±30 Years of IBM / U.C. Berkeley Synergy in Research

1. ±30 Years of IBM / U.C. Berkeley Synergy in Research Dave Patterson October 2005 Pardee Professor of Computer Science, UC Berkeley President, Association for Computing Machinery

2. Outline • Last 30 years of IBM/UC Berkeley research synergy • Relational Data Bases • Reduced Instruction Set Computers • Redundant Arrays of Inexpensive • Next 30 years • Topics: Technology push, Customer pull • New modes of pursuing research in 21st century

3. “It's slow, but it gets there.'' Interactive Graphics & Retrieval System (INGRES) 1973-79 • Codd publishes relational model in 1970 + debate • Inspired System R at IBM and INGRES at Berkeley • System R led to SQL • INGRES + System R people technical leadership of many data base companies • $15B year industry 2005 • 1988 ACM Systems SW Award for Ingres & System R System R: Chamberlin, Astrahan, Blasgen, Gray*, King, Lindsay*, Lorie, Mehl, Price, Putzolu, Selinger, Schkolnick*, Slutz, Traiger*, Wade, Yost UC: Mike Stonebraker, Gene Wong,Eric Allman, Bob Epstein*, Paula Hawthorn*, Jerry Held*, Carol Youseffi*, + 26 others *UC Berkeley PhD

4. RISC Reduced Instr. Set Computers ’80-’85 • John Cocke Compiler-oriented, pipelined architecture  24-bit ECL minicomputer, PL.8 • Mead/Conway VLSI + VAX  RISC I & II at UC32-bit microprocessor for C, Unix • Stanford MIPS: 32-bit microprocessor for Pascal • Commercial CPUs: ARM, Power, MIPS, SPARC, … • RISC sales 2005 ~ 109 embedded RISC MPUs IBM:John Cocke, Fran Allen, George Radin, Mark Auslander, … UC: David Patterson, Carlo Sequin, + ~ 16 students Stanford: John Hennessy + ~ 8 students

5. Close Up: Porsche on RISC chip Used cars to evangelize RISC (sports car) vs. CISC (Cadillac)

6. Redundant Array of Inexpensive Disks (1987-93) • “Use PC disks to build fast, reliable I/O to pace RISC?” • RAID I • Sun 4/280, 128 MB of DRAM, • 4 dual-string SCSI controllers, • 28 5.25” 340 MB disks + SW • RAID II • Gbit/s net + 144 3.5” 320 MB disks • 1st Network Attached Storage • Hagar (IBM Almaden Research) • Non-volatile caching, fault tolerance, distributed spares, EVENODD codes, … • IBM AS/400: RAID 5 patent • “Case for RAID” spread like virus • Products from IBM, Compaq, EMC, … • Today RAID ~ $15B industry; 80% of server disks in RAID IBM: Mike Mitoma, Jai Menon, Jim Brady, … UC: Randy Katz, David Patterson, Peter Chen, Ann Chevernak, Garth Gibson, Ed Lee, Ethan Miller, … RAID

7. More Recent Projects (too soon to tell) • Autonomic Computing at IBM • Automatically managed data centers • Self-* (optimize, repair, protect, …) • Recovery-Oriented Computing at Berkeley and Stanford • More dependable by recovering fast • Fast-* (notice error fast, diagnose error fast, fix error fast, reboot fast)

8. +30 Years of Research • Push of Technology • Pull of Customer Demand • New modes of long-term research • How do more efficiently? • New funding models?

9. Push of Technology • Statistics and IT • Statistical and Machine Learning as new AI • Statistics/randomization and Theory • Statistical and Machine Learning to Understand Large Systems • Understand behavior from millions of measurements

10. Push of Technology • Future is parallel • CS 2.0 - Time to rethink programming languages, environments, OS, … • We’ve heard this before; what’s different this time?

11. Conventional Wisdom (CW) in Computer Architecture • Old CW: Multiplies are slow, loads are fast • New CW: Memory slow (140 clocks to DRAM) • Old CW: Power is free, Transistors expensive • New CW: Power is expensive, Transistors free • Can put more on chip than can afford to turn on • Old CW: Uniprocessor performance 2X / 1.5 yrs • New CW: Power Wall + Memory Wall = Brick Wall • Uniprocessor performance only 2X / 5 yrs • New CW: 2X CPUs per socket / ~ 2 years since • More simpler processors are more power efficient

12. Uniprocessor Performance (SPECint)

13. Massively Parallel Socket (mMMP) • Processor is new transistor? • Intel 4004 (1971): 4-bit processor,2312 transistors, 0.4 MHz, 10 micron PMOS, 11 mm2 chip • RISC II (1983): 32-bit, 5 stage pipeline, 40,760 transistors, 3 MHz, 3 micron NMOS, 60 mm2 chip • 4004 shrinks to ~ 1 mm2 at 3 micron • 125 mm2 chip, 65 nm CMOS = 2312 RISC IIs + Icache + Dcache • RISC II shrinks to ~ 0.02 mm2 at 65 nm • Caches via DRAM or 1 transistor SRAM (www.t-ram.com) ? • Proximity Communication via capacitive coupling at > 1 TB/s ?(Ivan Sutherland @ Sun / Berkeley)

14. Pull of Customer Demand • Cost-of-purchase/Performance • 20th Century Homerun • Benchmarks critical to making progress • What neglected while pursuing Cost-Performance? • Dependability - PCs drop memory parity • Cost of Ownership much larger than Cost of Purchase • In 2004, 1% of U.S. households were victims of successful phishing attacks. • 17% of businesses received threats of being shut down by denial-of-service attacks

15. Pull of Customer Demand • SPUR supersedes Cost-Performance in 21st century • Security/Privacy – safe to use, store • As safe as 20th century banking? • Usability – cost of ownership • Ownership/purchase ratio = 20th century radio? • Reliability – really works • As reliable as 20th century telephony • Need benchmarks involving people to make progress, as people are major challenge in each aspect of SPUR

16. New Models of Pursuing Research? • 20th-Century model of success Research: • Long-term industrial research + Gov’t funded long-term academic research • NAE report documents academic-industry synergy leads to 17 1B$+ industries

17. NAE Report: 17 1B$+ Industries

18. State of Research Funding Today • Most industry research shorter term • DARPA exiting long-term (experimental) IT research • ’03-’05 BAAs IPTO: 9 AI, 2 classified, 1 SW radio, 1 sensor net, 1 reliability, all have 12 to 18 month “go/no go” milestones • Academic led funding reduced 50% (so far) 2001 to 2004 • Faculty ≈ consultants in consortia led by defense contractor, get grants ≈ support 1-2 students (~ NSF funding level) • NSF swamped with proposals, conservative • 2000 to 6500 proposals in 5 years • IT has lowest acceptance rate at NSF (between 8% to 16%) • “Ambitious proposal” is a negative review • Even if get NSF funding, proposal reduced to stretch NSF $ e.g., we got 3 x 1/3 faculty, 6 grad students, 0 staff, 3 years • (To learn more, see www.cra.org/research)

19. DARPA Grand Challenge 10/8/05 • Autonomous vehicles complete 132 mile off-road course < 10 hours • Stanford 6 hrs, 53 min • CMU Red 7 hrs, 4 min • CMU Red Too 7 hrs, 14 min • Gray Insurance 7 hrs, 30 min • Gov’t-funded, academic researchers Top 3 spots in open competition • Defense contractors did not finish: 5th, 6th, 11th, 16th, 17th, 23rd / 23

20. Research More Efficiently? • Share common infrastructure (e.g., BSD Unix) vs. everyone do-it-themselves? • For example, recent RAMP project (Research Accelerator for Multiple Processors) • FPGA today = ~25 CPUs; 2X CPUs/18 months; MPP? • Berkeley, CMU, MIT, Stanford, Texas, Wash. agree on common multiboard FPGA platform • Single hardware design, make boards for participants • Share development of “gateware”, SW, documentation • Better ideas via cooperation than do-it-yourself? • 6 groups work evolve specifications, share work • Support from Xilinx, NSF infrastructure prop. • Attractive platform for HW & SW researchers? • New research standard, like BSD Unix?

21. Why RAMP Attractive for Research? SMP, Cluster, Simulator v. RAMP

22. New Research Funding Model? • Replicate research centers based primarily on industrial funding to expand IT market (and to train next generation of IT leaders) • Exciting, long term technical vision • Industry largely funds • N companies, where N is 1 to 10? • Berkeley Wireless Research Center (BWRC): @ $5M per year (50% industry, ~5-10 companies) • Stanford Network Research Center (SNRC): @ $5M per year (80% industry, ~5-10 companies) • MIT Tparty $4M per year (100% $ from 1: Quanta) • How far can centers scale? • Maybe only afford 20 Top 20 CS departments?

23. Summary • Past 30 yrs: IBM Research & Berkeley together helped create 3 10B$ industries • Relational DB, RISC, RAID • In 20th century Industry and Academia created 17 1B$+ IT industries (11 IBM and/or Berkeley) • Challenges to creating more $1B+ industries in next 30 yrs • Push: Statistics & CS, Parallelism • Pull: Security, Privacy, Usability, Reliability • Drop in funding for long term research => More participation and collaboration between academia and industry in 21st Century