# KASIA SWIRYDOWICZ

Currently a Post-doc at the National Renewable Energy Lab

Formerly a postdoc researcher at VT.

Scientific interests:

1. Krylov subspace methods and Krylov subspace recycling; efficiency and effectiveness of Krylov subspace solvers and preconditioners; applications of Krylov subspace methods to engineering problems, such as CFD codes, topology optimization.

2. Scientific computing; GPU programming and code optimization.

CV

## PUBLISHED WORK

### GPU ACCELERATED SPECTRAL ELEMENT OPERATORS FOR ELLIPTIC PROBLEMS

October, 2017

Authors: Kasia Swirydowicz, Noel Chalmers, Ali Karakus, and Tim Warburton

Submitted to International Journal of HPC Applications.

Abstract. This paper is devoted to GPU kernel optimization and performance analysis of three tensor- product operators arising in finite element methods. We provide a mathematical background to these operations and implementation details. Achieving close-to-the-peak performance for these operators requires extensive optimization because of the operators’ properties: low arithmetic intensity, tiered structure, and the need to store intermediate results inside the kernel. We give a guided overview of optimization strategies and we present a performance model that allows us to compare the efficacy of these optimizations against an empirically calibrated roofline.

2016

Authors: William C. Tyson, Katarzyna (Kasia) Świrydowicz, Joseph M. Derlaga, Christopher J. Roy, Eric de Sturler

Conference paper for 46th AIAA Fluid Dynamics Conference, AIAA AVIATION Forum, (AIAA 2016-3809)

### COUPLED CELL NETWORKS: BOOLEAN PERSPECTIVE

2017

Author: Kasia Swirydowicz

Published in BIOMATH 6 (2017)

Abstract: During the 1980s and early 1990s, Martin Golubitsky and Ian Stewart  formulated and developed a theory of "coupled cell networks" (CCNs). Their research was primarily focused onquadrupeds' gaits and they applied the framework of differential equations. Golubitsky and Stewart were particularly interested in change of synchrony between $4$ legs of an animal. For example what happens when the animal speeds up from walk to gallop.

The most important concept of their theory is a {\it cell}. The cell captures the dynamics of one unit and a dynamical system consists of many identical (governed by the same principles) cells influencing (coupling to) each other. Models based on identical cooperating units are fairly common in many areas, especially in biology, ecology and sociology.

The goal of investigation in Coupled Cell Networks theory  is understanding the dependencies and interplay between dynamics of an individual cell, graph of connections between cells, and the nature of couplings. \vspace*{0.2em}
In this paper, I redefine Coupled Cell Networks using framework of Boolean functions. This moves the entire theory to a new setting. Some phenomena proved to be very similar as for continuous networks and some are completely different. Also, for discrete networks we ask questions differently and study different phenomena. The paper presents two examples: networks that bring 2-cell bidirectional ring as a quotient and networks that bring 3-cell bidirectional ring as a quotient.

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