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<title>Friday seminar talk announcement: GPU-accelerated Meta-heuristics for
Optimization</title>
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<p align=center style='text-align:center'><span style='font-size:24.0pt'>GPU-accelerated
Meta-heuristics for Optimization </span><o:p></o:p></p>
<p align=center style='text-align:center'><span style='font-size:18.0pt'>Dr.
Weihang Zhu </span><o:p></o:p></p>
<p align=center style='text-align:center'><span style='font-size:13.5pt'>Department
of Industrial Engineering</span><o:p></o:p></p>
<p align=center style='text-align:center'><span style='font-size:13.5pt'>Lamar
University</span><o:p></o:p></p>
<p align=center style='text-align:center'><b><span style='font-size:13.5pt'>When</span></b><span
style='font-size:13.5pt'>: 10 -11am, Friday, October 8, 2010</span><o:p></o:p></p>
<p align=center style='text-align:center'><b><span style='font-size:13.5pt'>Where</span></b><span
style='font-size:13.5pt'>: Room 102D, Engr. Bldg 1</span><o:p></o:p></p>
<p><b>Abstract:</b><o:p></o:p></p>
<p><span style='font-size:18.0pt'>This seminar will present the
interdisciplinary research work on GPU-accelerated meta-heuristics for
optimization. A framework of massively parallel evolutionary algorithms with
graphics hardware acceleration was established for global optimization and
multi-objective optimization problems. GPU, the common graphics hardware found
in modern personal computers (PC), can be used for data-parallel computing in a
desktop setting. In this research, multiple population-based evolutionary
algorithms were adapted to the data-parallel GPU computing platform featuring
‘Single Instruction – Multiple Thread’ (SIMT) to achieve orders of magnitude
speedup with affordable hardware. Applications of the framework on classical
problems such as Quadratic Assignment Problems (QAP) and new fields such as
protein structure modeling (Computational Biology) will be discussed. The
research result demonstrated a promising direction for high speed optimization
with desktop parallel computing in a PC.</span><o:p></o:p></p>
<p><b>Short Bio:</b><o:p></o:p></p>
<p>Weihang Zhu (Ph.D., North Carolina State University, 2003) is an assistant
professor of Industrial Engineering, directing Computational Optimization Lab,
and Manufacturing Lab at Lamar University, Beaumont, Texas. He has more than 15
years of engineering research experience and has participated in the projects
supported by NSF, NIST and DoD. He has about 50 technical publications on GPU
computing, metaheuristics, design optimization, computational biology, CAD/CAM,
medical simulation and haptics.<o:p></o:p></p>
<p><span style='font-family:"Calibri","sans-serif"'>Gino Lim</span><o:p></o:p></p>
<p><span style='font-size:10.0pt;font-family:"Calibri","sans-serif"'>Hari and
Anjali Agrawal Faculty Fellow and Associate Prof.</span><o:p></o:p></p>
<p><span style='font-size:10.0pt;font-family:"Calibri","sans-serif"'>Director
of Science & Technology, SWTC Center</span><o:p></o:p></p>
<p><span style='font-size:10.0pt;font-family:"Calibri","sans-serif"'>Department
of Industrial Engineering</span><o:p></o:p></p>
<p><span style='font-size:10.0pt;font-family:"Calibri","sans-serif"'>University
of Houston</span><o:p></o:p></p>
<p><span style='font-size:10.0pt;font-family:"Calibri","sans-serif"'><a
href="http://www.e">http://www.e</a>gr.uh.edu/ie/faculty/?e=lim</span><o:p></o:p></p>
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