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Parallel Computing Pioneer - Leslie G. Valiant
Gordon McKay Professor of Computer Science and
Applied Mathematics, Harvard University
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Leslie G. Valiant has conducted groundbreaking research in parallel
computation from the time he first became involved in the field. He took an
early interest in the central role that communication plays in parallel
computation. He developed an efficient randomized routing methodology for
general patterns of communication. This provided some positive evidence for
the possibility of general purpose parallel computing. This work in turn
led to his development, almost a decade later in 1989, of the bulk
synchronous parallel (BSP) model, intended to take the role of a unifying
"bridging" model for parallel computers and programs.
"When I started my research in the early 1970s, parallel computing was very
confusing as a field," says Valiant. "It contrasted starkly with some other
areas of computer science ‹ for instance, complexity theory had just
developed into a coherent and powerful science. However, despite its
frustrations, the field of parallelism did offer one attraction. It seemed
that there was one central question around which everything revolved: 'What
is the right model?' "
He has also contributed to several other areas of computer science. Some of
his early work was in complexity theory. He introduced the class #P and
showed how it could be used to classify many basic algebraic and
combinatorial counting problems according to their computational
difficulty. He has also a longstanding interest in the theoretical basis of
artificial intelligence.
In 1983 he introduced the PAC or "probably approximately correct" model of
learning, which was instrumental in giving rise to the field of
computational learning theory. More recently, he proposed this as a
foundation for a broader computational study of intelligence. His 1994
book, Circuits of the Mind, formulates such a study in a framework
suggested by cortical neurons.
Valiant was educated at King's College, Cambridge; Imperial College,
London; and Warwick University, where he received his Ph.D. in computer
science in 1974. He has been the Gordon McKay Professor of Computer Science
and Applied Mathematics at Harvard University's Division of Engineering and
Applied Sciences since 1982. Before coming to Harvard, he taught at
Carnegie-Mellon University, Leeds University, and the University of
Edinburgh.
Valiant is an active member of the high-performance computing community. He
is a regularly invited lecturer at conferences an symposia, distinguished
lecture series, and other events. He serve or has served on numerous
editorial boards and program committees including the SIAM Journal on
Computing, Machine Learning Computational Complexity, Neural Computation,
Neural Networks, the International Journal of Foundations of Computer
Science, the Symposium on Theory of Computing (STOC), the Conference on
Computational Learning Theory (COLT), EuroColt, the Symposium on Parallel
Algorithms & Architectures (SPAA), and others.
In addition to writing his 1994 book, Valiant is the author or co-author of
more than 80 articles and papers. He received the Nevanlinna Prize at the
International Congress of Mathematicians in 1986 and the Knuth Award in
1997. He is a Fellow of the Royal Society and the American Association for
Artificial Intelligence.
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