Welcome to the InfoSci Platform
Reference Hub1
Collective Relocation for Associative Distributed Collections of Objects

Collective Relocation for Associative Distributed Collections of Objects

Daisuke Fujishima, Tomio Kamada
Copyright: © 2017 |Volume: 5 |Issue: 2 |Pages: 15
ISSN: 2166-7160|EISSN: 2166-7179|EISBN13: 9781522515548|DOI: 10.4018/IJSI.2017040104
Cite Article Cite Article

MLA

Fujishima, Daisuke, and Tomio Kamada. "Collective Relocation for Associative Distributed Collections of Objects." IJSI vol.5, no.2 2017: pp.55-69. http://doi.org/10.4018/IJSI.2017040104

APA

Fujishima, D. & Kamada, T. (2017). Collective Relocation for Associative Distributed Collections of Objects. International Journal of Software Innovation (IJSI), 5(2), 55-69. http://doi.org/10.4018/IJSI.2017040104

Chicago

Fujishima, Daisuke, and Tomio Kamada. "Collective Relocation for Associative Distributed Collections of Objects," International Journal of Software Innovation (IJSI) 5, no.2: 55-69. http://doi.org/10.4018/IJSI.2017040104

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

The field of parallel computing has experienced an increase in the number of computing nodes, allowing broader applications, including computations that have irregular features. Some parallel programming languages handle object data structures and offer marshaling/unmarshaling mechanisms to transpose them. To manage data elements across computing nodes, some research on distributed collections has been conducted. This study proposes a distributed collection library that can handle multiple collections of object elements and change their distributions while maintaining associativity between their elements. This library is implemented on an object-oriented parallel programming language, X10. The authors assume pairs of associative collections such as vehicles and streets in a traffic simulation. When many vehicles are concentrated on streets assigned to certain computing nodes, some of these streets should be moved to other nodes. The authors' library assists the programmer in easily distributing the associative collections over the computing nodes and collectively relocating elements while maintaining the data sharing relationship among associative elements. The programmer can describe the associativity between objects by using both declarative and procedural methods. They show a preliminary performance evaluation of their library on a Linux cluster and the K computer.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.