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Next Century Challenges for Computer Science and Electrical Engineering

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Professor Randy H. Katz United Microelectronics Corporation Distinguished Professor CS Division, EECS Department University of California, Berkeley – PowerPoint PPT presentation

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Title: Next Century Challenges for Computer Science and Electrical Engineering


1
Next Century Challenges for Computer Science and
Electrical Engineering
  • Professor Randy H. Katz United Microelectronics
    Corporation Distinguished Professor
  • CS Division, EECS Department
  • University of California, Berkeley
  • Berkeley, CA 94720-1776 USA

2
Agenda
  • The Information Age
  • Enrollment and Curriculum Challenges
  • Random Thoughts and Recommendations
  • Summary and Conclusions

3
Agenda
  • The Information Age
  • Enrollment and Curriculum Challenges
  • Random Thoughts and Recommendations
  • Summary and Conclusions

4
A Personal Historical Tour
  • 20th Century as Century of the Electron
  • 1884 Philadelphia Exposition--Rise of EE as a
    profession
  • 1880s Electricity harnessed for communications,
    power, light, transportation
  • 1890s Large-Scale Power Plants (Niagara Falls)
  • 1895 Marconi discovers radio transmission/wireles
    s telegraphy
  • 1905-1945 Long wave/short wave radio, television
  • 1900s-1950s Large-scale Systems Engineering
    (Power, Telecomms)
  • 1940s-1950s Invention of the Transistor
    Digital Computer
  • 1960s Space program drives electrical component
    miniaturization
  • 1970s Invention of the Microprocessor/rise of
    microelectronics
  • 1980s-1990s PCs and data communications
    explosion
  • Power Engineering --gt Communications --gt Systems
    Engineering --gt Microelectronics --gt ???

5
Robert Luckys Inverted Pyramid
And software jobs go begging ...
6
Agenda
  • The Information Age
  • Enrollment and Curriculum Challenges
  • Random Thoughts and Recommendations
  • Summary and Conclusions

7
Undergraduate Enrollment Trends
Total
EECS/EE
CS Total
EECS/CS
LS CS
8
A New Vision for EECS
  • If we want everything to stay as it is, it will
    be necessary for everything to change.
  • Giuseppe Tomasi Di Lampedusa (1896-1957)

9
Old View of EECS
EE physics circuits signals control
CS algorithms programming comp systems AI
Physical World
Synthetic World
10
New View of EECS
EECS complex/electronics systems
Intelligent Sys Control Communications Sys
Intelligent Displays
Reconfigurable Systems Computing
Systems Multimedia User Interfaces
EE components
CS algorithms
Signal Proc Control
AI Software
Robotics/Vision InfoPad IRAM
Programming Databases CS Theory
Processing Devices MEMS Optoelectronics Circuits
CAD Sim Viz
11
Design Sci
MechE Sensors Control
Info Mgmt Systems
EECS
Physical Sciences/ Electronics
Cognitive Science
Materials Science/ Electronic Materials
Computational Sci Eng
BioSci/Eng Biosensors BioInfo
12
Observations
  • Introduction to Electrical Engineering course is
    really introduction to devices and circuits
  • Freshman engineering students extensive
    experience with computing significantly less
    experience with physical systems (e.g., ham
    radio)
  • Insufficient motivation/examples in the early EE
    courses excessively mathematical and
    quantitative
  • These factors drive students into the CS track

13
Curriculum Redesign
  • EECS 20 Signals and Systems
  • Every EECS student will take
  • Introduction to Signals and Systems
  • Introduction to Electronics
  • Introduction to Computing (3 course sequence)
  • Computing emerges as a tool as important as
    mathematics and physics in the engineering
    curriculum
  • More freedom in selecting science and mathematics
    courses
  • Biology becoming increasing important

14
EECS 20 Structure and Interpre-tation of Systems
and Signals
  • Course Format 3 hrs lecture, 3 hrs lab per week
  • Prerequisites Basic Calculus
  • Intro to mathematical modeling techniques used in
    design of electronic systems. Apps to comm
    systems, audio, video, and image processing
    systems, comm networks, and robotics and control
    systems. Modeling techniques introduced include
    linear-time-invariant systems, elementary
    nonlinear systems, discrete-event systems,
    infinite state space models, and finite automata.
    Analysis techniques introduced include frequency
    domain, transfer functions, and automata theory.
    Matlab-based lab is part of the course.

15
EE 40 Introduction to Microelectronics Circuits
  • Course Format Three hours of lecture, three
    hours of laboratory, and one hour of discussion
    per week.
  • Prerequisites Calculus and Physics.
  • Fundamental circuit concepts and analysis
    techniques in the context of digital electronic
    circuits. Transient analysis of CMOS logic gates
    basic integrated-circuit technology and layout.

16
CS 61A The Structure and Interpretation of
Computer Programs
  • Course Format 3 hrs lecture, 3 hrs discussion,
    2.5 hrs self-paced programming laboratory per
    week.
  • Prerequisites Basic calculus some programming.
  • Intro to programming and computer science.
    Exposes students to techniques of abstraction at
    several levels (a) within a programming
    language, using higher-order functions, manifest
    types, data-directed programming, and
    message-passing (b) between programming
    languages, using functional and rule-based
    languages as examples. It also relates these to
    practical problems of implementation of languages
    and algorithms on a von Neumann machine. Several
    significant programming projects, programmed in a
    dialect of LISP.

17
CS 61B Data Structures
  • Course Format 3 hrs lecture, 1 hr discussion, 2
    hrs of programming lab, average of 6 hrs of
    self-scheduled programming lab per week.
  • Prerequisites Good performance in 61A or
    equivalent class.
  • Fundamental dynamic data structures, including
    linear lists, queues, trees, and other linked
    structures arrays strings, and hash tables.
    Storage management. Elementary principles of
    software engineering. Abstract data types.
    Algorithms for sorting and searching.
    Introduction to the Java programming language.

18
CS 61C Machine Structures
  • Course Format 2 hrs lecture, 1 hr discussion,
    average of six hrs of self-scheduled programming
    laboratory per week.
  • Prerequisites 61B.
  • The internal organization and operation of
    digital computers. Machine architecture, support
    for high-level languages (logic, arithmetic,
    instruction sequencing) and operating systems
    (I/O, interrupts, memory management, process
    switching). Elements of computer logic design.
    Tradeoffs involved in fundamental architectural
    design decisions.

19
Agenda
  • The Information Age
  • Enrollment and Curriculum Challenges
  • Random Thoughts and Recommendations
  • Summary and Conclusions

20
21st Century Challenge for Computer Science
  • Avoid the mistakes of academic Math departments
  • Mathematics pursued as a pure and esoteric
    discipline for its own sake (perhaps unlikely
    given industrial relevancy)
  • Faculty size dictated by large freshman/sophomore
    program (i.e., Calculus teaching) with relatively
    few students at the junior/senior level
  • Other disciplines train and hire their own
    applied mathematicians
  • Little coordination of curriculum or faculty
    hiring
  • Computer Science MUST engage with other
    departments using computing as a tool for their
    discipline
  • Coordinated curriculum and faculty hiring via
    cross-departmental coordinating councils

21
21st Century Challenges for Electrical Engineering
  • Avoid the trap of Power Systems Engineering
  • Student interest for EE physical areas likely to
    continue their decline (at least in the USA),
    just when the challenges for new technologies
    becoming most critical
  • Beginning to see the limits of semiconductor
    technology?
  • What follows Silicon CMOS? Quantum dots?
    Cryogenics? Optical computation? Biological
    substrates? Synthesis of electrical and
    mechanical devices beyond transistors
    (MEMS/nanotechnology)
  • Basic technology development, circuit design and
    production methods
  • Renewed emphasis on algorithmic and mathematical
    EE Signal Processing, Control, Communications
  • More computing systems becoming
    application-specific
  • E.g., entertainment, civilian infrastructure (air
    traffic control),

22
21st Century Challenges for EE and CS
  • 21st Century to be Century of Biotechnology?
  • Biomimetics What can we learn about building
    complex systems by mimicing/learning from
    biological systems?
  • Hybrids are crucial in biological systems Never
    depend on a single group of software developers!
  • Reliability is a new metric of system performance
  • Human Genome Project
  • Giant data mining application
  • Genome as machine language to be reverse
    engineered
  • Biological applications of MEMS technology assay
    lab-on-a-chip, molecular level drug delivery
  • Biosensors silicon nose, silicon ear, etc.
  • What will be more important for 21st century
    engineers to know more physics or more biology?

23
Agenda
  • The Information Age
  • Enrollment and Curriculum Issues
  • Random Thoughts and Recommendations
  • Summary and Conclusions

24
Summary and Conclusions
  • Fantastic time for the IT fields of EE and CS
  • As we approach 2001, we are in the Information
    Age, not the Space Age!
  • BUT, strong shift in student interest from the
    physical side of EE towards the algorithmic side
    of CS
  • Challenge for CS
  • Avoid mistakes of math as an academic discipline
  • Coordinate with other fields as they add
    computing expertise to their faculties
  • Challenge for EE
  • What will be the key information system
    implementation technology of 21st century?
  • Challenge for EE and CS
  • How to participate in the Biotech revolution of
    the next century
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