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Embedded Systems Introduction L1. References 1.Embedded Systems Design, Steve Heath, Elsevier 2.Embedded Systems Design, Frank Vahid & Tony Givargis,

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Presentation on theme: "Embedded Systems Introduction L1. References 1.Embedded Systems Design, Steve Heath, Elsevier 2.Embedded Systems Design, Frank Vahid & Tony Givargis,"— Presentation transcript:

1 Embedded Systems Introduction L1

2 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

3 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 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 less These processors make these devices sophisticated, versatile and inexpensive Toys, mobile phones, kitchen appliances, even pens

6 A “short list” of embedded systems And the list goes on and on 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 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

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 preprocessorPixel coprocessor A2D D2A JPEG codec DMA controller Memory controllerISA bus interfaceUART 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 Size Performance Power NRE cost Microcontroller CCD preprocessorPixel coprocessor A2D D2A JPEG codec DMA controller Memory controllerISA bus interfaceUARTLCD 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 Peak revenue Peak revenue from delayed entry Market rise Market fall W2W 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)/2W 2 )*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 Delayed entry Peak revenue Peak revenue from delayed entry Market rise Market fall W2W Time D On-time Delayed Revenues ($)

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 = 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

21 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

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 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 Custom ALU DatapathController Program memory Assembly code for: total = 0 for i =1 to … Control logic and State register Data memory IRPC DatapathController Control logic State register Data memory index total + IRPC Register file General ALU Datapath Controller Program memory Assembly code for: total = 0 for i =1 to … Control logic and State register Data memory General-purpose (“software”)

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 General- purpose processor Single- purpose processor Application- specific processor Desired functionality

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 IRPC Register file General ALU Data pathController 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 IRPC Registers Custom ALU DatapathController 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 source drain channel oxide gate Silicon substrate IC package IC

30 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 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 1,000 100 10 1 0.1 0.01 0.001 Logic transistors per chip (in millions) 19811983 1985198719891991199319951997 19992001 2003200520072009 Note: logarithmic scale

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

36 Graphical illustration of Moore’s law 19811984198719901993199619992002 Leading edge chip in 1981 10,000 transistors Leading edge chip in 2002 150,000,000 transistors Something that doubles frequently grows more quickly than most people realize! –A 2002 chip can hold about 15,000 1981 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 Libraries/IP: Incorporates pre-designed implementation from lower abstraction level into higher level. System specification Behavioral specification RT specification Logic specification 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 System synthesis Behavior synthesis RT synthesis Logic synthesis Hw/Sw/ OS Cores RT components Gates/ Cells Model simulat./ checkers Hw-Sw cosimulators HDL simulators Gate simulators

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

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 1.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.

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) Object-Oriented Design method (OOD)

58 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 Exponential increase over the past few decades 100,000 10,000 1,000 100 10 1 0.1 0.0 1 1983 1981 1987 1989 1991 1993 1985 1995 1997 1999 2001 2003 2005 2007 2009 Productivity (K) Trans./Staff – Mo.

62 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.

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 General- purpose processor ASIP Single- purpose processor Semi-customPLDFull-custom General, providing improved: Customized, providing improved: Power efficiency Performance Size Cost (high volume) Flexibility Maintainability NRE cost Time- to-prototype Time-to-market Cost (low volume)

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 1,000 100 10 1 0.1 0.01 0.001 Logic transistors per chip (in millions) 100,000 10,000 1000 100 10 1 0.1 0.01 Productivity (K) Trans./Staff- Mo. 1981198319851987 198919911993 19951997199920012003200520072009 IC capacity productivity Gap

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 / 5000 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”) 102030400 10000 20000 30000 40000 50000 60000 43 24 19 16 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

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

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