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Bill Dally

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Bill Dally
Alma materVirginia Tech
Stanford University
Caltech
Scientific career
Doctoral advisorCharles Seitz[1]

William James Dally is an American computer scientist and educator.

Life

Dally received the B.S. degree in electrical engineering from Virginia Tech. While working for Bell Telephone Laboratories he contributed to the design of the Bellmac 32, an early 32-bit microprocessor, and earned an M.S. degree in electrical engineering from Stanford University in 1981. He then went to the California Institute of Technology (Caltech), graduating with a Ph.D. degree in computer science in 1986. At Caltech he designed the MOSSIM simulation engine and an integrated circuit for routing. While at Caltech, he was part of the founding group of Stac Electronics in 1983.[2]

From 1986 to 1997 he taught at MIT where he and his group built the J–Machine and the M–Machine,[3] parallel machines emphasizing low overhead synchronization and communication. During his MIT times he claims to have collaborated on developing design of Cray T3D and Cray T3E supercomputers. He became the Willard R. and Inez Kerr Bell Professor in the Stanford University School of Engineering and chairman of the computer science department at Stanford.

He developed a number of techniques used in modern interconnection networks including routing-based deadlock avoidance, wormhole routing, link-level retry, virtual channels, global adaptive routing, and high-radix routers. He has developed efficient mechanisms for communication, synchronization, and naming in parallel computers including message-driven computing and fast capability-based addressing. He has developed a number of stream processors starting in 1995 including Imagine, for graphics, signal, and Image processing, and Merrimac, for scientific computing.

Dally was elected a Fellow of the Association for Computing Machinery in 2002, and a Fellow of the IEEE, also in 2002. In 2003 he became a consultant for NVIDIA for the first time and helped to develop GeForce 8800 GPUs series.[4] He received the ACM/SIGARCH Maurice Wilkes Award in 2000, the Seymour Cray Computer Science and Engineering Award in 2004, and the IEEE Computer Society Charles Babbage Award in 2006. In 2007 he was elected to the American Academy of Arts and Sciences, and in 2009 the National Academy of Engineering. He received the 2010 ACM/IEEE Eckert–Mauchly Award for "outstanding contributions to the architecture of interconnection networks and parallel computers."[5]

He has published over 200 papers as well as the textbooks "Digital Systems Engineering" with John Poulton, and "Principles and Practices of Interconnection Networks" with Brian Towles. He was inventor or co-inventor on over 70 granted patents.

Dally's corporate involvements include various collaborations at Cray Research since 1989. He did Internet router work at Avici Systems starting in 1997, was chief technical officer at Velio Communications from 1999 until its 2003 acquisition by LSI Logic, founder and chairman of Stream Processors, Inc until it folded.[2] In January 2009 he was appointed chief scientist of Nvidia.[6] He worked full-time at Nvidia, while supervising about 12 of his graduate students at Stanford.[7]

An author quoted him saying: "Locality is efficiency, Efficiency is power, Power is performance, Performance is king".[8]

Books

  • Dally and Poulton, Digital Systems Engineering, 1998, ISBN 0-521-59292-5.
  • Dally and Towles, Principles and Practices of Interconnection Networks, 2004, ISBN 0-12-200751-4.
  • Dally and Harting, Digital Design: A Systems Approach, 2012, ISBN 978-0-521-19950-6.

References

  1. ^ Bill Dally at the Mathematics Genealogy Project
  2. ^ a b William Dally (November 4, 2011). "From Science to Technology, From Research to Product" (PDF). Slides from Norway Science Week. Stanford Engineering. Retrieved March 7, 2017.
  3. ^ "Practical AI #15: Artificial intelligence at NVIDIA with Chief Scientist Bill Dally". Changelog. Retrieved 2019-04-25. I was on the faculty at MIT for 11 years, where I built a research group that built a number of pioneering supercomputers,
  4. ^ "Practical AI #15: Artificial intelligence at NVIDIA with Chief Scientist Bill Dally". Changelog. Retrieved 2019-04-25.
  5. ^ "ACM Award Citation". Association for Computing Machinery. Archived from the original on 2 April 2012. Retrieved 25 October 2010.
  6. ^ "Nvidia Names Stanford's Bill Dally Chief Scientist, VP Of Research". Press release. January 28, 2009. Archived from the original on February 3, 2009. Retrieved March 7, 2017.
  7. ^ Ashlee Vance (April 8, 2009). "Hello, Dally: Nvidia Scientist Breaks Silence, Criticizes Intel". The New York Times. Retrieved March 10, 2017.
  8. ^ Johnson, Matt (2011). An Analysis of Linux Scalability to Many Cores. p. 4. Locality is efficiency, Efficiency is power, Power is performance, Performance is king
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