Creativity in Load-Balance Schemes for Multi/Many-Core Heterogeneous Graph Computing: Emerging Research and Opportunities

Creativity in Load-Balance Schemes for Multi/Many-Core Heterogeneous Graph Computing: Emerging Research and Opportunities

Alberto Garcia-Robledo (Center for Research and Advanced Studies of the National Polytechnic Institute (Cinvestav-Tamaulipas), Mexico), Arturo Diaz-Perez (Center for Research and Advanced Studies of the National Polytechnic Institute (Cinvestav-Tamaulipas), Mexico) and Guillermo Morales-Luna (Center for Research and Advanced Studies of the National Polytechnic Institute (Cinvestav-IPN), Mexico)
Release Date: January, 2018|Copyright: © 2018 |Pages: 217
ISBN13: 9781522537991|ISBN10: 1522537996|EISBN13: 9781522538004|DOI: 10.4018/978-1-5225-3799-1

Description

Recent years have witnessed the rise of analysis of real-world massive and complex phenomena in graphs; to efficiently solve these large-scale graph problems, it is necessary to exploit high performance computing (HPC), which accelerates the innovation process for discovery and invention of new products and procedures in network science.

Creativity in Load-Balance Schemes for Multi/Many-Core Heterogeneous Graph Computing: Emerging Research and Opportunities is a critical scholarly resource that examines trends, challenges, and collaborative processes in emerging fields within complex network analysis. Featuring coverage on a broad range of topics such as high-performance computing, big data, network science, and accelerated network traversal, this book is geared towards data analysts, researchers, students in information communication technology (ICT), program developers, and academics.

Topics Covered

The many academic areas covered in this publication include, but are not limited to:

  • Accelerated Network Traversal
  • Big Data
  • Bioinformatics
  • Data Mining
  • High Performance Computing
  • Network Science
  • Social Network Analysis

Table of Contents and List of Contributors

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Author(s)/Editor(s) Biography

Alberto Garcia-Robledo has a Ph.D. in Computer Science from the Center for Research and Advanced Studies, and Erdos Number 3. Alberto Garcia-Robledo has attended courses, participated in projects, or performed presentations in renowned Mexican and international academic institutions, such as the Monterrey Institute of Technology and Higher Education, the National Laboratory of Advanced Informatics, the University of La Laguna and the Università della Svizzera Italiana. From 2013 to 2014, Alberto Garcia-Robledo was appointed technical lead of a financial data analysis research project that involved government, academia and industry at the Geospatial Data Center of the Massachusetts Institute of Technology.
Arturo Diaz-Perez has a Ph.D. in Electrical Engineering from Cinvestav. Since 2006, he is the head of the Cinvestav’s IT Lab and his work has focused on promoting information technology developments for the State of Tamaulipas in a joint venture initiative between Cinvestav and Government of Tamaulipas. IT Lab performs projects related to scientific research and technological development in IT field. Prof. Diaz-Perez is member of the Computing and Telecommunications Board at Cinvestav. Arturo Diaz-Perez has published one book in the field of reconfigurable computing for cryptographic algorithms, 16 papers in technical refereed journals, and more than 40 papers in technical conferences.
Guillermo Morales-Luna is a Researcher at Cinvestav-IPN since 1985. He received a Ph.D in Mathematics from the Polish Academy of Sciences, Poland. From 1989 to 1992 he chaired the Cinvestav Computer Science Section. He has refereed texts and books edited by the Sociedad Matemática Mexicana, the Universidad Auto´noma Metropolitana and IPN. He has received several grants for research and technology projects from Mexican CONACyT, UNESCO, PEMEX and the Mexican Institute of Telecommunications. His research interest areas include Logic (model theory, Peano arithmetic, proof theory) and mathematical foundations of Computer Science (recursive functions, computational complexity and algorithms).