Communications of the ACM

P H O T O C O U R T E S Y O F D A V I D P A T T E R S O N

that it doesn’t work,” Patterson says.

The men, of course, were academics as well as processor designers, and they were unsatisfied with how computer architecture was taught. “We were really unhappy with the quality of textbooks,” says Hennessy. “They were descriptive and comparative, but not in a numeric and quantitative fashion.” So they developed ways to measure whether a new processor design was an improvement, using metrics such as cost and speed. In 1989, they published their textbook, Computer Architecture: A Quantitative Approach. A year later, they published a version for undergraduates. Both are now in their sixth edition.

Garth Gibson, a professor of computer science at Carnegie Mellon University in Pittsburgh, PA, was a student in Patterson’s lab in the mid-1980s. “The book became a very good way for a lot of people to understand how computer architecture works and do a very good job at it,” Gibson says.

RISC has evolved as well, though many of the basics remain the same. The current version is RISC-V, an open source instruction set architecture allowing designers to add extensions that optimize a particular application. Such domain-specific architectures are the only option for improving performance as the benefits of Moore’s Law start to fade. “The circuits aren’t getting faster any more, so you’re going to have to change the instruction set architecture,” Patterson says with an air of excitement.

The impending end of Moore’s Law, and the demise of Dennard scaling, which said that as transistors get smaller their power density stays constant, are imposing new limitations on architecture, Hennessy says, and that makes RISC even more important. “Before, when transistors were doubling every two years or so, if you waste a few transistors, who cares? But when they’re not going up that fast, then efficiency becomes very important,” he says.

Patterson officially retired from Berkeley in 2016, although he still works there part-time. He also works at Google, developing domain-specific architectures for machine learning. Hennessy was president of Stanford from 2000 to 2016, and now directs the Knight-Hennessy Scholars program, which provides full scholarships to Stanford to graduate students from around the world. The program has just accepted its first class of 49 students from 16 countries.

Hennessy says the quantitative and
engineering approach he brought to
computer architecture served him well
as president when the financial cri-
sis hit in 2008 and Stanford, like other
schools, lost a quarter of its endow-
ment. He decided the university had
to cut its budget and do layoffs in one
fell swoop, rather than parceling out
the pain over time as many other insti-
tutions did. The next year its finances
had stabilized, and Stanford was able
to hire faculty and recruit new graduate
students again. “We had one harrowing
year, and then things were better,” he
says.

The men will share the Turing Award’s $1-million prize, supported by Google. Hennessy, who says he’s been fortunate in life, plans to donate his half to charity. Patterson, with several children and grandchildren who will need to pay college tuition, says he’ll invest his in education as a consumer.

The two came to computing along different paths. Patterson stumbled into it; during his senior year as a math major at the University of California, Los Angeles, a math class he meant to take was cancelled, so instead he took a course in programming with Fortran. The experience grabbed him, and he went on to earn an M.S., then a Ph.D., from UCLA in computer science. He applied for a job at Berkeley and, when he had not heard a response, his wife urged him to call and ask, which got him an interview and, eventually, a job.

Hennessy was interested in computers in high school, and as a science project built a machine that used relays to play tic-tac-toe. “It both won me a prize and it also helped me win my wife, because it impressed her family sufficiently that they thought ‘well, maybe this guy’s going to be okay’,” he says. He earned a B.S. in electrical engineering from Villanova University, and an M.S. and Ph.D. in computer science from the State University of New York at Stony Brook.

Both encourage young computer scientists to take risks as they did. “It wasn’t clear that that was the safest path to tenure, to rock conventional wisdom, but we believed in what we were doing, and that worked out pretty well,” Patterson says.