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Next Century Challenges for Computer Science and Electrical Engineering

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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
  • EECS Department at Berkeley
  • Student Enrollment Pressures
  • Random Thoughts and Recommendations
  • Summary and Conclusions

3
Agenda
  • The Information Age
  • EECS Department at Berkeley
  • Student Enrollment Pressures
  • Random Thoughts and Recommendations
  • Summary and Conclusions

4
A Personal Historical View
  • 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
    minaturization
  • 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
Late 20th Century Rise of the Information Age
  • Electronics computing information
    technology
  • Technologies crucial for manipulating large
    amounts of information in electronic formats
  • Hardware Semiconductors, optoelectronics, high
    performance computing and networking, satellites
    and terrestrial wireless communications devices
  • Software Computer programs, software
    engineering, software agents
  • Hardware-Software Combination Speech and vision
    recognition, compression technologies
  • Information industries assemble, distribute, and
    process information in a wide range of media,
    e.g., telephone, cable, print, and electronic
    media companies
  • 3 trillion world wide industry by 2010

6
View from California on the Importance of
Information Technology
  • 35 billion in 1995 sales (vs. 90 billion
    nationwide)
  • 27 of computer manufacturing industry
    employment 50 of computer peripheral industry
    employment 37 of nations venture capital
  • computers/electronics sector employment 176,400
    software sector employment 104,000
    telecomms/info tech employed 329,000
  • Approximately 28 billion for information
    technology RD
  • Exports 58.9 billion, more than half of
    Californias total
  • Bay region
  • 93,000 employed in computers/electronics, 80,000
    in telecomms, 59,000 in multimedia, 30,000
    software jobs in Santa Clara county alone (45,000
    new jobs statewide between 90-95)!
  • San Jose dominates NY as highest average wage
    city in country
  • Intense political pressure to increase the
    production of students with information
    technology skills

7
Software Jobs Go Begging
  • Americas New Deficit The Shortage of
    Information Technology Workers, Department of
    Commerce
  • Job growth exceeds the available talent
  • 1994-2005 1 million new information technology
    workers will be needed
  • Help Wanted The IT Workforce Gap at the Dawn of
    a New Century, ITAA
  • 190,000 unfilled positions for IT workers
    nationwide
  • Between 1986 and 1994, bachelor degrees in CS
    fell from 42,195 to 24,200 (43)

8
Robert Luckys Inverted Pyramid
9
Agenda
  • The Information Age
  • EECS Department at Berkeley
  • Student Enrollment Pressures
  • Random Thoughts and Recommendations
  • Summary and Conclusions

10
Student and Faculty Statistics
  • Faculty
  • EE 40.75 FTE
  • CS 37 FTE
  • Architecture, CAD, Signal Processing, Circuits
    faculty overlap
  • 83.75 authorized FTE
  • Undergraduate Program
  • 893.5 (515 in CS, 378.5 in EE) in B.S. program
  • 212 in B.A. program
  • 1105.5 total (66 CS, 34 EE)
  • Graduate Program
  • 300 EE
  • 200 CS

11
Departmental Culture
  • A shared view of computing joining mathematics
    and physics as core of the sciences and
    engineering
  • Large-scale interdisciplinary experimental
    research projects with strong industrial
    collaborations
  • Architecture RISC, RAID, NOW, IRAM, CNS-1, BRASS
  • Parallel Systems Multipole, ScaLAPACK, Spilt-C,
    Titanium
  • Berkeley Digital Library Project Environmental
    Data
  • InfoPad Portable Multimedia Terminal for
    Classroom Use
  • PATH Intelligent Highway Project, FAA Center of
    Excellence
  • Computation and algorithmic methods in EE
  • Circuit Simulation, Process Simulation, Optical
    Lithography
  • CAD Synthesis/Optimization, Control Systems
  • Increasing collaboration with other departments
    in Engineering and elsewhere on campus

12
Historical Perspective
  • Early-mid 1950s Computer engineering activity
    grows within EE department
  • Early 1960s Separate CS Department formed within
    College of Letters and Science
  • Early 1970s Forced merger--semi-autonomous CS
    Division within single EECS Department separate
    LS CS program for undergraduates continues
  • 1980s Strong collaborations between EE and CS in
    VLSI, CAD
  • 1990s Increasing interactions between EE
    systems/CS AI/vision EE comms/CS
    networking/distributed systems Intelligent
    Systems/Hybrid Control Systems
  • 1994-Present Very rapid growth in CS enrollments
  • 1996-1999 First CS Department Chair Goal to
    make symmetric the relationship between EE and CS

13
Departmental Structure
14
Faculty FTE Breakdown
  • EE
  • Signal Processing 4.5
  • Communication 3.0
  • Networks 2.5
  • CAD 3.5
  • ICs 5.0
  • Solid State MEMs 4.5
  • Process Tech. Man. 5.0
  • Optoelectronics 5.0
  • EM Plasma 2.25
  • Controls 3.0
  • Robotics 2.0
  • Bioelectronics (1.3)
  • Power 1.5
  • TOT 40.75 (1.3 P-in-R)
  • CS
  • Sci Comp 2.5
  • Architecture 5.0
  • Software 5.5
  • Theory 6.0
  • OS/Nets 4.5
  • MM/UI/Graphics 4.0
  • AI 5.5
  • DB 2.0
  • TOT 35 2 SOE Lecturers
  • DEPARTMENT 77.75 FTE
  • 83.75 Authorized (2000)
  • 3 New 2 Continue

15
Agenda
  • The Information Age
  • EECS Department at Berkeley
  • Student Enrollment Pressures
  • Random Thoughts and Recommendations
  • Summary and Conclusions

16
UG Degree History at Berkeley
Degrees
About half are CS degrees
Year
17
Undergraduate Enrollment Trends
Total
EECS/EE
CS Total
EECS/CS
LS CS
18
College of Engineering Growth
  • Demand for CS skills far exceeds supply in
    California
  • University administration and Governor Wilson
    targets student and faculty growth in CS and
    engineering
  • Thrust at Berkeley is Bioengineering, Computer
    Science, and Engineering Science (Computational
    Engineering) across the College
  • EECS to accept 140 additional students in return
    for 6-8 new FTE over four years

19
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)

20
Old View of EECS
EE physics circuits signals control
CS algorithms programming comp systems AI
Physical World
Synthetic World
21
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
22
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
23
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

24
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

25
EECS 20 Structure and Interpretation of Systems
and Signals
  • Course Format Three hours of lecture and three
    hours of laboratory per week.
  • Prerequisites Basic Calculus.
  • Introduction to mathematical modeling techniques
    used in the design of electronic systems.
    Applications to communication systems, audio,
    video, and image processing systems,
    communication networks, and robotics and control
    systems. Modeling techniques that are 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.
    A Matlab-based laboratory is part of the course.

26
Topics Covered
  • Sets
  • Signals
  • Image, Video, DTMF, Modems, Telephony
  • Predicates
  • Events, Networks, Modeling
  • Frequency
  • Audio, Music
  • Linear Time Invarient Systems
  • Filtering
  • Sounds, Images
  • Convolution
  • Transforms
  • Sampling
  • State
  • Composition
  • Determinism
  • State Update
  • Examples
  • Modems, Speech models, Audio special effects,
    Music

27
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.

28
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.
  • Introduction 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.

29
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.

30
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.

31
Five Undergraduate Programs
  • Program I Electronics
  • Electronics
  • Integrated Circuits
  • Physical Electronics
  • Micromechanical Systems
  • Program II Communications, Networks, Systems
  • Computation
  • Bioelectronics
  • Circuits and Systems
  • Program III Computer Systems
  • Program IV Computer Science
  • Program V General

32
Agenda
  • The Information Age
  • EECS Department at Berkeley
  • Student Enrollment Pressures
  • Random Thoughts and Recommendations
  • Summary and Conclusions

33
Departments Strategic Plan
  • Human Centered Systems
  • User Interfaces Image, graphics, audio, video,
    speech, natural language
  • Information Management Intelligent Processing
  • Embedded and Network-connected computing
  • Hardware building blocks DSP, PGA, Comms
  • High performance, low power devices, sensors,
    actuators
  • OS and CAD
  • Ambient/Personalized/ Pervasive Computing
  • Software Engineering
  • Design, development, evolution, and maintenance
    of high-quality complex software systems
  • Specification verification
  • Real time software
  • Scalable algorithms
  • Evolution maintenance of legacy code

34
President Clintons IT2 Initiative
  • Software
  • Software Engineering
  • End-User Programming
  • Component-Based Software Development
  • Active Software
  • Autonomous Software
  • HCI and Info Mgmt
  • Speech/Natural Language
  • Information Visualization
  • Scalable Info Infrastructure
  • Deeply Networked Sys
  • Anytime, Anywhere Connect
  • Net Modeling/Simulation
  • High End Computing
  • Improving perform/efficiency of supercomputers
  • Creating a computation grid
  • Revolutionary computing
  • Advanced Computing for Science/Engineering
  • Advanced Infrastructure
  • Advanced Science Engineering Computation
  • Computer Science Enabling Technology
  • National Information Infrastructure Applications
  • Economic/Social Impacts of IT

35
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

36
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),

37
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?

38
Example Affymetrix www.affymetrix.com
  • Develops chips used in the acquisition, analysis,
    management of genetic information for
    biomedical research, genomics, clinical
    diagnostics
  • GeneChip system disposable DNA probe arrays
    containing specific gene sequences, instruments
    to process the arrays, bioinformatics software
  • IC company? Software company? Bioengineering
    company? Biotech company?

39
Should EE and CS Be Separate Departments?
  • EEs need extensive computing will spawn
    competing Computer Engineering activity anyway
  • Much productive collaborative at intersection of
    EE and CS CAD, Architecture, Signal Processing,
    Control/Intelligent Systems, Comms/Networking
  • But all quantitative fields are becoming as
    computational as EE e.g., transportation systems
    in CivilEng
  • Will natural center of gravity of CS move towards
    cognitive science, linguistics, economics,
    biology?

40
Agenda
  • The Information Age
  • EECS Department at Berkeley
  • Student Enrollment Pressures
  • Random Thoughts and Recommendations
  • Summary and Conclusions

41
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 contribute to the Biotech revolution of
    the next century
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