EECS at UC Berkeley

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 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%)

Robert Luckys Inverted Pyramid Information Technology Software Applications Software Middleware Software Algorithms Embedded Software System Software FPGA Design VLSI Design Circuit Design Hardware Device Design

Process Design Physics Increasing Numbers of Practitioners Technology 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 EE Devices and Circuits Physical Systems EE Signals and Systems Electrical Engineering Computer Science Computer Science Soda Hall

What happens to faculty who work at the intersections? EE/CS Faculty FTE Breakdown EE

CS 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)

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

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

250 200 150 100 50 0 158 142 286 About 243 half are CS degrees 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 Year

BA BS Undergraduate Enrollment Trends 1400 1200 1000 Total 800 600 EECS/EE 400 CS Total

200 EECS/CS L&S CS 0 88 89 90 91 92 93 94 95

96 The trend towards CS enrollment growth continues 97 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 (18961957) Old View of EECS Physical World EE CS

physics circuits signals control algorithms programming comp systems AI Synthetic World New View of EECS Intelligent Sys & Control Communications Sys Intelligent Displays EECS complex/electronics

systems Signal Proc Control EE Processing Devices MEMS Optoelectronics Circuits AI Software Robotics/Vision InfoPad IRAM components Reconfigurable Systems

Computing Systems Multimedia User Interfaces CS algorithms CAD Sim & Viz Programming Databases CS Theory MechE Sensors & Control Physical Sciences/

Electronics Materials Science/ Electronic Materials Design Sci Info Mgmt & Systems EECS Cognitive Science Computational Sci & Eng BioSci/Eng 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 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 selfpaced 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 selfscheduled 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 Departments Strategic Plan Human Centered Systems User Interfaces: Image, graphics, audio, video, speech, natural language Information Management & Intelligent Processing Embedded and Networkconnected 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 highquality complex software systems Specification & verification Real time software Scalable algorithms Evolution & maintenance of legacy code 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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