Chess ReviewOctober 4, 2006Alexandria, VA
Edited and presented by
Educating a New Generation of Students in Embedded Systems
Edward A. LeeChair of EECS, UC Berkeley
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Statement of Principles
Although computer-based embedded systems have been designed for more than 30 years, they have only recently emerged as an intellectual discipline distinct from the applications and distinct from both hardware and software technologies.
The embedded revolution requires a reexamination—and often a reinvention—of core abstractions of computing and systems engineering. All effective abstractions hide properties of the underlying systems, but the key to their effectiveness is that they hide the right properties. The core abstractions of computing, for example, do not include time, yet embedded computing systems depend critically on predictable timing. Engineering education and research needs to anticipate, shape, and guide this transformation. This has to be done through a partnership that includes specialists in computing, electrical engineering, and the application domains such as scientific instrumentation, manufacturing systems, automotive electronics, etc.
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The Goal
To create an integrated curriculum on computational systems theory and systems design practice with
– Concurrency– Composability– Time– Modularity– Security– Heterogeneity– Verifiability– Understandability
This systems theory must be at once computational and physical.
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The Challenge
Models for the physical world and for computation diverge.
– physical: time continuum, ODEs, dynamics– computational: a “procedural epistemology,” logic
There is a huge cultural gap.
Physical system models must be viewed as semantic frameworks, and theories of computation must be viewed as alternative ways of talking about dynamics.
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Research and Education at Berkeley
Large research projects(e.g. PATH, GSRC, CHESS)
Advanced courses (290 series)
Graduate courses (e.g. EE249: Embedded System Design: Modeling, Validation and Synthesis)
Undergraduate courses (e.g. EE20: Structure and Interpretation of Signals and Systems)
EE221A/222 Linear and Nonlinear SystemsCE290I Control and Information Management
ME233 Advanced ControlCS270 Algorithms
EE 249 Embedded System DesignEE290O Model Integrated Computing
EE290N Concurrent embedded softwareEE291E Hybrid Systems
CS262 Computer NetworksEE192/ME102 Mechatronics Design
ME239 Advanced Design and AutomationEE228A High Speed Communication Networks
CS152/252 ArchitectureEE141/142/241/242 Analog and Digital DesignEECS145M/145L Microcomputer/electronics
EE125/128 Introductory controls and robotics
EE20: Structure and Interpretation of Signals and Systems
Robotics and Unmanned Vehicles
Traffic control
HabitatMonitoring
Systems Biology
mic
roar
chite
ctur
esy
stem
mod
els
algo
rithm
s
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Build on our Introductory Course on Computational Signals and Systems
Berkeley has a required sophomore course for EE and CS students that addresses mathematical modeling of signals and systems from a computational perspective.
The web page at the right illustrates a broad view of feedback, where
the behavior is a fixed point solution to a set of
equations. This view covers both traditional
continuous feedback and discrete-event systems.
The textbook
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Current Role in EECS, Undergrad
eecs 20structure and
interpretation of signals and systems
eecs 121digital
communication
eecs 123digital signal processing
eecs 120signals and systems
eecs 126probability and
random processes
eecs 122communication
networks
eecs 125robotics
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Future Role in EECS Undergrad
eecs 20structure and
interpretation of signals and systems
eecs 121digital
communication
eecs 123digital media &
signal processing
eecs 120signals and systems
eecs 126probability and
random processes
eecs 122communication
networks
eecs 125robotics
eecs xxxembedded software
eecs xxxhybrid and
embedded systems
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The EECS Department Commitment
• Has secured $1.5M for facilities, $0.5M for equipment for an embedded systems design lab.
• Will make embedded systems a priority area for faculty hiring.
• Will commit resources to course development and instruction.
• Will work with other College of Engineering departments for maximum leverage.
• Will re-examine the curriculum for appropriate math, statistics, and computing requirements.
• Will coordinate with outside leaders at peer institutions worldwide.
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EECS reception
Under-graduate lounge
ClassroomClassroomClass-room
Office of the Chair
Main entrance
Secondary entrance
Courtyard
Conference
Instruc-tionallab
Honor society
Main corridor
NationalInstrumentsEmbedded Systems
Design Lab
Main elevators
Class-room
Classroom Class-room Classroom
Wong WirelessFoundations
Center
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Outreach to the College of EngineeringE.g.: CE290I: Control & Information Mgmt
[Sengupta]
Mathematical methods and information technologies for controlling CEE systems. Emphasizes designing component organizations that interact with the world in real-time to control a large system. Methods applied to transportation operations, supply chains, and structures. Management of design complexity by hierarchical specification, systematic use of simulation and verification tools, semantics, polymorphism, information management services, and compilation from high-level design languages.
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Why Should We Lead The Way?
• We have long track record of shaping and defining the core of the standard curriculum in several engineering specialties.
• We represent the strongest research programs in embedded systems:– wireless sensor networks– model-based design– embedded software– configurable hardware– hybrid systems modeling– bio-mimetic systems– wireless communications systems– power-aware systems
• Our partners in the College of Engineering have world-class research programs in manufacturing systems, automotive electronics, process control, mechatronics, transportation systems, and eco-systems.
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Involved Faculty at Berkeley
• Dave Auslander, Mechanical Engineering• Ahmad Bahai, Electrical Engineering• Alex Bayen, Civil and Environmental Engineering• Eric Brewer, Computer Science• David Culler, Computer Science• Stephen Derenzo, Electrical Engineering• Ron Fearing, Electrical Engineering• Karl Hedrick, Mechanical Engineering• Hami Kazerooni, Mechanical Engineering• Kurt Keutzer, Electrical Engineering• Ali M Niknejad, Electrical Engineering• Kris Pister, Electrical Engineering• Jan Rabaey, Electrical Engineering• Alberto Sangiovanni-Vincentelli, Electrical Engineering• Shankar Sastry, Electrical Engineering• Raja Sengupta, Civil and Environmental Engineering• Sanjit Seshia, Electrical Engineering• Claire Tomlin, Electrical Engineering• John Wawrzynek, Computer Science