Embedded Intro India05

Embedded Computing Systems Rajesh Gupta, UC San Diego, CA mesl . ucsd . edu

Outline: what are embedded systems and what is so interesting about them?

What are embedded systems?

Embedded system characteristics

Challenges in Embedded Systems research and education

"Embedded Everywhere"

Generally, part of a larger system that may not be a “computer”

works in a reactive , time- and energy-constrained environment.

employs a combination of hardware & software (a “computational engine”) to perform a specific function;

Software is used for providing features and flexibility

Hardware = {Processors, ASICs, Memory,...} is used for performance (& sometimes security)

An Embedded Computing System Application Specific Gates Processor Cores Analog I/O Memory DSP Code

Example: Automotive Embedded Systems Dominated by software and networking complexities

Control, processing, networking, …

Embedded, reactive controllers, for

Central locking system

Crash management

Power windows & seats

Airbag controller

etc.

90 % of all innovations are SW-driven

Embedded processing for

Multimedia system

Navigation system

Infotainment alone uses up to 20 processors

Challenges in automotive embedded software

Highly complex , networked , and distributed

Consider processing

70-80 electronic control units (ECUs) supporting hundreds of features

ECUs delivered by multiple suppliers, with their own software chains

Consider networking

Separate, integrated networks for power train, chassis, security, MMI, multimedia, body/comfort functions

Increasing interaction beyond car’s boundaries with devices, networks

Software development challenges:

hardware independence, information interdependence among subsystems, system composition, validation.

But that is just the beginning… Embedded Systems come in many (more) shapes.

Intel Montecito

Two 2-threaded 64b EPIC cores

Two threads hide memory latency on a single thread (TMT)

Total of 26.5 MB caches

1.72 Billion transistors, 596 mm 2 , 90nm

130 W; GBps

Generated clock frequency is a function of the measured voltage

-- 3X gain in power consumption

MicroController 16 bit Instr 32 bit datapath 4K*16bit program 4K*8bit data 1 GHz, 5-stage pipe Real-time scheduler Power control Temperature control Calibration

Computers + Radios = Mobile Platforms

Sensor Nodes as Wireless Networked Embedded Systems Source: Estrin, MOBICOM’03

Indeed, computing nodes are changing rapidly

New computing nodes and networks are no longer monolithic entities

High-end processing migrating to mobile computing, sensor computing

Very likely sources of innovations in future for mainstream computing.

Pointer to major sensor node platforms at http://mesl.ucsd.edu/gupta/SPOTSurl.html

Application Specific

Perform a single or tightly knit set of functions;

(not usually "general purpose”)

Constrained

Power, cost and reliability are often important attributes that influence design;

Application specific processor design can be a significant component of some embedded systems.

Customization yields lower area, power, cost, ...

Higher HW/software development overhead

design, compilers, debuggers, ...

Typical Characteristics

Real-Time Requirements

Hard-real time systems: where there is a high penalty for missing a deadline

e.g., control systems for aircraft/space probes/nuclear reactors; refresh rates for video, or DRAM.

Soft real-time systems: where there is a steadily increasing penalty if a deadline is missed.

e.g., laser printer: rated by pages-per-minute, but can take differing times to print a page (depending on the "complexity" of the page) without harming the machine or the customer.

However, the rate at which the image is delivered to the drum is a hard deadline, since the image will be lost otherwise.

Many systems have hard-deadlines imposed by the operations of peripherals, e.g., DRAM (refresh rate), disk (spin rate), cameras (scan rate), displays (refresh rate).

Modelling

the system to be designed, and experimenting with algorithms involved;

Refining (or “partitioning”)

the function to be implemented into smaller, interacting pieces;

HW-SW partitioning: Allocating

elements in the refined model to either (1) HW units, or (2) SW running on custom hardware or a general microprocessor.

Scheduling

the times at which the functions are executed. This is important when several modules in the partition share a single hardware unit.

Mapping (Implementing)

a functional description into (1) software that runs on a processor or (2) a collection of custom, semi-custom, or commodity HW.

ES Design: Task Ingredients Environ -ment Processor Analog I/O Memory ASIC DSP Code

Scope and Ingredients of ES Design Tasks

The specific issues that need to be addressed in ES design depend to some extent on

the scope of the application at hand, and

the richness of the system delivered

Dedicated system Digital Signal Processors General purpose processors Single Task General Task Mix Correlated Task Mix System + Application SW + SW environment Single Chip System + Applications Engine Control DFT

Programming with Time

E. G., Computing at the intersection of two different time topologies

/* monitor temperature */ do forever { measure temp; if (temp < setting) start furnace; else if (temp > setting + delta) stop furnace; } /* monitor time of day */ do forever { measure time; if (6:00am) setting = 72; else if (11:00pm) setting = 60; } /* monitor keypad */ do forever { check keypad; if (raise temp) setting++; else if (lower temp) setting--; } Computing system Environment Sense Actuate

Programming with Location

Enabled by technology advances

Outdoor, indoor, absolute, relative, assertive

Infrastructure for location

Dynamic resource discovery and binding

Transparent location updates

Monitor resources in their environment

Virtual resource naming, that is, resources referred to based on their expected location

Reactive to changes in the resource availability

Control resource usage: access timeouts.

Programming with location

Spatial programming: how to use the location information in spatial references

One is already seeing time in programming

Absolute and relative delays

Delays as uninterruptible actions

Timeouts, timed procedure calls, wait selects

Of course, we have seen time before…

A process controller with following modules

a clock tick comes every 20 ms when a clock module must run

a control module must run every 40 ms

three modules with soft constraints

operator display update; operator input; information logs

Can be done synchronously (in one program) or asychronously through multiple tasks.

while (1) {

wait for clock; do clock module;

if (time for control) do control;

else if (time for display update) do display;

else if (time for operator input) do operator input;

else if (time for mgmnt. request) do mgmnt. output;

}

Must have t1 + max(t2, t3, t4, t5)  20 ms

may require splitting tasks… gets complex!

Multi-tasking

Most tasks are event driven

Asynchronous implementation approaches

Foreground/background systems : 2 tasks

Foreground (interrupt)

on interrupt {

do clock module; if (time for control) do control;

}

Background

while (1) {

if (time for display update) do display;

else if (time for operator input) do operator;

else if (time for mgmnt. request) do mgmnt.;

}

Decoupling relaxes constraint: t1 + t2  20 ms

Multi-tasking: also called processes, threads

Requires task scheduling, communication, sharing among tasks.

So, then how to organize multiple tasks?

Cyclic executive (Static table driven scheduling)

static schedulability analysis

resulting schedule or table used at run time

TDMA-like scheduling

Event-driven non-preemptive

tasks are represented by functions that are handlers for events

next event processed after function for previous event finishes

Static and dynamic priority preemptive scheduling

static schedulability analysis

no explicit schedule constructed: at run time tasks are executed “highest priority first”

Rate monotonic, deadline monotonic, earliest deadline first, least slack

Continued…

Dynamic planning-based scheduling

Schedulability checked at run time for a dynamically arriving task

“ admission control”

resulting schedule to decide when to execute

Dynamic best-effort scheduling

no schedulability checking is done

system tries its best to meet deadlines

Extensive literature on best scheduling methods with increasing complexity of tasks and architectures.

(Real-Time Symposiums).

This research has had an impact on how OS’s are structured for embedded systems…

OS Classes

General Purpose

Open, multiple applications, memory protection, multiple units of failure

Temporally unpredictable, large overheads

Real Time OS

Closed, single application, no memory protection, single unit of failure, temporally predictable, small system overhead

Consumer Electronics OS are in between

(CE Linux): Open, multiple apps, memory protection, temporally predictable, small overhead

Major OS Structures monolithic microkernel cyclic executive exo kernel

A changing ecosystem of embedded systems “ Text” Timing- Dependent Data Real-World Sensor Inputs Single- or Few- Threaded Multi-Threaded OS Kernels/ Device Drivers MS Word cat Robotics Sensor Networks Distributed, Timing Dependent System MPI/Linda Distributed Robotics Squid TCP System/Internal Uncertainty Data/External Uncertainty Jeremy Elson, Microsoft

In the Human Body Source: Shkel (MAE), Ikei (Biomed), Zheng (ENT), UC Irvine

Into Fabrics and Buildings Ember radios and networks Source: Ember Networks

Summary: New “Computers”, New Challenges

Software development is a challenge with evolving processors

How to efficiently model, compile, target applications?

What is the right programming model for these systems?

What is the right set of OS, middleware services and API to provide a “usable” programming model?

Application modeling, programming for highly distributed, mobile, networked embedded systems

What happens in hardware versus software?

What is compiled and what happens dynamically?

What is done at the node, at the network?

How is awareness exploited?

Location, Energy, Connectivity

Getting it right means many more systems capabilities through software

Controlling power/energy usage, functional adaptivity, reliability, re/usability, availability, …

An emerging area for technical education

The design of embedded systems draws upon several disparate disciplines in CS and EE.

Application domain (Signal processing, ...)

Software engineering (Programming Languages, Compilers)

For implementing the software components; this can be a major component of several systems.

VLSI (computer aided) design

For implementing the custom and semi-custom hardware components.

Parallel/Distributed system design

since many embedded systems and multiprocessors are structured as a network of communicating processors; the network may be loosely coupled or tightly coupled.