Title: Next Century Challenges for Computer Science and Electrical Engineering
1Next Century Challenges for Computer Science and
Electrical Engineering
- Professor Randy H. KatzUnited Microelectronics
Corporation Distinguished Professor - CS Division, EECS Department
- University of California, Berkeley
- Berkeley, CA 94720-1776 USA
2Agenda
- The Information Age
- Enrollment and Curriculum Challenges
- Random Thoughts and Recommendations
- Summary and Conclusions
3Agenda
- The Information Age
- Enrollment and Curriculum Challenges
- Random Thoughts and Recommendations
- Summary and Conclusions
4A 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 ???
5Robert Luckys Inverted Pyramid
And software jobs go begging ...
6Agenda
- The Information Age
- Enrollment and Curriculum Challenges
- Random Thoughts and Recommendations
- Summary and Conclusions
7Undergraduate Enrollment Trends
Total
EECS/EE
CS Total
EECS/CS
LS CS
8A 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)
9Old View of EECS
EE physics circuits signals control
CS algorithms programming comp systems AI
Physical World
Synthetic World
10New 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
11Design Sci
MechE Sensors Control
Info Mgmt Systems
EECS
Physical Sciences/ Electronics
Cognitive Science
Materials Science/ Electronic Materials
Computational Sci Eng
BioSci/Eng Biosensors BioInfo
12Observations
- 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
13Curriculum 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
14EECS 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.
15EE 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.
16CS 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.
17CS 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.
18CS 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.
19Agenda
- The Information Age
- Enrollment and Curriculum Challenges
- Random Thoughts and Recommendations
- Summary and Conclusions
2021st 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
2121st 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),
2221st 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?
23Agenda
- The Information Age
- Enrollment and Curriculum Issues
- Random Thoughts and Recommendations
- Summary and Conclusions
24Summary 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