV set-top boxesVCR’s, DVD playersVideo game consolesVideo phonesWashers and dryers

Embedded systems

A microprocessor based system that is built to control a function(s) of a system and is designed not to be programmed by the user. (controller)

User could select the functionality but cannot define the functionality.

Embedded system is designed to perform one or limited number of functions, may be with choices or options.

PCs provide easily accessible methodologies, HW & SW that are used to build Embedded systems

Why did they become popular?

Replacement for discrete logic-based circuits

Functional upgradability ?, easy maintenance upgrades

Improves the performance of mechanical systems through close control

Protection of Intellectual property

Replacement of Analogue circuits (DSPs)

What does an Embedded system consist of?

Processor – Types, technologies, functionalities

Memory – how much, what types, organisation

Peripherals/ I/O interfaces – communicate with the user, external environment

Inputs and outputs / sensors & actuators – Digital - binary, serial/parallel, Analogue, Displays and alarms, Timing devices

SW – OS, application SW, initialisation, self check

Algorithms

Path of electronic design

Mechanical control systems- expensive & bulky

Discrete electronic circuits – fast but no flexibility

SW controlled circuits – microprocessors and controllers – slow, flexible

HW implementation of SW, HW & SW systems

Some Common Characteristics of Embedded Systems

• Single-functioned– Executes a single program, repeatedly

• Tightly-constrained– Low cost, low power, small, fast, etc.

• Reactive and real-time– Continually reacts to changes in the system’s

environment– Must compute certain results in real-time

without delay

Embedded system - digital camera

Microcontroller

CCD preprocessor Pixel coprocessorA2D

D2A

JPEG codec

DMA controller

Memory controller ISA bus interface UART LCD ctrl

Display ctrl

Multiplier/Accum

Digital camera chip

lens

CCD

• Single-functioned -- always a digital camera

• Tightly-constrained -- Low cost, low power, small, fast

• Reactive and real-time -- only to a small extent

Design challenge – optimizing design metrics

• Obvious design goal:– Construct an implementation with desired

functionality• Key design challenge:

– Simultaneously optimize numerous design metrics

• Design metric– A measurable feature of a system’s

implementation– Optimizing design metrics is a key challenge

Design challenge – optimizing design metrics

• Common metrics– Unit cost: the monetary cost of manufacturing each

copy of the system, excluding NRE cost

– NRE cost (Non-Recurring Engineering cost): The one-time monetary cost of designing the system

– Size: the physical space required by the system

– Performance: the execution time or throughput of the system

– Power: amount of power consumed by the system

– Flexibility: the ability to change the functionality of the system without incurring heavy NRE cost

Design challenge – optimizing design metrics

• Common metrics (continued)

– Time-to-prototype: the time needed to build a working version of the system

– Time-to-market: the time required to develop a system to the point that it can be released and sold to customers

– Maintainability: the ability to modify the system after its initial release

– Correctness, safety, many more

Design metric competition -- improving one may worsen others

• Expertise with both software and hardware is needed to optimize design metrics– A designer must be

comfortable with various technologies in order to choose the best for a given application and constraints

SizePerformance

Power

NRE cost

Microcontroller

CCD preprocessor Pixel coprocessorA2D

D2A

JPEG codec

DMA controller

Memory controller ISA bus interface UART LCD ctrl

Display ctrl

Multiplier/Accum

Digital camera chipCCD

Hardware

Software

Time-to-market: a demanding design metric

• Time required to develop a product to the point it can be sold to customers

• Market window– Period during which the

product would have highest sales

• Average time-to-market constraint is about 8 months

• Delays can be costly

Revenue

Time (months)

Losses Due to Delayed Market Entry

• Simplified revenue model– Product life = 2W, peak

at W– Time of market entry

defines a triangle, representing market penetration

– Triangle area equals revenue

• Loss – The difference between

the on-time and delayed triangle areas

On-time Delayedentry entry

Peak revenue

Peak revenue from delayed entry

Market rise

Market fall

W 2W

Time

D

On-time

Delayed

Rev

enu

es (

$)

Losses due to delayed market entry (cont.)• Area = 1/2 * base * height

– On-time = 1/2 * 2W * W

– Delayed = 1/2 * (W-D+W)*(W-D)

• Percentage revenue loss =

(D(3W-D)/2W2)*100%

• Try some examples

– Lifetime 2W=52 wks, delay D=4 wks

– (4*(3*26 –4)/2*26^2) = 22%

– Lifetime 2W=52 wks, delay D=10 wks

– (10*(3*26 –10)/2*26^2) = 50%

– Delays are costly!

On-time Delayedentry entry

Peak revenue

Peak revenue from delayed entry

Market rise

Market fall

W 2W

Time

D

On-time

Delayed

Rev

enu

es (

$)

NRE and Unit Cost Metrics

• Costs:– Unit cost: the monetary cost of manufacturing each copy of the

system, excluding NRE cost

– NRE cost (Non-Recurring Engineering cost): The one-time monetary cost of designing the system

– total cost = NRE cost + unit cost * # of units

– per-product cost = total cost / # of units

= (NRE cost / # of units) + unit cost

• Example– NRE= Rs 20000, unit= Rs100– For 100 units

– total cost = 20000 + 100*100 = 30000– per-product cost = 30,000/100 or 20000/100 + 100 = 300

Amortizing NRE cost over the units results in an additional Rs 200 per

unit

NRE and unit cost metrics

• Compare technologies by costs -- best depends on quantity !– Technology A: NRE=Rs 5,000, unit=Rs

100

– Technology B: NRE=Rs 1,00,000, unit=Rs 25

– Technology C: NRE=Rs10,00,000, unit= Rs 2

The performance design metric• Widely-used measure of system, widely-abused

– Clock freq, instructions per second – not good measures– Digital camera example – a user cares about how fast it

processes images, not clock speed or instructions per second• Latency (response time)

– Time between task start and end– e.g., Camera’s A and B process images in 0.25 & 0.3 seconds

• Throughput– Tasks per second, e.g. Camera A processes 4 images & B say

8 images per second– Throughput can be more than latency seems to imply due to

concurrency, (by capturing a new image while previous image is being stored).

• Speedup of B over S = B’s performance / A’s performance– Throughput speedup = 8/4 = 2

Three key embedded system technologies

• Technology– A manner of accomplishing a task,

especially using technical processes, methods, or knowledge

• Three key technologies for embedded systems– Processor technology– IC technology– Design technology

Processor technology• The architecture of the computation engine used to

implement a system’s desired functionality• Processor does not have to be programmable

– “Processor” not equal to general-purpose processor

Application-specific

Single-purpose (“hardware”)

Registers

CustomALU

DatapathController

Program memory

Assembly code for:

total = 0 for i =1 to …

Control logic and

State register

Datamemory

IR PC

DatapathController

Control logic

State register

Datamemory

index

total

+

IR PC

Registerfile

GeneralALU

DatapathController

Program memory

Assembly code for:

total = 0 for i =1 to …

Control logic and

State register

Datamemory

General-purpose (“software”)

Processor technology• Processors vary in their customization for the problem at

hand

total = 0for i = 1 to N loop total += M[i]end loop

General-purpose

processor

Single-purpose processor

Application-specific

processor

Desired functionality

General-purpose processors

• Programmable device used in a variety of applications– Also known as “microprocessor”

• Features– Program memory– General datapath with large register

set and general ALU

• User benefits– Low time-to-market and NRE costs– High flexibility

• “Pentium” the most well-known, but there are hundreds of others

IR PC

Registerfile

GeneralALU

Data pathController

Program memory

Assembly code for:

total = 0 for i =1 to …

Control logic and

State register

Datamemory

Single-purpose processors

• Digital circuit designed to execute exactly one program– Ex. coprocessor, accelerator Features– Contains only the components

needed to execute a single program

– No program memory

• Benefits– Fast– Low power– Small size

DatapathControllerControl logic

State register

Datamemory

index

total

+

Application-specific Instruction set Processors• Programmable processor

optimized for a particular class of applications having common characteristics– Compromise between general-

purpose and single-purpose processors

• Features– Program memory– Optimized datapath– Special functional units

• Benefits– Some flexibility, good performance,

size and power

IR PC

Registers

CustomALU

DatapathController

Program memory

Assembly code for:

total = 0 for i =1 to …

Control logic and

State register

Datamemory

IC technology

• The manner in which a digital (gate-level) implementation is mapped onto an IC– IC: Integrated circuit, or “chip”– IC technologies differ in their customization to a

design– IC’s consist of numerous layers (perhaps 10 or

more)• IC technologies differ with respect to who builds each

layer & when

source drainchannel

oxide

gate

Silicon substrate

IC package

IC

IC technology

• Three types of IC technologies– Full-custom/VLSI

– Semi-custom ASIC (gate array and standard cell)

– PLD (Programmable Logic Device)

Full-custom/VLSI

• All layers are optimized for an embedded system’s particular digital implementation– Placing transistors– Sizing transistors– Routing wires

• Benefits– Excellent performance, small size, low power

• Drawbacks– High NRE cost (e.g., Rs 2 M), long time-to-market

Semi-custom

• Lower layers are fully or partially built– Designers are left with routing of wires and

maybe placing some blocks

• Benefits– Good performance, good size, less NRE

cost than a full-custom implementation (perhaps $10k to $100k)

• Drawbacks– Still require weeks to months to develop

PLD (Programmable Logic Device)

• All layers already exist– Designers can purchase an IC– Connections on the IC are either created or

destroyed to implement desired functionality– Field-Programmable Gate Array (FPGA) very

popular

• Benefits– Low NRE costs, almost instant IC availability

• Drawbacks– Bigger, expensive (perhaps Rs 2000 per unit),

power hungry, slower

Moore’s law• The most important trend in embedded systems

– Predicted in 1965 by Intel co-founder Gordon Moore

IC transistor capacity has doubled roughly every 18 months for the past several decades

10,000

1,000

100

10

10.1

0.01

0.001

Log

ic

tran

sist

ors

per

chip

(in

mil

lion

s)

1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009

Note: logarithmic

scale

Moore’s law

– This growth rate is hard to imagine, most people underestimate

Graphical illustration of Moore’s law

1981 1984 1987 1990 1993 1996 1999 2002

Leading edgechip in 1981

10,000transistors

Leading edgechip in 2002

150,000,000transistors

• Something that doubles frequently grows more quickly than most people realize!– A 2002 chip can hold about 15,000 1981 chips inside itself

Design of Embedded Systems (Wescon 1975)

• “... avoid data processing aides such as assemblers, high-level languages, simulated systems, and control panels. These computer-aided design tools generally get in the way of cost-effective design and are more a result of the cultural influence of data processing, rather than a practical need.”

• “bulk of real-world control problems require less than 2,000 instructions to implement. For this size of program computer aided design does little to improve the design approach and does a lot to separate the design engineer from intimate knowledge of his hardware.”

Design needs Design technology

Achieving the metrics + fast & reliably

Enhanced productivity

Design – single stage

Multi stage - several abstraction levels

Design Technology• The manner in which we convert our concept of

desired system functionality into an implementation

Libraries/IP: Incorporates pre-designed implementation from lower abstraction level into higher level.

Systemspecification

Behavioralspecification

RTspecification

Logicspecification

To final implementation

Compilation/Synthesis: Automates exploration and insertion of implementation details for lower level.

Test/Verification: Ensures correct functionality at each level, thus reducing costly iterations between levels.

Compilation/Synthesis

Libraries/IP

Test/Verification

Systemsynthesis

Behaviorsynthesis

RTsynthesis

Logicsynthesis

Hw/Sw/OS

Cores

RTcomponents

Gates/Cells

Model simulat./checkers

Hw-Swcosimulators

HDL simulators

Gate simulators

Compilation and synthesis

Specify in abstract manner and get lower level details

Libraries and IP - reusability

Are ICs a form of libraries?

How do cores differ from ICs

Test / verification

Simulation

HDL based simulations

System

User I/F or Operator perspective

Functionality perspective

Architectural perspective

Multiple perspectives for visualisation of a system

Physical

Environmental

Performance

Systematic Design of Embedded Systems• Most embedded systems are far too complex for

Adhoc/empirical approach to design(100,000 lines) • Methodical, engineering-oriented, tool-based

approach is essential– specification, synthesis, optimization,

verification etc.– prevalent for hardware, still rare for software

• One key aspect is the creation of models– Representation of knowledge and ideas about

the system being developed - specification– Models only represent certain properties to be

analyzed, understood & verified. They omit or modify certain details (abstraction) based on certain assumptions. One of the few tools available for dealing with complexity

Abstractions and Models• Models are foundations of science and engineering• Designs usually start with informal specifications• However, soon a need for Models and Abstractions

is established• Models or abstractions have connections to

Implementation (h/w, s/w) and Application• Two types of modeling: System structure & system

behavior– The relationships, behavior and interaction of

atomic components– Coordinate computation of & communication

between components • Models from classical CS

– FSM, RAM (von Neumann), CCS (Milner)– Turing machine, Universal Register Machine

Models

Conceptual model

Physical model

Analogue model

Mathematical model

Numerical model

Computational model

Implementation

Assumptions & accuracy

Good Models• Simple

– Ptolemy vs. Galileo• Amenable for development of theory to reason

– should not be too general• Has High Expressive Power

– a game is interesting only if it has some level of difficulty!

• Provides Ability for Critical Reasoning– Science vs. Religion

• Practice is currently THE only serious test of model quality

• Executable (for Simulation)• Synthesizable• Unbiased towards any specific implementation (h/w

or s/w)

Modeling Embedded Systems

• Functional behavior: what does the system do– in non-embedded systems, this is sufficient

• Contract with the physical world– Time: meet temporal contract with the environment

• temporal behavior important in real-time systems, as most embedded systems are

• simple metric such as throughput, latency, jitter• more sophisticated quality-of-service metrics

– Power: meet constraint on power consumption• peak power, average power, system lifetime

– Others: size, weight, heat, temperature, reliability etcSystem model must support description of both

functional behavior and physical interaction

Elements of a Model of a Computation System: Language

• Set of symbols with superimposed syntax & semantics– textual (e.g. matlab), visual (e.g. labview) etc.

• Syntax: rules for combining symbols– well structured, intuitive

• Semantics: rules for assigning meaning to symbols and combinations of symbols– without rigorous semantics, precise model behavior

over time is not well defined– full executability and automatic h/w or s/w

synthesis is impossible– E.g. operational semantics (in terms of actions of an

abstract machine), denotational semantics (in terms of relations)

Simulation and Synthesis

• Two sides of the same coin• Simulation: scheduling then execution on desktop

computer(s)• Synthesis: scheduling then code generation in C++, C,

assembly, VHDL, etc.• Validation by simulation important throughout

design flow• Models of computation enable

– Global optimization of computation and communication

– Scheduling and communication that is correct by construction

Models Useful In Validating Designs• By construction

– property is inherent.• By verification

– property is provable.• By simulation

– check behavior for all inputs.• By intuition

– property is true. I just know it is.• By assertion

– property is true. Would make something of it?• By intimidation

– Don’t even try to doubt whether it is true

It is generally better to be higher in this list !

An embedded system is expected to receive inputs, process data or information, and provide outputs

The processing is done by processors

Before we build the processor we must know the expected behaviour of the processor

This is the model of the processor. We may call it a computational model. Before the processor is built it is in our mind. We express this model through a description - text, graphics, or some formal language

Models & Languages

Models exist without languageModels are expressed in some language or the other A model could be expressed in different languagesA language could express more than one modelSome languages are better suited to express some models

Types of models – many & include

Sequential model – A model that represents the embedded system as a sequence of actions. A variety of systems need this sequence of steps. Most programming languages and natural languages can express this featureCommunicating-process model – A number of independent processes (may be sequential) communicate among themselves whilst doing their job. Synchronisation/signalling, passing data, mutual exclusion etc. Some languages are better suited.

State machine model – A model where the embedded system resides in a state till an input to the system/event makes it change its state. Most reactive and control system applications fall under this category. FSM representations are good way expressing the model. Text Vs Graphic languagesData flow model – An embedded system that functions mainly by transforming an input data stream into an output data stream – functioning of an mpeg camera – UML may be more useful. Most DSP applications

OO models – Well known – Useful for successive decomposition problems, problems where OO paradigm is useful etc.

Multiple models and multiple languages may be needed to describe a complex system.

The model description must be accompanied by semantic descriptions for proper processing

Lift model - English language description Lift cage contains a number of controls – floor numbers, open and close door, it receives the data regarding the floor it is at. Users press the floor number to which they desire to go and depending upon the current location and the floor it has to go it moves up and down. Before it moves, the door is closed. On reaching the floor it keeps the door open for 15 sec, unless close door operation is executed before door closes. When stationary, door is kept closed. When moving in a direction it does not return to opposite direction, even on request, unless no request for higher or lower floor in the same direction is pending

Problems1. Develop a model for the lift controller 2. Identify one problem each that fits into the

models discussed above.3. Develop a model for a data acquisition

system that receives data from 14 channels through A/D converters and takes appropriate control actions as a function of the 14 inputs and communicates with 4 actuators. Inputs from channel 15 or 16 need immediate response, and the controller must respond in a time of about 20 clock cycles. In these cases, actuator 5 is activated.

Modeling Approaches based on Software Design Methods

• No systematic design in 60s• From 70s, many different s/w design strategies

– Design methods based on functional decomposition• Real-Time Structured Analysis and

Design(RTSAD)– Design methods based on concurrent task

structuring• Design Approach for Real-Time Systems

(DARTS)– Design methods based on information hiding

• Object-Oriented Design method (OOD)– Design methods based on modeling the domain

• Jackson System Development method (JSD)• Object-Oriented Design method (OOD)

continued

• UML is the latest manifestation– becoming prevalent in complex embedded

system design

How Models Influence an Application Design?

• Example: given input from a camera, digitally encode it using MPEG II encoding standards.

• this task involves: storing the image for processing going through a number of processing steps, e.g., Discrete cosine transform (DCT), Quantization, encoding (variable length encoding), formatting the bit stream, Inverse Discrete Cosine transform (IDCT), ...

• Is this problem appropriate for• Reactive Systems, Synchronous Data flow,

CSP, ...• More than one model could be appropriate.

Choice of Model

• Model Choice: depends on– application domain

• DSP applications use data flow models• Control applications use finite state machine

models• Event driven applications use reactive models

– efficiency of the model• in terms of simulation time• in terms of synthesized circuit/code.

• Language Choice: depends on– underlying semantics

• semantics in the model appropriate for the application.

– available tools– personal taste and/or company policy

Design productivity exponential increase

• Exponential increase over the past few decades

100,000

10,000

1,000

100

10

1

0.1

0.01

19831981 1987 1989 1991 19931985 1995 1997 1999 2001 2003 2005 2007 2009

Productivity(K) Trans./Staff – Mo.

The co-design ladder

• In the past:– Hardware and software

design technologies were very different

– Recent maturation of synthesis enables a unified view of hardware and software

• Hardware/software “codesign”

Implementation

Assembly instructions

Machine instructions

Register transfers

Compilers(1960's,1970's)

Assemblers, linkers(1950's, 1960's)

Behavioral synthesis(1990's)

RT synthesis(1980's, 1990's)

Logic synthesis(1970's, 1980's)

Microprocessor plus program bits: “software”

VLSI, ASIC, or PLD implementation: “hardware”

Logic gates

Logic equations / FSM's

Sequential program code (e.g., C, VHDL)

The choice of hardware versus software for a particular function is simply a tradeoff among various design metrics, like performance, power, size, NRE cost,

and especially flexibility; there is no fundamental difference between what hardware or software can implement.

Independence of Processor and IC Technologies

• Basic tradeoff– General vs. custom

– With respect to processor technology or IC technology

– The two technologies are independent

General-purpose

processor

ASIPSingle-

purposeprocessor

Semi-customPLD Full-custom

General,providing improved:

Customized, providing improved:

Power efficiencyPerformance

SizeCost (high volume)

FlexibilityMaintainability

NRE costTime- to-prototype

Time-to-marketCost (low volume)

Design productivity gap

• While designer productivity has grown at an impressive rate over the past decades, the rate of improvement has not kept pace with chip capacity

10,000

1,000

100

10

1

0.1

0.01

0.001

Log

ic

tran

sist

ors

per

chip

(in

mil

lion

s)

100,000

10,000

1000

100

10

1

0.1

0.01

Prod

ucti

vity

(K)

Tra

ns./S

taff

-M

o.

1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009

IC capacity

productivity

Gap

Design productivity gap

• 1981 leading edge chip required 100 designer months– 10,000 transistors / 100 transistors/month

• 2002 leading edge chip requires 30,000 designer months– 150,000,000 / 5000 transistors/month

• Designer cost increase from $1M to $300M

The mythical man-month• The situation is even worse than the productivity gap indicates• In theory, adding designers to team reduces project completion time• In reality, productivity per designer decreases due to complexities of team

management and communication • In the software community, known as “the mythical man-month” (Brooks

1975)• At some point, can actually lengthen project completion time! (“Too many

cooks”)

10 20 30 400

100002000030000400005000060000

43

24

1916 15 16

18

23

Team

Individual

Months until completion

Number of designers

• 1M transistors, 1 designer=5000 trans/month

• Each additional designer reduces for 100 trans/month

• So 2 designers produce 4900 trans/month each

Summary

• Embedded systems are everywhere

• Key challenge: optimization of design metrics– Design metrics compete with one another

• A unified view of hardware and software is necessary to improve productivity

• Three key technologies– Processor: general-purpose, application-specific,

single-purpose– IC: Full-custom, semi-custom, PLD– Design: Compilation/synthesis, libraries/IP,

test/verification