Parallel Experiences in Solving Complex Problems

Speaker:  Enrique Alba – Malaga, Spain
Topic(s):  Artificial Intelligence, Machine Learning, Computer Vision, Natural language processing


This lecture introduces the basic concepts of two fields of research: parallelism and metaheuristics. We will revise the main concepts, tools, metrics, open issues, and application domains related to parallel models of search, optimization, and learning techniques. The very special kind of algorithms searching in a decentralized manner and later parallelized will be shown to solve complex problems at unseen levels of efficiency and efficacy. Facts, methodology, and general open issues will be presented in this talk. The syllabus of this lecture is as follows: an introduction to parallel algorithms, facts in modern parallel optimization, models vs. implementation, metrics, heterogeneity, experimental assessment, software, many core computing, grid/cloud, GPUs, applications, example case studies.

About this Lecture

Number of Slides:  29
Duration:  50 - 60 minutes
Languages Available:  English
Last Updated: 

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