DocumentCode :
495421
Title :
Implementation and Quantitative Analysis of a Shared-Memory Based Parallel Server Architecture for Aerospace Information Exchange Applications
Author :
Alegre, A. ; Beltran, S. ; Estrada, J. ; Milshteyn, A. ; Liu, C. ; Boussalis, H.
Author_Institution :
Dept. of Electr. & Comput. Eng., California State Univ., Los Angeles, Los Angeles, CA, USA
Volume :
3
fYear :
2009
fDate :
March 31 2009-April 2 2009
Firstpage :
359
Lastpage :
363
Abstract :
This paper focuses on the implementation and quantitative analysis of a high-performance parallel processing aerospace information server. An innovative model of software architecture is provided to effectively utilize the computational power of a parallel server platform for efficient, on-demand aerospace information exchange through the Internet. This is a representative application for servers whose features are common to the classical client-server model. The server architecture supports thread, core, and/or processor-level parallel processing for high performance computing. Memory devices (i.e. cache memory, main memory, and secondary memory) are either shared or distributed among the computational units. Such features facilitate our study of identifying and overcoming the architectural bottlenecks of current commercial server configurations.
Keywords :
aerospace computing; client-server systems; parallel processing; shared memory systems; aerospace information exchange application; aerospace information server; client-server model; computational power; high performance computing; parallel server platform; processor-level parallel processing; quantitative analysis; shared-memory based parallel server architecture; software architecture; Application software; Computer architecture; Concurrent computing; High performance computing; Information analysis; Internet; Parallel processing; Software architecture; Web server; Yarn; Aerospace; bottleneck; hashing; high performance server; image transmission; parallel processing; quantitative analysis; runtime; tuple space; wavelet compression;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Information Engineering, 2009 WRI World Congress on
Conference_Location :
Los Angeles, CA
Print_ISBN :
978-0-7695-3507-4
Type :
conf
DOI :
10.1109/CSIE.2009.509
Filename :
5170863
Link To Document :
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