1. Embedded System, A Brief
Introduction
Presented by
Subash Chandra Nayak
01EC3010, IIT Kharagpur

2. Part - 1

3. Introduction
Embedded Systems :Application-specific systems which contain hardware and software
tailored for a particular task and are generally part of a larger
system (e.g., industrial controllers)
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Characteristics
– Are dedicated to a particular application
– Include processors dedicated to specific functions
– Represent a subset of reactive (responsive to external inputs)
systems
– Contain real-time constraints
– Include requirements that span:
• Performance
• Reliability
• Form factor

4. Examples

5. Characteristics

6. Concepts of co-design
• Codesign
– The meeting of system-level objectives by exploiting the
trade-offs between hardware and software in a system
through their concurrent design
• Key concepts
– Concurrent: hardware and software developed at the
same time on parallel paths
– Integrated: interaction between hardware and software
developments to produce designs that meet performance
criteria and functional specifications

7. Essential components and
considerations
• Essential components :- Microprocessor / DSP core
- Sensors
- Converter ( A-D and D-A )
- Actuators
- Memory (on-chip and off-chip )
- Communication path with interfacing environment
• Essential considerations :- Response time ;- ( Real time system )
- Area, Cost, Power, Portability, Fault-tolerance

8. Design-flow in ES Design

9. A mix of Disciplines
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DSP, Communication, Control…..
Software Engineering
Programming Languages
Compiler and OS
Architecture, Processor and IO techniques
Parallel and Distributed computing
Real Time Systems
VLSI CAD

10. Part - 2

11. Models and Architecture
• Models :- Conceptual view of system’s functionality
- A set of functional objects and rules for composing these
objects.
• Architectures :- Abstract view of system’s functionality
- A set of implementation components and their connections

12. Modeling : Introduction
• Modeling starts with System Specification
• System Specification : Main purpose : To provide clear and
unambiguous description of the system function, and to
provide a documentation of initial design process
• It supports diverse models of computation
• It allows the application of CAD tools for design space
exploration, partitioning, SW-HW synthesis, validation and
testing
• It should not constrain the implementation options

13. Models and Modeling
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Models :- Conceptual views of system’s functionality ; A set of functional objects and
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One of the keys to a GOOD hardware/software Codesign process is a unified
representation the allows the functionality of the system (at various levels of abstraction)
to be specified in a manner that is “unbiased” towards either a hardware or software
implementation.
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Unified Representation –
– A representation of a system that can be used to describe its functionality
independent of its implementation in hardware or software
– Allows hardware/software partitioning to be delayed until trade-offs can be made
– Typically used at a high-level in the design process
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Provides a simulation environment after partitioning is done, for both hardware and
software designers to use to communicate
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Supports cross-fertilization between hardware and software domains
rules for composing these objects

14. Models And Modeling
• Models are used for design representation
• Design representation can be of three types
- Behavioral
- Physical
- Structural
• There are various methods of Designing ES namely
- Capture and Simulate : Schematic capture , simulation
- Describe and Synthesis : HDL , Behavioral and Logic
synthesis
- Specify-Explore-Rene : Executable specification and other
formal methods….

15. Models
• State Oriented Models :- FSM : Melay and Moore models
- Petri Nets
- Hierarchical Concurrent FSM ( HCFSM )
• Activity Oriented Models :- Data Flow Graph ( DFG )
- Flow Chart / Control Flow Graph ( CFG )
• Structure Oriented Models :- Components Connectivity Diagrams
- RT net lists, Gate net lists

16. Models
• Data Oriented Models :- Entry Relationship diagram
- Jackson’s Diagram
• Heterogeneous Models :- Control / Data Flow Graph
- Structure Chart
- Programming Languages : C, C++, Java, Verilog, VHDL, Esterel,
SDL (Speciation and Description Language), CSP (Communicating
Sequential Process), SpecCharts, StateCharts etc...
- Object Oriented Paradigm
- Program state Machine
- Queuing model
- Process Networks : Kahn’s Process Network
- Communicating Sequential Processes ( CSP )
- Synchronous Data Flow model ( SDF )

17. Models
• N numbers of Models for design representation !!! Now
question is which
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model to choose ???
DSP apps uses Data flow Models
Control Intensive apps
FSM Models
Similarly Event driven apps uses Reactive Models
Finally the choice of models largely depends on
personal tastes, Application Domains, Availability of
software and tools etc....

18. Architectures
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We must be clear about the architecture that we are going to use for
design of ES
It has also got a wide variety of choices, to be chosen according to the
given application.
The choices are as follows
Application-specific Architecture :- Controller Architecture
- Datapath Architecture
- Finite state machine with datapath
General Purpose Architecture :- CISC
- RISC
- Vector machine
- VLIW ( Very Long Instruction Word Computer )

19. System Specification
• For every design there exists an conceptual view
• Conceptual view depends on application
- Computation : Conceptualize as a Program
- Controller
: Conceptualize as a FSM
• Goal of specification language : To capture conceptual view
with minimum designer’s effort
• Ideal language : 1-to-1 mapping between conceptual model
and language construct
• Characteristics of commonly used conceptual models
- Concurrency
- Hierarchy
- Synchronization

20. Specification Language
Requirements I
• A good ES specification Language should have a bunch of
feature supported such as :-
• Concurrency :- Can exists at difference levels such as :# Job Level
# Task Level
# Statement Level
# Operation Level
# Bit Level
- Two types of concurrency within a behavior :# Data driven
# Control driven

21. Specification Language
Requirements II
• State Transitions :- System are often modeled as state-based, e.g. Controller
- difficult to capture using programming construct
• Hierarchy :- Required for managing system complexity
- Allows system modeler to focus on one sub-system at a time
- Two types of hierarchy :# Structural Hierarchy
# Behavioral Hierarchy
# Concurrent Decomposition :- fork-join , process
# Sequential Decomposition :- procedure, state machine

22. Specification Language
Requirements III
• Behavioral Completion :- Behavior completes when all computation performed
- Advantages : Behavior can be viewed with inter-level
transitions and allows natural decomposition into sequential
behavior
• Communication :- Concurrent behavior exchange data
- Are of two types
# Shared memory model
# Message passing model

23. Specification Language
Requirements IV
• Synchronization :- Needed when concurrent behavior executes at different
speeds
- Required when :# Data exchange between behavior
# Different activities must be performed simultaneously
- Types
# Control dependent :- by reset , fork-join etc...
# Data dependent :- synchronization by :# Common event
# Status detection
# Common variable

24. Specification Language
Requirements V
• Exception handling :- Occurrence of event terminates current computation
- Control transferred to appropriate next mode
- Ex :- Reset, Interrupt
• Timing :- Required to implement / represent real time situation
- Ex :Wait for 100 ns
A <= A+1 after 200ns etc..

25. Specification Languages
Examples
• A good ES specification Language should support all the
above characteristics of ES
• Essential Characteristics :# State Transition
# Exceptions
# Behavioral Hierarchy
# Concurrency
# Programming Construct
# Behavioral Completion
• Some commonly used languages for ES specification :VHDL, Verilog, Esterel, SDL, CSP, SpecChart, StateChart

26. Specification Languages
Examples : A comparison

28. Hardware/Software Partitioning
• Definition
– The process of deciding, for each subsystem, whether the
required functionality is more advantageously implemented
in hardware or software
• Goal
– To achieve a partition that will give us the required
performance within the overall system requirements (in
size, weight, power, cost, etc.)
• This is a multivariate optimization problem that when
automated, is an NP-hard problem

29. HW/SW Partitioning Issues
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Partitioning into hardware and software affects overall system
cost and performance
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Hardware implementation
– Provides higher performance via hardware speeds and
parallel execution of operations
– Incurs additional expense of fabricating ASICs
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Software implementation
– May run on high-performance processors at low cost (due
to high-volume production)
– Incurs high cost of developing and maintaining (complex)
software

30. Partitioning Approaches
• Start with all functionality in software and move
portions into hardware which are time-critical and
can not be allocated to software
(softwareoriented partitioning)
• Start with all functionality in hardware and move
portions into software implementation (hardwareoriented partitioning)

31. System Partitioning
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Structural :# Implement structure and then partition ...
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Functional :# System partitioning in the context of HW-SW partitioning is known
as functional partitioning
# Approach:- System’s functionality is described as collection of
indivisible functional objects
# Each system’s functionality is either implemented in either
hardware or software
# Advantages:- Enables better size/performance tradeoff
# Uses fewer objects
# Better for Algorithms / Humans
# Permits HW-SW solutions
# But is harder than graph partitioning

32. Partitioning Metrics
• Deterministic estimation techniques
– Can be used only with a fully specified model with all data
dependencies removed and all component costs known
– Result in very good partitions
• Statistical estimation techniques
– Used when the model is not fully specified
– Based on the analysis of similar systems and certain
design parameters
• Profiling techniques
– Examine control flow and data flow within an architecture to
determine computationally expensive parts which are
better realized in hardware

33. Binding Software
to Hardware
• Binding: assigning software to hardware components
• After parallel implementation of assigned modules, all design
threads are joined for system integration
– Early binding commits a design process to a certain course
– Late binding, on the other hand, provides greater flexibility
for last minute changes

34. Issues in Partitioning
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Specification abstraction level
Granularity
System-component allocation
Metrics and estimations
Partitioning algorithms
Objective and closeness functions
Partitioning algorithms
Output
Flow of control and designer interaction

35. Issues in Partitioning (cont.)
High Level Abstraction
Decomposition of functional objects
• Metrics and estimations
• Partitioning algorithms
• Objective and closeness functions
Component allocation
Outpu
t

36. Specification Abstraction
Levels
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Task-level dataflow graph
– A Dataflow graph where each operation represents a task
Task
– Each task is described as a sequential program
Arithmetic-level dataflow graph
– A Dataflow graph of arithmetic operations along with
some control operations
– The most common model used in the partitioning
techniques
Finite state machine (FSM) with datapath
– A finite state machine, with possibly complex expressions
being computed in a state or during a transition

37. Specification Abstraction Levels
(Cont.)
• Register transfers
– The transfers between registers for each machine state are
described
• Structure
– A structural interconnection of physical components
– Often called a netlist

38. Granularity Issues in Partitioning
• The granularity of the decomposition is a measure of the size
of the specification in each object
• The specification is first decomposed into functional objects,
which are then partitioned among system components
– Coarse granularity means that each object contains a large
amount of the specification.
– Fine granularity means that each object contains only a
small amount of the specification
• Many more objects
• More possible partitions
– Better optimizations can be achieved

39. System Component
Allocation
• The process of choosing system component types from among
those allowed, and selecting a number of each to use in a
given design
• The set of selected components is called an allocation
– Various allocations can be used to implement a
specification, each differing primarily in monetary cost and
performance
– Allocation is typically done manually or in conjunction with
a partitioning algorithm
• A partitioning technique must designate the types of system
components to which functional objects can be mapped
– ASICs, memories, etc

40. Metrics and Estimations Issues
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A technique must define the attributes of a partition that determine its
quality
– Such attributes are called metrics
• Examples include monetary cost, execution time,
communication bit-rates, power consumption, area, pins,
testability, reliability, program size, data size, and memory
size
• Closeness metrics are used to predict the benefit of grouping
any two objects
Need to compute a metric’s value
– Because all metrics are defined in terms of the structure (or
software) that implements the functional objects, it is difficult to
compute costs as no such implementation exists during
partitioning Two key metrics are used in hardware/software
partitioning
– Performance: Generally improved by moving objects to hardware
– Hardware size: Hardware size is generally improved by moving
objects out of hardware

41. Partitioning Approaches
• Traditional Approaches
– Take Objective function as a weighted sum along
with constrains considerations
– Aim:- To minimize Power, Delay, cost, Area
etc...
– Here is the objective function values which is
obviously multimodal with multiple maxima and
minima.
B
A
C
A, B - Local minima
C - Global minimum

42. Basic partitioning algorithms
• Clustering and multi-stage clustering [Joh67, LT91]
• Group migration (a.k.a. min-cut or Kernighan/Lin) [KL70,
FM82]
• Ratio cut [KC91]
• Simulated annealing [KGV83]
• Genetic evolution
• Integer linear programming

43. Functional Partitioning Algorithms
• For Hardware :# BUD
# Aparty
• For Systems :#
#
#
#
Vulcan I
Vulcan II
Cosyma
SpecSyn

44. Summary
• Partitioning heavily influence design quality
• Functional partitioning is necessary
• Executable specification enables
# Automation
# Exploration
# Documentation
• Variety of algorithm exist
• Variety of techniques exist for different applications