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  <div class="vevent h-event"> <h1 class="summary p-name">PSU CS Colloquium: Chaos in Computer Science</h1> <div class='date'><time class="dtstart dt-start" title="2009-10-23T13:00:00" datetime="2009-10-23T13:00:00">Friday, October 23, 2009 from 1</time>–<time class="dtend dt-end" title="2009-10-23T14:00:00" datetime="2009-10-23T14:00:00">2pm</time></div> <div class="location vcard p-location h-card"> <a class="url" href='http://calagator.org/venues/202390760'><span class='fn org p-name'>Portland State University Fourth Avenue Building (FAB)</span></a> <div class="adr p-adr h-adr"> <div class="street-address p-street-address">1900 SW 4th Ave.</div> <span class="locality p-locality">Portland</span> , <span class="region p-region">OR</span> <span class="postal-code p-postal-code">97201</span> <div class="country-name p-country-name">US</div> (<a href='https://maps.google.com/maps?q=1900%20SW%204th%20Ave.,%20Portland%20OR%2097201%20US'>map</a>) </div> </div> <div class="description p-description"> <p>CS conference room, FAB 086-01</p> <p>Abstract: Although it is not necessarily the view taken by those who design them, modern computers are deterministic nonlinear dynamical systems, and it is both interesting and useful to treat them as such. In this talk, I will describe a nonlinear dynamics-based framework for modeling and analyzing computer systems. Using this framework, together with a custom measurement infrastructure, we have found strong indications of low-dimensional dynamics in the performance of a simple program running on a popular Intel microprocessor—including the first experimental evidence of chaotic dynamics in real computer hardware. These dynamics change completely when we run the same program on a different Intel microprocessor, or when we change that program slightly. All of this raises important issues about computer analysis and design. These engineered systems have grown so complex as to defy the analysis tools that are typically used by their designers: tools that assume linearity and stochasticity, and essentially ignore dynamics. The ideas and methods developed by the nonlinear dynamics community are a much better way to study, understand, and (ultimately) design modern computer systems.</p> <p>This is joint work with Amer Diwan and Todd Mytkowicz.</p> <p>Computer Science Department University of Colorado at Boulder Biography: Elizabeth Bradley did her undergraduate and graduate work at MIT, interrupted by a one-year leave of absence to row in the 1988 Olympic Games, and has been with the Department of Computer Science at the University of Colorado at Boulder since January of 1993. Her research interests include nonlinear dynamics, artificial intelligence, and control theory. She is the recipient of a NSF National Young Investigator award, a Packard Fellowship, a Radcliffe Fellowship, and the 1999 student-voted University of Colorado College of Engineering teaching award.</p> <p>Host: Melanie Mitchell</p> </div> <h3>Links</h3> <ul> <li><a class="url u-url" href="http://web.cecs.pdx.edu/~colloq/2009-10/Bradley.html">Website</a></li> </ul> </div>