ACM Paris Kanellakis Theory and Practice Award
University of California, Berkeley United States – 2014

For contributions to algorithms and software for numerical linear algebra used in scientific computing and large-scale data analysis.

Jim Demmel introduced a geometric view of error that could be applied to a broad class of known but unstable eigenvalue (and other) computations to produce methods that worked efficiently and had provably small error. This work served as an important view in the field for others as well for his own work. His theoretical work also identified and analyzed the impact of communication in finding optimal methods in numerical analysis. All the while, Professor Demmel was crucially involved in the implementation of provably reliable methods in LAPACK, the definitive and central code used whenever accuracy and speed is desired. Professor Demmel was deeply involved at various levels ranging from fast and accurate algorithms for the singular value decomposition to floating point issues. Professor Demmel's theoretical work in scalable systems is evident in his extensive involvement in scalable implementations of eigenvalue computations in ScaLAPACK. His joint work on the implementations of matrix factorizations central to solving sparse linear systems is embodied in SuperLU, the thesis work of his PhD student, Xiaoye Li. These libraries have been used in many scientific research projects, including some cover articles in Nature and Science.

Press Release

United States – 1999

For outstanding contributions to scientific computing, parallel processing and software engineering.

James Demmel Receives 2014 The Paris Kanellakis Theory And Practice Award


James Demmel is the recipient of the Paris Kanellakis Theory and Practice Award for his work on numerical linear algebra libraries, including LAPACK (Linear Algebra Package), a standard software library that forms part of the standard mathematical libraries for many vendors. The software and standards Demmel developed enable users to transition their computer programs to new high-performance computers without resorting to basic building blocks. His accomplishments range from creation of algorithms with rigorous mathematical foundations to hands-on development of high-quality, widely available software. Demmel is a professor of Computer Science and of Mathematics at UC Berkeley and an ACM Fellow.


 Press Release