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 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 – : 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

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 nation’s 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 R&D Exports: $58.9 billion, more than half of California’s 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

Software Jobs Go Begging “America’s New Deficit: The Shortage of Information Technology Workers,” Department of Commerce –Job growth exceeds the available talent – : 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 Software Hardware Technology Applications Software System Software Middleware Software Embedded Software FPGA Design VLSI Design Circuit Design Device Design Process Design Increasing Numbers of Practitioners Algorithms Physics Information Technology

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

Student and Faculty Statistics Faculty –EE: FTE –CS: 37 FTE –Architecture, CAD, Signal Processing, Circuits faculty “overlap” –83.75 authorized FTE Undergraduate Program –893.5 (515 in CS, in EE) in B.S. program –212 in B.A. program – total (66% CS, 34% EE) Graduate Program –300 EE –200 CS

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 : First CS Department Chair; Goal to make symmetric the relationship between EE and CS

Departmental Structure Electrical Engineering Computer Science EE/CS What happens to faculty who work at the intersections? Cory Hall EE Devices and Circuits EE Signals and Systems Computer Science Soda Hall Physical Systems

Faculty FTE Breakdown EE –Signal Processing: 4.5 –Communication: 3.0 –Networks: 2.5 –CAD: 3.5 –ICs: 5.0 –Solid State & MEM’s: 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: (+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: SOE Lecturers –DEPARTMENT: FTE Authorized (2000) 3 New + 2 Continue

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

UG Degree History at Berkeley Year #Degrees About half are CS degrees

Undergraduate Enrollment Trends L&S CS EECS/CS CS Total EECS/EE Total The trend towards CS enrollment growth continues

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

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 ( )

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

New View of EECS EE components CS algorithms EECS complex/electronics systems Processing Devices MEMS Optoelectronics Circuits CAD Sim & Viz Programming Databases CS Theory Intelligent Sys & Control Communications Sys Intelligent Displays Reconfigurable Systems Computing Systems Multimedia User Interfaces Robotics/Vision InfoPad IRAM Signal Proc Control AI Software

EECS Info Mgmt & Systems Cognitive Science Computational Sci & Eng BioSci/Eng Biosensors & BioInfo Materials Science/ Electronic Materials Physical Sciences/ Electronics MechE Sensors & Control Design Sci

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 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

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 –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

President Clinton’s IT 2 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

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 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

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