Conference Paper

Methodology for Performance Evaluation of the Input/Output System on Computer Clusters

DOI: 10.1109/CLUSTER.2011.83 Conference: 2011 IEEE International Conference on Cluster Computing (CLUSTER), Austin, TX, USA, September 26-30, 2011
Source: DBLP


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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Available from: Emilio Luque, Mar 04, 2014
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    • "A number of studies assumes that each of the workloads has its own characteristics for which specific actions, e.g., management, tuning, configuring can be performed to achieve optimal throughput. A methodology for evaluating of I/O performance on computer clusters under different I/O configurations is proposed in [8]. Three levels of the I/O path are considered: application level, I/O system level and I/O devices. "
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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.
    Preview · Article · Jan 2012 · Scientific Programming