#### Filter Results:

#### Publication Year

2011

2016

#### Publication Type

#### Co-author

#### Publication Venue

#### Key Phrases

Learn More

- Amanda Bienz, Kossi Fokle, Zachary Keller, Ed Zulkoski, Scott Thede
- 2011

The focus of this paper is to implement a genetic algorithm using parallel programming. Genetic algorithms are well-suited to " parallelization, " since they model many individuals. Three implementations of a genetic algorithm were created for this paper-a standard sequential programming algorithm , a parallel algorithm using a master process to control the… (More)

- Amanda Bienz, Robert D. Falgout, William Gropp, Luke N. Olson, Jacob B. Schroder
- SIAM J. Scientific Computing
- 2016

Algebraic multigrid (AMG) is an O(n) solution process for many large sparse linear systems. A hierarchy of progressively coarser grids is constructed that utilize complementary relaxation and interpolation operators. High-energy error is reduced by relaxation, while low-energy error is mapped to coarse-grids and reduced there. However, large parallel… (More)

- Amanda Bienz, William Gropp, Luke N. Olson
- ArXiv
- 2016

This paper introduces a method to reduce communication that is injected into the network during a sparse matrix-vector multiply by reorganizing messages on each node. This results in a reduction of the inter-node communication, replaced by less-costly intra-node communication, which reduces both the number and size of messages that are injected into the… (More)

- Amanda Bienz, Luke Olson
- 2015

Algebraic multigrid (AMG) is an iterative method for solving sparse linear systems of equations (Aˆx = b), such as discretized partial differential equations arising in various fields of science and engineering. AMG is considered an optimal solver, requiring only O(n) operations to solve a system of n unknowns. Standard computers contain neither the memory… (More)

- ‹
- 1
- ›