Distinguished ACM Speaker:
Based in CA, USA
David H. Bailey is a leading figure in high-performance scientific computing and computational mathematics. Although officially retired from the Lawrence Berkeley National Laboratory, he continues as an active researcher. He is also a Research Fellow at the University of California, Davis, Department of Computer Science.
Bailey has been active in the Association for Computing Machinery for many years. He has chaired the ACM Gordon Bell Prize Committee on numerous occasions (most recently in 2013), served on the Technical Papers Committee for the Supercomputing Conferences, and served on the Steering Committee of the Supercomputing Conferences.
Bailey’s research in high-performance computing includes studies in numerical algorithms and supercomputer performance. He authored a paper on a technique for performing the fast Fourier transform on parallel and hierarchical memory computers that is the now basis of almost all FFT implementations on modern computer systems. His paper "The NAS Parallel Benchmarks" is widely cited in performance studies of scientific computer systems. He has received both the IEEE Computer Society’s Sidney Fernbach Award and the ACM Gordon Bell Prize.
Bailey is also a leading figure in the field of computational and experimental mathematics. He is an author of two high-precision computation software packages that are widely used in the field. His best-known paper in this area (co-authored with Peter Borwein and Simon Plouffe) describes a new formula for pi that permits arbitrary digit calculation, which formula was discovered using Bailey's computer implementation of the PSLQ algorithm. In two more recent papers, Bailey, with his colleague Richard Crandall, demonstrated a connection between these formulas and a fundamental question about digit randomness. Bailey has received the Chauvenet Prize and the Merten Hesse Prize from the Mathematical Association of America.
Bailey and his colleague Jonathan Borwein jointly operate a website (http://www.experimentalmath.info) devoted to experimental mathematics, and another (http://www.financial-math.org) to financial mathematics. They also write articles on mathematics, computing, science and society for the Math Drudge blog (http://www.experimentalmath.info/blog), the Huffington Post (http://www.huffingtonpost.com) and the Conversation (http://www.theconversation.com.au).
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- Conquering Numerical Error in Large-Scale Scientific Computing:
The proliferation of extremely large-scale, highly parallel computation (in some cases involving one million or more processors) has greatly exacerbated issues of numerical error and numerical reproducibility. In some cases, developers of appl...
- High-Precision Computation: Applications and Challenges:
High-precision floating-point arithmetic software, ranging from "double-double" or "quad" precision to arbitrarily high precision (hundreds or thousands of digits), has been available for years. Such facilities are standard...
- Numerical Reproducibility in Exascale Computing:
The rapidly growing scale of modern scientific computing is exacerbating issues of numerical reproducibility. A computation running on 4096 CPUs, for instance, may give significantly different numerical answers than the same program runn...
- Twelve ways to fool the masses: Fast forward to 2013:
In 1991, the present author wrote a humorous essay "Twelve Ways to Fool the Masses," which outlined a number of highly questionable "techniques" often used at the time by researchers in the high performance computing field ...
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