EECS at UC Berkeley Next Century Challenges

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					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
                   Agenda

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

•   The Information Age
•   EECS Department at Berkeley
•   Student Enrollment Pressures
•   Random Thoughts and Recommendations
•   Summary and Conclusions
        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/wireless 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 --> Communications --> Systems
  Engineering --> Microelectronics --> ???
     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
     Software Jobs Go Begging

• “America’s 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%)
     Robert Lucky’s Inverted Pyramid
                                Information
                                Technology         Software
                          Applications Software
                          Middleware Software

             Algorithms   Embedded Software
                            System Software
                                 FPGA Design       Hardware
                                 VLSI Design
                                Circuit Design
                                Device Design
                                    Process
                                    Design
                                                  Technology
               Physics


Increasing Numbers
  of Practitioners
                   Agenda

•   The Information Age
•   EECS Department at Berkeley
•   Student Enrollment Pressures
•   Random Thoughts and Recommendations
•   Summary and Conclusions
             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
             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 L&S 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
              Departmental Structure
Cory Hall           Physical
     EE Devices
     and Circuits     Systems
                                         What happens to
      EE Signals          Electrical
                                         faculty who work
     and Systems         Engineering   at the intersections?


       Computer           Computer
                                               EE/CS
        Science            Science

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

•   The Information Age
•   EECS Department at Berkeley
•   Student Enrollment Pressures
•   Random Thoughts and Recommendations
•   Summary and Conclusions
         UG Degree History at Berkeley
#Degrees
   500
   450
   400
   350
   300     158                                        142
                                                              BA
   250
                                                              BS
   200
   150                                                      About
           286                                        243  half are
   100
                                                          CS degrees
    50
     0
         81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97
                              Year
 Undergraduate Enrollment Trends

1400
1200
       Total
1000
 800
       EECS/EE
 600
       CS Total
 400
       EECS/CS
 200
       L&S CS

   0
       88       89   90   91   92   93    94    95    96   97

       The trend towards CS enrollment growth continues
 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)
           Old View of EECS


            EE            CS
           physics     algorithms
           circuits   programming
           signals    comp systems
           control         AI


Physical                       Synthetic
World                          World
                      New View of EECS

Intelligent Sys & Control                                  Reconfigurable Systems
Communications Sys
Intelligent Displays                EECS                       Computing Systems
                                                                       Multimedia
                            complex/electronics                   User Interfaces
                                 systems
                            Signal Proc            AI
                              Control           Software
                                  Robotics/Vision

                            EE       InfoPad
                                      IRAM          CS
                    components                  algorithms
Processing                                                           Programming
Devices                                                                Databases
MEMS                                                                   CS Theory
Optoelectronics                       CAD
Circuits                            Sim & Viz
                     Design
        MechE         Sci
       Sensors &                   Info Mgmt
        Control                    & Systems



  Physical
                                        Cognitive
Sciences/
Electronics        EECS                  Science



      Materials
       Science/                   Computational
      Electronic                    Sci & Eng
                    BioSci/Eng
      Materials
                   Biosensors &
                      BioInfo
              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
           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
       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.
                      Topics Covered
• Sets                             •   Transforms
• Signals                          •   Sampling
   – Image, Video, DTMF, Modems,   •   State
     Telephony
• Predicates                       •   Composition
   – Events, Networks, Modeling    •   Determinism
• Frequency                        •   State Update
   – Audio, Music                  •   Examples
• Linear Time Invarient                 – Modems, Speech models,
  Systems                                 Audio special effects, Music

• Filtering
   – Sounds, Images
• Convolution
      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.
      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.
       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.
     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.
  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
                   Agenda

•   The Information Age
•   EECS Department at Berkeley
•   Student Enrollment Pressures
•   Random Thoughts and Recommendations
•   Summary and Conclusions
       Department’s Strategic Plan
• Human Centered Systems           • “Software” Engineering
  – User Interfaces: Image,           – Design, development,
    graphics, audio, video,             evolution, and maintenance
    speech, natural language            of high-quality complex
  – Information Management &            software systems
    Intelligent Processing               » Specification &
                                           verification
  – Embedded and Network-
    connected computing                  » Real time software
     » Hardware building blocks:         » Scalable algorithms
       DSP, PGA, Comms                   » Evolution & maintenance
     » High performance, low               of legacy code
       power devices, sensors,
       actuators
     » OS and CAD
     » Ambient/Personalized/
       Pervasive Computing
       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
        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), …
   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?
         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?
 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?
                   Agenda

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