Performance Analysis and Grid Computing : Selected Articles from the Workshop on Performance Analysis and Distributed Computing August 19-23, 2002, Dagstuhl, Germany

Vladimir Getov

ISBN 10: 1402076932 / ISBN 13: 9781402076930

Published by Springer US, Springer New York, 2003

About this Item

Druck auf Anfrage Neuware - Printed after ordering - Past and current research in computer performance analysis has focused primarily on dedicated parallel machines. However, future applications in the area of high-performance computing will not only use individual parallel systems but a large set of networked resources. This scenario of computational and data Grids is attracting a great deal of attention from both computer and computational scientists. In addition to the inherent complexity of parallel machines, the sharing and transparency of the available resources introduces new challenges on performance analysis, techniques, and systems. In order to meet those challenges, a multi-disciplinary approach to the multi-faceted problems of performance is required. New degrees of freedom will come into play with a direct impact on the performance of Grid computing, including wide-area network performance, quality-of-service (QoS), heterogeneity, and middleware systems, to mention only a few.

Seller Inventory # 9781402076930

Bibliographic Details

• Title: Performance Analysis and Grid Computing : Selected Articles from the Workshop on Performance Analysis and Distributed Computing August 19-23, 2002, Dagstuhl, Germany
• Publisher: Springer US, Springer New York
• Publication Date: 2003
• Language: English
• ISBN 10: 1402076932
• ISBN 13: 9781402076930
• Binding: Buch
• Condition: Neu
• Dimensions: 241W x 160H x 23D millimeters 241 millimeters width by 160 millimeters height by 23 millimeters depth
• Weight: 627 grams

About this title

Synopsis

Past and current research in computer performance analysis has focused primarily on dedicated parallel machines. However, future applications in the area of high-performance computing will not only use individual parallel systems but a large set of networked resources. This scenario of computational and data Grids is attracting a great deal of attention from both computer and computational scientists. In addition to the inherent complexity of parallel machines, the sharing and transparency of the available resources introduces new challenges on performance analysis, techniques, and systems. In order to meet those challenges, a multi-disciplinary approach to the multi-faceted problems of performance is required. New degrees of freedom will come into play with a direct impact on the performance of Grid computing, including wide-area network performance, quality-of-service (QoS), heterogeneity, and middleware systems, to mention only a few.