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Computer Science @ Rochester
Monday, November 05, 2012
10:45 AM
Computer Studies Bldg. Room 209
Sonia Lopez Alarcon
RIT
Towards Heterogeneous Hardware Acceleration of Patient-Specific Modeling Applications
Patient-specific modeling, as an emerging area in the study of biomedical sciences, has started to gain increasing attention because it offers us a potential ability to \emph{virtually} reproduce the subject-specific pathophysiological conditions of the living organisms, an ability could potentially transform the current practice of medicine. However, these patient-specific modeling applications are highly compute intensive and take unreasonable amounts of time that make their inclusion in the medical environment unfeasible. Computationally speaking, data-assimilation modeling applications perform linear algebra computations over large data sets in the shape of matrices, source of high parallelism. They also encompass different computation phases that communicate with each other through data transfers. We will present a heterogeneous (CPU, GPU, and FPGA) hardware solution to this type of applications that can dramatically reduce the execution time, to the point where these applications become practical in a medical setting.

BIO: Professor Sonia Lopez Alarcon was born in Madrid, Spain. She received a Bachelor of Physic degree in Physic and Master degree in Electronic in 2002 from the University Complutense of Madrid. In her latest college years she worked at Lucent Technologies, Madrid, and Fundetel at Polytechnic University of Madrid, were she became familiar with the design and fabrication process of integrated circuits. In 2003 she started working toward a PhD degree in Computer Engineering at the University Complutense of Madrid, working on cache hierarchy in simultaneous multithreaded architectures. In 2004 she started her cooperative research with Professor David H. Albonesi, at the University of Rochester and, later on, at Cornell University. She graduated in 2009, and she joined the Department of Computer Engineering at the Rochester Institute of Technology in the fall of 2009. Her current research interest is on cache optimization, GPU architecture, and heterogeneous hardware solutions.

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