Parallel Inductive Logic Programming System for Superlinear Speedup

In this study, we improve our parallel inductive logic programming (ILP) system to enable superlinear speedup. This improvement redesigns several features of our ILP learning system and parallel mechanism. The redesigned ILP learning system searches and gathers all rules that have the same evaluatio...

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Bibliographic Details
Published inInductive Logic Programming Vol. 10759; pp. 112 - 123
Main Authors Nishiyama, Hiroyuki, Ohwada, Hayato
Format Book Chapter
LanguageEnglish
Published Switzerland Springer International Publishing AG 01.01.2018
Springer International Publishing
SeriesLecture Notes in Computer Science
Subjects
Dairy Cattle Data
Nlimit
Parallel ILP
Plimit
Superlinear Speedup
Online AccessGet full text
ISBN9783319780894
3319780891
ISSN0302-9743
1611-3349
DOI10.1007/978-3-319-78090-0_8

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Summary:In this study, we improve our parallel inductive logic programming (ILP) system to enable superlinear speedup. This improvement redesigns several features of our ILP learning system and parallel mechanism. The redesigned ILP learning system searches and gathers all rules that have the same evaluation. The redesigned parallel mechanism adds a communication protocol for sharing the evaluation of the identified rules, thereby realizing superlinear speedup.
ISBN:9783319780894
3319780891
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-319-78090-0_8