Methodology for Performance Evaluation of the Input/Output System on Computer Clusters
ABSTRACT The increase of processing units, speed and computational power, and the complexity of scientific applications that use high performance computing require more efficient Input/Output (I/O) systems. In order to efficiently use the I/O it is necessary to know its performance capacity to determine if it fulfills applications I/O requirements. This paper proposes a methodology to evaluate I/O performance on computer clusters under different I/O configurations. This evaluation is useful to study how different I/O subsystem configurations will affect the application performance. This approach encompasses the characterization of the I/O system at three different levels: application, I/O system and I/O devices. We select different system configuration and/or I/O operation parameters and we evaluate the impact on performance by considering both the application and the I/O architecture. During I/O configuration analysis we identify configurable factors that have an impact on the performance of the I/O system. In addition, we extract information in order to select the most suitable configuration for the application.
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Conference Paper: Methodology for Performance Evaluation of the Input/Output System on Computer Clusters
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ABSTRACT: In this paper a method for execution programming of data-intensive applications is presented. The method is based on storage Quality of Service SQoS provisioning. SQoS provisioning uses the semantic based storage monitoring based on a storage resources model and a storage performance management. Test results show the gain for the execution time when using the QStorMan toolkit which implements the presented method. Taking into account the SQoS provisioning opportunity on the one hand, and the increasingly growing user demands on the other hand, we believe that the execution programming of data-intensive applications can bring a new quality into the application execution.Scientific Programming 01/2012; 20(1):69-80. DOI:10.1155/2012/684217 · 0.67 Impact Factor