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Embedded Systems Introduction. L1. References Embedded Systems Design, Steve Heath, Elsevier Embedded Systems Design, Frank Vahid & Tony Givargis, John wiley Fundamentals of embedded software, Daniel W lewis, Pearson education

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slide2

References

  • Embedded Systems Design, Steve Heath, Elsevier
  • Embedded Systems Design, Frank Vahid & Tony Givargis, John wiley
  • Fundamentals of embedded software, Daniel W lewis, Pearson education
  • Embedded Microcomputer Systems, Jonathan W Valavano, Brooks/cole, Thomson Learning
  • Embedded Systems Design, Oliver Bailey, Dreamtech
  • Embedded Real-time Systems, K V K K Prasad, Dreamtech
outline
Outline
  • Embedded systems overview
    • What are they?
  • Design challenge – optimizing design metrics
  • Technologies
    • Processor technologies
    • IC technologies
    • Design technologies
embedded systems overview
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 overview1

Computers/ microprocessors are in here...

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

Toys, mobile phones, kitchen appliances, even pens 

Many times more processors used in each of them , though they cost much less

These processors make these devices sophisticated, versatile and inexpensive

a short list of embedded systems
A “short list” of embedded systems

Modems

MPEG decoders

Network cards

Network switches/routers

On-board navigation

Pagers

Photocopiers

Point-of-sale systems

Portable video games

Printers

Satellite phones

Scanners

Smart ovens/dishwashers

Speech recognizers

Stereo systems

Teleconferencing systems

Televisions

Temperature controllers

Theft tracking systems

TV set-top boxes

VCR’s, DVD players

Video game consoles

Video phones

Washers and dryers

Anti-lock brakes

Auto-focus cameras

Automatic teller machines

Automatic toll systems

Automatic transmission

Avionic systems

Battery chargers

Camcorders

Cell phones

Cell-phone base stations

Cordless phones

Cruise control

Curbside check-in systems

Digital cameras

Disk drives

Electronic card readers

Electronic instruments

Electronic toys/games

Factory control

Fax machines

Fingerprint identifiers

Home security systems

Life-support systems

Medical testing systems

And the list goes

on and on

slide7

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

slide8

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)

slide9

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

slide10

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
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

Digital camera chip

CCD

CCD preprocessor

Pixel coprocessor

D2A

A2D

lens

JPEG codec

Microcontroller

Multiplier/Accum

DMA controller

Display ctrl

Memory controller

ISA bus interface

UART

LCD ctrl

Embedded system - digital camera
  • 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
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 metrics1
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 metrics2
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

Digital camera chip

CCD

CCD preprocessor

Pixel coprocessor

D2A

A2D

lens

JPEG codec

Microcontroller

Multiplier/Accum

DMA controller

Display ctrl

Memory controller

ISA bus interface

UART

LCD ctrl

Design metric competition -- improving one may worsen others

Power

Performance

Size

NRE cost

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

Time-to-market: a demanding design metric

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

Peak revenue

Peak revenue from delayed entry

Revenues ($)

On-time

Market fall

Market rise

Delayed

D

W

2W

On-time Delayed

entry entry

Time

Losses Due to Delayed Market Entry
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

Peak revenue

Peak revenue from delayed entry

Revenues ($)

On-time

Market fall

Market rise

Delayed

D

W

2W

On-time Delayed

entry entry

Time

Losses due to delayed market entry (cont.)
  • 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!
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

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

NRE and Unit Cost Metrics
  • 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
nre and unit cost metrics1
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

NRE and unit cost metrics
the performance design metric
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
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
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

Controller

Controller

Datapath

Datapath

Controller

Datapath

Control

logic

index

Control

logic and State register

Control logic and State register

Registers

Register

file

total

Custom

ALU

State register

+

General

ALU

IR

PC

IR

PC

Data

memory

Data

memory

Program memory

Program memory

Data

memory

Assembly code for:

total = 0

for i =1 to …

Assembly code for:

total = 0

for i =1 to …

Single-purpose

(“hardware”)

General-purpose

(“software”)

Application

-specific

processor technology1
Processor technology
  • Processors vary in their customization for the problem at hand

total = 0

for i = 1 to N loop

total += M[i]

end loop

Desired functionality

General-purpose processor

Application-specific processor

Single-purpose processor

general purpose processors

Controller

Data path

Control

logic and State register

Register

file

General

ALU

IR

PC

Program memory

Data

memory

Assembly code for:

total = 0

for i =1 to …

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
single purpose processors

Datapath

Controller

Control logic

index

total

State register

+

Data

memory

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
application specific instruction set processors

Controller

Datapath

Control

logic and State register

Registers

Custom

ALU

IR

PC

Data

memory

Program memory

Assembly code for:

total = 0

for i =1 to …

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
ic technology
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

gate

oxide

IC package

IC

drain

channel

source

Silicon substrate

ic technology1
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
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
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
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
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

Logic transistors per chip

(in millions)

1,000

100

10

1

0.1

Note: logarithmic scale

0.01

0.001

1985

1987

1989

1991

1993

1995

1997

2003

2005

2007

2009

1981

1983

1999

2001

moore s law1
Moore’s law
  • This growth rate is hard to imagine, most people underestimate
graphical illustration of moore s law
Graphical illustration of Moore’s law
  • Something that doubles frequently grows more quickly than most people realize!
    • A 2002 chip can hold about 15,000 1981 chips inside itself

1981

1984

1987

1990

1993

1996

1999

2002

10,000

transistors

150,000,000

transistors

Leading edge

chip in 1981

Leading edge

chip in 2002

slide37

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.”
slide38

Design needs Design technology

Achieving the metrics + fast & reliably

Enhanced productivity

Design – single stage

Multi stage - several abstraction levels

design technology
Design Technology
  • The manner in which we convert our concept of desired system functionality into an implementation

Compilation/

Synthesis

Libraries/

IP

Test/

Verification

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

System

specification

System

synthesis

Hw/Sw/

OS

Model simulat./

checkers

Hw-Sw

cosimulators

Behavioral

specification

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

Cores

Behavior

synthesis

RT

components

HDL simulators

RT

specification

RT

synthesis

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

Gate

simulators

Logic

specification

Gates/

Cells

Logic

synthesis

To final implementation

slide40

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

slide41

Multiple perspectives for visualisation of a system

Functionality perspective

Environmental

User I/F or Operator perspective

System

Performance

Architectural perspective

Physical

slide42

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
slide43

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
slide44

Models

Conceptual model

Physical model

Analogue model

Mathematical model

Numerical model

Computational model

Implementation

Assumptions & accuracy

slide45

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
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 etc

System model must support description of both

functional behavior and physical interaction

elements of a model of a computation system language
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
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
slide49

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 !
slide50

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

slide51

Models & Languages

Models exist without language

Models are expressed in some language or the other

A model could be expressed in different languages

A language could express more than one model

Some languages are better suited to express some models

slide52

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 feature

Communicating-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.

slide53

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 languages

Data 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

slide54

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

slide55

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

slide56

Problems

  • Develop a model for the lift controller
  • Identify one problem each that fits into the models discussed above.
  • 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
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
continued
  • UML is the latest manifestation
    • becoming prevalent in complex embedded system design
how models influence an application 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
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
Design productivity exponential increase
  • Exponential increase over the past few decades

100,000

10,000

1,000

Productivity

(K) Trans./Staff – Mo.

100

10

1

0.1

0.01

1981

2009

1995

2007

1997

1989

1993

1999

2001

1991

1983

2003

1987

1985

2005

the co design ladder
The co-design ladder

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

  • 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”

Behavioral synthesis

(1990's)

Compilers

(1960's,1970's)

Register transfers

Assembly instructions

RT synthesis

(1980's, 1990's)

Assemblers, linkers

(1950's, 1960's)

Logic equations / FSM's

Logic synthesis

(1970's, 1980's)

Machine instructions

Logic gates

Implementation

VLSI, ASIC, or PLD implementation: “hardware”

Microprocessor plus program bits: “software”

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
Independence of Processor and IC Technologies
  • Basic tradeoff
    • General vs. custom
    • With respect to processor technology or IC technology
    • The two technologies are independent

Customized,

providing improved:

General-purpose

processor

ASIP

Single-

purpose

processor

General,

providing improved:

Power efficiency

Performance

Size

Cost (high volume)

Flexibility

Maintainability

NRE cost

Time- to-prototype

Time-to-market

Cost (low volume)

PLD

Semi-custom

Full-custom

design productivity gap
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

100,000

1,000

10,000

100

1000

Logic transistors per chip

(in millions)

Gap

Productivity

(K) Trans./Staff-Mo.

10

100

IC capacity

1

10

0.1

1

productivity

0.01

0.1

0.001

0.01

1981

1983

1985

1987

1995

1997

1999

2001

2003

2005

2007

2009

1989

1991

1993

design productivity gap1
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 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”)

Team

  • 1M transistors, 1 designer=5000 trans/month
  • Each additional designer reduces for 100 trans/month
  • So 2 designers produce 4900 trans/month each

15

60000

16

16

18

50000

19

40000

23

24

30000

Months until completion

20000

43

Individual

10000

0

10

20

30

40

Number of designers

summary
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