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
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
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.
Hennessy agrees, “You have to be
a little fearless, willing to take some
chances and work on things that are a
Neil Savage is a science and technology writer based in
© 2018 ACM 0001-0782/18/6 $15.00
and Hennessy discuss
their work in this exclusive