Resource aware load distribution strategies for scheduling divisible loads on large-scale data intensive computational grid systems

Ph.DDOCTOR OF PHILOSOPH

Resource unaware load distribution strategies for processing divisible loads in networked computing environments

Ph.DDOCTOR OF PHILOSOPH

Design and analysis of load balancing/scheduling strategies on distributed computer networks using virtual routing approach

Ph.DDOCTOR OF PHILOSOPH

Divisible load scheduling of image processing applications on the heterogeneous star and tree networks using a new genetic algorithm

The divisible load scheduling of image processing applications on the heterogeneous star and multi-level tree networks is addressed in this paper. In our platforms, processors and network links have different speeds. In addition, computation and communication overheads are considered. A new genetic algorithm for minimizing the processing time of low-level image applications using divisible load theory is introduced. The closed-form solution for the processing time, the image fractions that should be allocated to each processor, the optimum number of participating processors, and the optimal sequence for load distribution are derived. The new concept of equivalent processor in tree network is introduced and the effect of different image and kernel sizes on processing time and speed up are investigated. Finally, to indicate the efficiency of our algorithm, several numerical experiments are presented

Design, analysis and application of divisible load scheduling strategies in linear daisy chain networks with system constraints

Ph.DDOCTOR OF PHILOSOPH

Ishu bunsan shisutemu ni okeru kabun tasuku no sukejulingu

制度:新 ; 報告番号:甲2691号 ; 学位の種類:博士(国際情報通信学) ; 授与年月日:2008/7/30 ; 早大学位記番号:新486

Parallel and Distributed Computing

The 14 chapters presented in this book cover a wide variety of representative works ranging from hardware design to application development. Particularly, the topics that are addressed are programmable and reconfigurable devices and systems, dependability of GPUs (General Purpose Units), network topologies, cache coherence protocols, resource allocation, scheduling algorithms, peertopeer networks, largescale network simulation, and parallel routines and algorithms. In this way, the articles included in this book constitute an excellent reference for engineers and researchers who have particular interests in each of these topics in parallel and distributed computing

Load Scheduling for Bioinformatics Applications in Large Scale Networks

A load scheduling strategy with near-optimal processing time is designed to explore the computational characteristics of DNA sequence alignment algorithms, specifically, the Needleman-Wunsch Algorithm. Following the divisible load scheduling theory, we design an efficient load scheduling strategy to manage such bioinformatics applications in a large-scale network so that the overall processing time of the sequencing tasks is minimized. The row-wise and column-wise partitioning of the workload is adopted in the scheduling strategy. In this study, the load distribution depends on the length of the sequence and number of processors in the network and, the total processing time is also affected by communication link speed. We considered several cases in our study by varying the sequences, communication and computation speeds, and number of processors. Through simulation and numerical analysis, this study demonstrates that for a constant sequence length as the numbers of processors increase in the network the processing time for the job decreases and minimum overall processing time is achieved.Computer Science Departmen

Scheduling for Large Scale Distributed Computing Systems: Approaches and Performance Evaluation Issues

Although our everyday life and society now depends heavily oncommunication infrastructures and computation infrastructures,scientists and engineers have always been among the main consumers ofcomputing power. This document provides a coherent overview of theresearch I have conducted in the last 15 years and which targets themanagement and performance evaluation of large scale distributedcomputing infrastructures such as clusters, grids, desktop grids,volunteer computing platforms, ... when used for scientific computing.In the first part of this document, I present how I have addressedscheduling problems arising on distributed platforms (like computinggrids) with a particular emphasis on heterogeneity and multi-userissues, hence in connection with game theory. Most of these problemsare relaxed from a classical combinatorial optimization formulationinto a continuous form, which allows to easily account for keyplatform characteristics such as heterogeneity or complex topologywhile providing efficient practical and distributed solutions.The second part presents my main contributions to the SimGrid project,which is a simulation toolkit for building simulators of distributedapplications (originally designed for scheduling algorithm evaluationpurposes). It comprises a unified presentation of how the questions ofvalidation and scalability have been addressed in SimGrid as well asthoughts on specific challenges related to methodological aspects andto the application of SimGrid to the HPC context