Data distribution and task scheduling for distributed computing of all-to-all comparison problems


Autoria(s): Zhang, Yi-Fan
Data(s)

2016

Resumo

This research studied distributed computing of all-to-all comparison problems with big data sets. The thesis formalised the problem, and developed a high-performance and scalable computing framework with a programming model, data distribution strategies and task scheduling policies to solve the problem. The study considered storage usage, data locality and load balancing for performance improvement in solving the problem. The research outcomes can be applied in bioinformatics, biometrics and data mining and other domains in which all-to-all comparisons are a typical computing pattern.

Formato

application/pdf

Identificador

http://eprints.qut.edu.au/92604/

Publicador

Queensland University of Technology

Relação

http://eprints.qut.edu.au/92604/1/Yi-fan_Zhang_Thesis.pdf

Zhang, Yi-Fan (2016) Data distribution and task scheduling for distributed computing of all-to-all comparison problems. PhD thesis, Queensland University of Technology.

Fonte

Science & Engineering Faculty

Palavras-Chave #big data #distributed system #data storage #task scheduling #computing framework #programming model
Tipo

Thesis