Erin Carson
I am a PhD candidate in Computer Science at U.C. Berkeley, advised by James Demmel and Armando Fox.
I am affiliated with the Berkeley Benchmarking and Optimization Group (BeBOp) within the ASPIRE Lab
I am also a student in the Designated Emphasis in Computational Science and Engineering Program.
My research sits at the intersection of high performance computing, parallel algorithms, scientific computing, and numerical linear algebra.
Office

586E Soda Hall
Computer Science Division
University of California at Berkeley
Berkeley, CA 947201776
Email: ecc2z@cs.berkeley.edu
Publications
My Google Scholar profile

 G. Ballard, E. Carson, J. Demmel, M. Hoemmen, N. Knight, and O.Schwartz, Communication lower bounds and optimal algorithms for numerical linear algebra, Acta Numerica, 23 (2014), pp. 1155.
 N. Knight, E. Carson and J. Demmel. Exploiting data sparsity in parallel matrix powers computations, in Parallel Processing and Applied Mathematics, R. Wyrzykowski, J. Dongarra, K. Karczewski, and J. Waniewski, eds., Lecture Notes in Computer Science, Springer Berlin Heidelberg, 2014, pp.1525.
 E. Carson and J. Demmel. A residual replacement strategy for improving the maximum attainable accuracy
of sstep Krylov subspace methods. SIAM J. Matrix Anal. Appl. 35(1), 2014.
 E. Carson, N. Knight, and J. Demmel. Avoiding communication in twosided Krylov subspace methods.
SIAM J. Sci. Comp. 35 (5), 2013.
Conference Papers

 E. Solomonik, E. Carson, N. Knight, and J. Demmel. Tradeoffs between synchronization, communication, and work in parallel linear algebra computations. Proceedings of the 26th ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), June 2014 (to appear).

S. Williams, E. Carson, M. Lijewski, N. Knight, A. Almgren, B. Van Straalen, and J. Demmel. sstep Krylov Subspace Methods as Bottom Solvers for Geometric
Multigrid. Proceedings of the 28th IEEE International Parallel and Distributed
Processing Symposium (to appear).
Technical Reports

 E. Carson and J. Demmel. Error analysis of the sstep Lanczos method in finite precision. Technical Report UCB/EECS201455, EECS Dept., U.C. Berkeley, May 2014. [pdf]
 E. Carson and J. Demmel. Analysis of the finite precision sstep biconjugate gradient method. Technical Report UCB/EECS201418, EECS Dept., U.C. Berkeley, Mar 2014. [pdf]
 E. Solomonik, E. Carson, N. Knight, and J. Demmel. Tradeoffs between synchronization, communication, and work in parallel linear algebra computations. Technical Report UCB/EECS20148, EECS Dept., U.C. Berkeley, Jan 2014. [pdf]
 E. Carson, N. Knight, and J. Demmel. Avoiding communication in twosided Krylov subspace methods. Technical Report UCB/EECS201193, EECS Dept., U.C. Berkeley, Aug 2011. [pdf]
 E. Carson and J. Demmel. A residual replacement strategy for improving the maximum attainable accuracy
of sstep Krylov subspace methods. Technical Report UCB/EECS2012197, EECS Dept.,
U.C. Berkeley, Sept. 2012. [pdf]
Talks and Extended Abstracts

 S. Williams, E. Carson, N. Knight, M. Lijewski, A. Almgren, B. van Straalen and J. Demmel. Avoiding synchronization in geometric multigrid. SIAM Parallel Processing for Scientific Computing, Feb 2014. [abstract]

E. Carson. CommunicationAvoiding Krylov Subspace Methods in Finite Precision, Bay Area Scientific Computing Day, Dec 2013. [abstract]
 E. Carson and J. Demmel. Efficient deflation for communication avoiding Krylov methods (extended abstract).
In Proc. Numerical Analysis and Scientific Computation with Applications, Jun 2013.
 N. Knight, E. Carson, and J. Demmel. Avoiding communication with hierarchical matrices (abstract). In
Proc. SIAM Conference on Applied Linear Algebra, Jun 2012.
 E. Carson, N. Knight, and J. Demmel. Improving the stability of communicationavoiding Krylov subspace
methods (abstract). In Proc. SIAM Conference on Applied Linear Algebra, Jun 2012.
 E. Carson, N. Knight, and J. Demmel. Exploiting lowrank structure in computing matrix powers with
applications to preconditioning (abstract). In Proc. SIAM Conference on Parallel Processing for Scientific
Computing, Feb 2012. [ pdf  pptx ]
 E. Carson and J. Demmel. A residual replacement strategy for improving the maximum attainable accuracy
of communicationavoiding Krylov subspace methods (extended abstract). In Proc. 9th International
Workshop on Accurate Solution of Eigenvalue Problems, pages 19–21, Jun 2012.
 E. Carson, N. Knight, and J. Demmel. Hypergraph partitioning for computing matrix powers (extended
abstract). In Proc. Fifth SIAM Workshop on Comb. Sci. Comput., pages 31–33, May 2011. [pdf]
Past Projects
 G. Ballard, E. Carson, and N. Knight, Algorithmicbased fault tolerance for matrix multiplication on Amazon EC2, (2009).
[pdf]
 J. Carnahan, S. Policastro, E. Carson, P. Reynolds Jr., and R. Kelly, Using flexible points in a developing simulation of selective dissolution in alloys, in Proceedings of the 39th conference on Winter simulation, IEEE Press, 2007, pp. 891899.
[ACMDL]
Teaching

U.C. Berkeley
 Math 54: Linear Algebra and Differential Equations, Spring 2011. Instructor: Constantin Teleman. Topics: Basic linear algebra; matrix arithmetic and determinants. Vector spaces; inner product as spaces. Eigenvalues and eigenvectors; linear transformations. Homogeneous ordinary differential equations; firstorder differential equations with constant coefficients. Fourier series and partial differential equations.
University of Virginia
 CS 101: Introduction to CS, Fall 2007. Instructor: Kevin Sullivan and Greg Humphreys.
 CS 101x: Introduction to CS (for nonengineers), Fall 2007. Instructor: Jim Cohoon.
 CS 202: Discrete Mathematics, Spring & Fall 2008. Instructors: Paul Reynolds and John Knight.
Activities