ECE153a/253 Embedded Systems
Class Overview
Forrest Brewer
Class Overview
What is an Embedded System?
– Physical Constraints: Time, Cost, Power
– Software Engineering in Real Time
– Multiple Stimulus/Response loops
Principles of Structured Design
– Metrics and System Performance
– Correctness and Design Costs
– Specification, Modeling and Abstraction
Class Logistics
2 Weekly Lectures
– Papers to read (no textbook --)
– Ref: “Practical UML StateCharts in C/C++” Miro Samek
– Weekly Exercises (Homework) 25%
– Out Wednesday, due Wednesday before 3PM in box
Recitation Section 10%
– Graded only for undergrads, everyone should go!
Final Project + Presentation 25%
– Graduates – ‘open’ final project
– Undergraduates – directed lab
4 orchestrated Labs 40%
Lab Location
Linux or Windows can be used
– Beware path issues if moving between platforms
– You can install 14.3 on your own laptop
• Need to use VPN to access license off campus
2-person teams need to obtain:
– Digilent Spartan 3E Starter Board
• $179 from http:/5/www.digilentinc.com/Products/Detail.cfm?NavPath=2,400,792&Prod=S3EBOARD
• PMOD SPI Microphone (digilent site)
• Order asap! – labs start in 1 week
ECI Lab (HFH 1st floor)
– Xilinx 14.3 Suite
• Licenses served from 2100@license.ece.ucsb.edu
Class Labs
Xilinx/Digilent Spartan 3e
Card
– MicroBlaze/PicoBlaze
Processors
– Verilog/VHDL Programmable
Peripheral Devices
– EDK/SDK tools (ECI)
Each 2 person group
responsible for own card!
– Card: $179, microphone, <
$200/team
Graduate Section (ECE 253)
Extra Readings (See Course Bibliography)
Must Propose final project and have it approved. Final
project must use soft platform (i.e. Xilinx or Altera
FPGA – DE0-nano $79 is smaller/faster form factor –
beware platform issues!) Groups of 1-2 only.
Many possible sensors/control PMODS all 5/10 pin SPI
Beware that SPI is a ‘loose’ standard, be prepared for
at least 2 weeks to verify/validate interface to your
hardware in addition to design/coding time. I2C seems
more generally stable
We cannot accept last minute platform changes
Syllabus 1
I. Overview of Embedded Systems
– What is an Embedded System?
• Technology
– CPU/FPGA/DSP/ASIC
• Hardware and Software
• Real-time, limited resources
– Computation Models and Abstractions
• Why Abstract Models?
• Models: Circuit, RTL, Threads, Tasks
• Modeling Time
Syllabus 2
II. Finite-State Automata
– Overview of Finite Automata
– States (DFA/NFA)
– Sampling and Triggering
– Hierarchy and Concurrence (State Charts)
• Modality
• Decomposition
• C implementation
– NFA Models and Scheduling
III. Process Models
– Kahn Process Models
– SDF
Syllabus 3
IV. Data-Flow and Scheduling
– Loops and Timed Behavior
– Constraints, ASAP, ALAP, Resources
– Exact and Heuristic Scheduling
– Real-Time Task Scheduling
• Periodic and Priority Policies
• Rate-Monotone and Deadline Scheduling
• Priority Inversion
• Preemption, Overhead and Context
– ILP optimization (IBM CPLEX, LP_SOLVE)
Syllabus 4
V. Real-World:
– Sensors
– Signal Sampling/Noise and Jitter
• Conversion Issues
– Motors and Actuators
• DC/Servo, Stepper, Pulse-Drive
– Intro to PID Control
Syllabus 5
VI. Tricks of the Trade
A. Data Representation
B. Representation and Computation of
Functions
C. Speculation, Pipelining, Systolic
Computation, Trace Optimization
D. Real-Time Reprise
Embedded Systems
Computing systems performing
specific tasks within a framework of
real-world constraints
– Automotive: ECS, ABS; Aircraft
– Network Appliances: Routers, Modems
– Cell Phones, PDA, Mouse, E-Star Power
– Printers, Hand Mixers, Toasters, Tires!
Microprocessors are Ubiquitous
Embedded Systems
Everywhere!
Tire Pressure Sender
SmartPen
Characteristics of Embedded Systems
Part of larger system
– not a “computer with keyboard, display, etc.”
HW & SW application-specific – not G.P.
– application is known a-priori
– definition and development concurrent
Interact (sense, manipulate, communicate) with the
external world
Never terminate (ideally)
Operation is time constrained: latency, throughput
Other constraints: power, size, weight, heat, reliability
Increasingly high-performance (DSP) & networked
Slide courtesy of Mani Srivastava
Why Embed Computers?
Enablers
– New behaviors and applications (GPS, PDA, Wii)
Cost!
– Intelligent Control: workaround manufacturing
flaws (Auto ABS), replace antiquated controllers
(Toaster), combine functions (Cell Phone)
Remote Sensing and Control
– Expanding Human perception and effectiveness
Embedded Automotive
•More than 30% of the cost of a car is now in Electronics
•90% of all innovations will be based on electronic systems
Slide courtesy of Alberto Sangiovanni-Vincentelli
Why do we care? Some Market Tidbits...
Specialized devices and appliances replacing PCs
– variety of forms: set-top boxes, fixed-screen phones,
smart mobile phones, PDAs, NCs, etc.
– In 1997, 96% of internet access devices sold in the US
were PCs, by 2004, shipments far exceeded PCs
– 2009 Tire Pressure Sensors: 60-70M/yr, Smart cards 100-
200M/yr
Traditional Products
– dependent on computation systems
– Modern cars: ~100 processors running complex software
Slide courtesy of Mani Srivastava
Where are the CPUs?
Estimated 98% of 8 Billion CPUs produced in 2000 used for embedded apps
Where Has CS Focused? Where Are the Processors?
Direct
2%
Interactive Robots Vehicles
Computers 6% 12%
200M Servers, 13.5B Parts
per Year etc. per Year
Embedded Computers
Computers
80%
In Vehicles In Robots
Embedded
Look
Lookfor
forthe
theCPUs…the
CPUs…theOpportunities
OpportunitiesWill
WillFollow!
Follow!
Source: DARPA/Intel (Tennenhouse)
Design Issues
Complex Systems!
– How to get it working?
• (on time, on budget)
• Need for abstraction and design reuse
– How to test it?
• Unforeseen Behaviors (Air Bus!)
Real Time Physical Embedding
– Does it meet constraints?
– Design Budgeting: Power, Size, Cost, Reliability
– What are the exploitable design options?
Technology
Integrated Processors
– Nearly free in production
A/D, D/A, Sampling
– Interface Analog world to cheap computing
MEMS, NEMS, Opto-Devices
– Miniature Direct Coupling to Real World
Batteries, Solar Cells, Vibration
Scavenging, Thermal Gradient Cell
– Computation and Communication Power
“Traditional” Software Embedded Systems =
CPU + RTOS
Slide courtesy of Mani Srivastava
ASIC Hardware Embedded System
ASIC Features
Area: 4.6 mm x 5.1 mm
Speed: 20 MHz @ 10 Mcps
Technology: HP 0.5 m
Power: 16 mW - 120 mW
(mode dependent) @ 20
MHz, 3.3 V
Avg. Acquisition Time: 10 s
to 300 s
A direct sequence spread spectrum (DSSS) receiver ASIC
Slide courtesy of Mani Srivastava
ASIC Issues
Good:
– High performance custom peripherals
– Multiple heterogenous Cores
– Integrated A/D, D/A, timers …
– Low Cost, High performance on-chip
communication
– Low Part Cost in Volume
Bad:
– Very expensive ($5-$75M/design)
– Very High Risk (Several total failure points)
– Potentially impossible to Program even if
working!
Reconfigurable SoC
Other Examples
Atmel’s FPSLIC
(AVR + FPGA)
Altera’s Nios
(configurable
RISC on a PLD)
TI’s OMAP
(ARM Cortex+
Custom GPU+ TI
DSP)
Triscend’s A7 CSoC
Slide courtesy of Mani Srivastava
FPGA
CLB
Switchbox Routing
Channel
IOB
Channel
Routing
FPGA advantage:
performance of
parallel hardware
with the flexibility
of software
Configuration
Bit
FPGA Embedded RAM
Xilinx – Block SelectRAM
– 18Kb dual-port RAM arranged in columns
Altera – TriMatrix Dual-Port RAM
– M512 – 512 x 1
– M4K – 4096 x 1
– M-RAM – 64K x 8
Embedded System Design Flow
Environ Modeling
-ment the system, and algorithms involved;
Refining (or “partitioning”)
the function into smaller, interacting pieces
Test Bench Design
Abstractions from the Design, Communication,
Storage, and Computation resources
HW-SW partitioning: Allocation
(1) HW
(2) SW
Determine power and performance bounds
Scheduling
When are functions executed
Resource Arbitration
Mapping (Implementing)
(1) software, (2) Hardware,
(3) Coherence/Communication
Testing/Validation
Insitu with Design
DSP
Code
Many Implementation Choices
Microprocessors Speed Power Cost
Domain-specific processors
– DSP
– Network processors
– Microcontrollers
ASIPs
Reconfigurable SoC
FPGA
GateArray
ASIC
Full-Custom (COTS) High Low
Volume
Slide courtesy of Mani Srivastava
Hardware vs. Software Modules
Hardware = functionality implemented in custom
architecture
Software = functionality implemented stored
program
Key differences:
– Configurability, Adaptability
– Process Time Multiplexing
• software modules time multiplexed on a processor
• hardware modules often mapped to dedicated hardware
– Concurrency
• processors have serial “thread of control”
• dedicated hardware has concurrent activity
Slide courtesy of Mani Srivastava
Hardware-Software Architecture
A significant part of the system design
problem is deciding which parts are software,
and which are hardware
Issues:
– Cost of development
– System performance
– Upgrade potential
– Sales/Implementation Volume
– Availability of IP
– Development Time-Line
Slide courtesy of Mani Srivastava
IP-based Design
Slide courtesy of Mani Srivastava
Map Behavior to Architecture
Slide courtesy of Mani Srivastava
Metrics / Models / Abstractions
and Systematic Analysis
To make progress, we need objective means to evaluate
heterogeneous collections of components, to test and validate
correct operation and models to abstract system complexity.
Models of Computation
– Provide metrics on component and system performance
• Time, Throughput, Power?
– Abstract models as bounds on system behavior
• Provable or at least Simulation bound on system correctness
– Unfortunately– no complete, encompassing, provable model exists
• Lots of small provable sub-models: FSM, eFSM, SDL, Kahn Processes
• Lots of encompassing but undecidable models: RT-FSM, General Modal
Logic
In search of set of generally useful abstractions
– Embedded Systems a bit like software compilers in Lisp/Fortran era
This Class
Focus on tightly constrained environments and
high performance demands
– Multi-kHz sample rates
– Multiple Interrupt sources
– Relatively small memory, realistic bus environment
Will use HFSM approach to organize execution and
task dispatch (1-2kbytes)
Labs focus on software side of interface (hardware
issues in 153b).
Conceptual understanding of broader aspects of
real-time systems.
– Scheduling, Priority Inversion, Atomic Code Blocks
