Chess Review October 4, 2006 Alexandria, VA Edited and presented by Educating a New Generation of Students in Embedded Systems Edward A. Lee Chair of EECS, UC Berkeley

ITR Review, Oct. 4, 2006"Educating Students", Lee2 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.

ITR Review, Oct. 4, 2006"Educating Students", Lee3 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.

ITR Review, Oct. 4, 2006"Educating Students", Lee4 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.

ITR Review, Oct. 4, 2006"Educating Students", Lee5 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 Systems CE290I Control and Information Management ME233 Advanced Control CS270 Algorithms EE 249 Embedded System Design EE290O Model Integrated Computing EE290N Concurrent embedded software EE291E Hybrid Systems CS262 Computer Networks EE192/ME102 Mechatronics Design ME239 Advanced Design and Automation EE228A High Speed Communication Networks CS152/252 Architecture EE141/142/241/242 Analog and Digital Design EECS145M/145L Microcomputer/electronics EE125/128 Introductory controls and robotics EE20: Structure and Interpretation of Signals and Systems Robotics and Unmanned Vehicles Traffic control Habitat Monitoring Systems Biology micro architecture system models algorithms

ITR Review, Oct. 4, 2006"Educating Students", Lee6 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

ITR Review, Oct. 4, 2006"Educating Students", Lee7 Current Role in EECS, Undergrad eecs 20 structure and interpretation of signals and systems eecs 121 digital communication eecs 123 digital signal processing eecs 120 signals and systems eecs 126 probability and random processes eecs 122 communication networks eecs 125 robotics

ITR Review, Oct. 4, 2006"Educating Students", Lee8 Future Role in EECS Undergrad eecs 20 structure and interpretation of signals and systems eecs 121 digital communication eecs 123 digital media & signal processing eecs 120 signals and systems eecs 126 probability and random processes eecs 122 communication networks eecs 125 robotics eecs xxx embedded software eecs xxx hybrid and embedded systems

ITR Review, Oct. 4, 2006"Educating Students", Lee9 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.

ITR Review, Oct. 4, 2006"Educating Students", Lee10 EECS reception Under- graduate lounge Classroom Class- room Office of the Chair Main entrance Secondary entrance Courtyard Conference Instruc- tional lab Honor society Main corridor National Instruments Embedded Systems Design Lab Main elevators Class- room ClassroomClass- room Classroom Wong Wireless Foundations Center

ITR Review, Oct. 4, 2006"Educating Students", Lee11 Outreach to the College of Engineering E.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.

ITR Review, Oct. 4, 2006"Educating Students", Lee12 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.

ITR Review, Oct. 4, 2006"Educating Students", Lee13 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