1. Embedded Systems IntroductionL1

2. 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

3. Embedded systems overview Design challenge – optimizing design metrics
Outline
Embedded systems overview
What are they?
Design challenge – optimizing design metrics
Technologies
Processor technologies
IC technologies
Design technologies

4. 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...

5. Embedded systems overview
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

6. 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

7. 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

8. 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)

9. 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

10. 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

11. 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

12. Embedded system - digital camera
Microcontroller
CCD preprocessor
Pixel coprocessor
A2D
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

13. 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

14. 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

15. 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

16. 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
Power
Performance
Size
NRE cost
Microcontroller
CCD preprocessor
Pixel coprocessor
A2D
D2A
JPEG codec
DMA controller
Memory controller
ISA bus interface
UART
LCD ctrl
Display ctrl
Multiplier/Accum
Digital camera chip
lens
CCD
Hardware
Software

17. 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)

18. 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 Delayed
entry entry
Peak revenue
Peak revenue from delayed entry
Market rise
Market fall W 2W
Time D
On-time
Delayed
Revenues ($)

19. 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
On-time Delayed
entry entry
Peak revenue
Peak revenue from delayed entry
Market rise
Market fall W 2W
Time D
On-time
Delayed
Revenues ($)
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!

20. 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 = *100 = 30000
per-product cost = 30,000/100 or 20000/ = 300
Amortizing NRE cost over the units results in an additional Rs 200 per unit

21. NRE and unit cost metrics
Compare technologies by costs -- best depends on quantity !
Technology A: NRE=Rs ,000, unit=Rs 100
Technology B: NRE=Rs 1,00,000, unit=Rs 25
Technology C: NRE=Rs10,00,000, unit= Rs 2

22. 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

23. 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

24. logic and State register Control logic and State register
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 and State register
Register
file
Control logic and State register
Registers
Control
logic
index
total
Custom
ALU
State register +
General
ALU IR PC IR PC
Data
memory
Data
memory
Program memory
Data
memory
Program 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

25. 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

26. 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
Register
file
General
ALU
Data path
Controller
Program memory
Assembly code for:
total = 0
for i =1 to …
Control
logic and State register
Data
memory

27. 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
Datapath
Controller
Control logic
State register
Data
memory
index
total +

28. 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
Custom
ALU
Datapath
Controller
Program memory
Assembly code for:
total = 0
for i =1 to …
Control
logic and State register
Data
memory

29. 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
source
channel
drain
Silicon substrate

30. Three types of IC technologies
IC technology
Three types of IC technologies
Full-custom/VLSI
Semi-custom ASIC (gate array and standard cell)
PLD (Programmable Logic Device)

31. 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

32. Lower layers are fully or partially built
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

33. 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

34. 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
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
2001
2003
2005
2007
2009

35. Moore’s law
This growth rate is hard to imagine, most people underestimate

36. Graphical illustration of Moore’s law
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
Something that doubles frequently grows more quickly than most people realize!
A 2002 chip can hold about 15, chips inside itself

37. 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.”

38. Design needs Design technology
Achieving the metrics + fast & reliably
Enhanced productivity
Design – single stage
Multi stage - several abstraction levels

39. 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
Libraries/IP: Incorporates pre-designed implementation from lower abstraction level into higher level.
Behavioral
specification
Behavior
synthesis
Cores 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
Logic
synthesis
Gates/
Cells
To final implementation

40. 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

41. Architectural perspective Physical
Multiple perspectives for visualisation of a system
Functionality perspective
Environmental
User I/F or Operator perspective
System
Performance
Architectural perspective
Physical

42. 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

43. 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

44. Models Conceptual model Physical model Analogue model
Mathematical model
Numerical model
Computational model
Implementation
Assumptions & accuracy

45. 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)

46. 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

47. 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)

48. 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

49. 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 !

50. 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

51. 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

52. 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.

53. 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

54. 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

55. 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

56. 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.

57. 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)

58. UML is the latest manifestation
continued
UML is the latest manifestation
becoming prevalent in complex embedded system design

59. 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.

60. 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

61. Design productivity exponential increase
100,000
10,000
1,000
(K) Trans./Staff – Mo.
Productivity
100 10 1
0.1
0.01
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
2001
2003
2005
2007
2009
Exponential increase over the past few decades

62. The co-design ladder In the past: Hardware/software “codesign”
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.

63. 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

64. 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
Logic transistors per chip
(in millions)
100
1000
Gap 10
Productivity
(K) Trans./Staff-Mo.
100
IC capacity 1 10
0.1 1
productivity
0.01
0.1
0.001
0.01
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
2001
2003
2005
2007
2009

65. 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 / transistors/month
Designer cost increase from $1M to $300M

66. 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, designer=5000 trans/month
Each additional designer reduces for 100 trans/month
So 2 designers produce 4900 trans/month each
60000 15 16 16 18
50000 19
40000 24 23
30000
Months until completion
20000 43
Individual
10000 10 20 30 40
Number of designers

67. 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