Performance analysis of heterogeneous multi-cluster systems

When building a cost-effective high-performance parallel processing system, a performance model is a useful tool for exploring the design space and examining various parameters. However, performance analysis in such systems has proven to be a challenging task that requires the innovative performance analysis tools and methods to keep up with the rapid evolution and ever increasing complexity of such systems. To this end, we propose an analytical model for heterogeneous multi-cluster systems. The model takes into account stochastic quantities as well as network heterogeneity in bandwidth and latency in each cluster. Also, blocking and non-blocking network architecture model is proposed and are used in performance analysis of the system. The message latency is used as the primary performance metric. The model is validated by constructing a set of simulators to simulate different types of clusters, and by comparing the modeled results with the simulated ones.<br /

Analytical interconnection networks model for multi-cluster computing systems

This paper addresses the problem of interconnection networks performance modeling of large-scale distributed systems with emphases on multi-cluster computing systems. The study of interconnection networks is important because the overall performance of a distributed system is often critically hinged on the effectiveness of its interconnection network. We present an analytical model that considers stochastic quantities as well as processor heterogeneity of the target system. The model is validated through comprehensive simulation, which demonstrates that the proposed model exhibits a good degree of accuracy for various system sizes and under different operating conditions.<br /

Parallel processing DNA sequences on multicluster and grid architectures : Software overhead

A DNA sequence analysis parallelization in large databases using cluster, multi-cluster, and GRID is presented. Achievable speedup, scalability, and overhead introduced by communications are discussed, and the impact of the Grid middleware on the performance obtained with clusters is detailed. The experimental work carried out with homogeneous and heterogeneous clusters is presented, along with a comparison of the results obtained when migrating the algorithms to a GRID. Finally, current lines of work related to the study of models and paradigms for the resolution of parallel algorithms on GRID architectures are presented.Workshop de Procesamiento Distribuido y Paralelo (WPDP)Red de Universidades con Carreras en Informática (RedUNCI

Performance of distributed multiscale simulations

Multiscale simulations model phenomena across natural scales using monolithic or component-based code, running on local or distributed resources. In this work, we investigate the performance of distributed multiscale computing of component-based models, guided by six multiscale applications with different characteristics and from several disciplines. Three modes of distributed multiscale computing are identified: supplementing local dependencies with large-scale resources, load distribution over multiple resources, and load balancing of small- and large-scale resources. We find that the first mode has the apparent benefit of increasing simulation speed, and the second mode can increase simulation speed if local resources are limited. Depending on resource reservation and model coupling topology, the third mode may result in a reduction of resource consumption

Tuning Application in a Multi-cluster Environment

Abstract. The joining of geographically distributed heterogeneous clusters of workstations through the Internet can be a simple and effective approach to speed up a parallel application execution. This paper describes a methodology to migrate a parallel application from a single-cluster to a collection of clusters, guaranteeing a minimum level of efficiency. This methodology is applied to a parallel scientific application to use three geographically scattered clusters located in Argentina, Brazil and Spain. Experimental results prove that the speedup and efficiency estimations provided by this methodology are more than 90% precision. Without the tuning process of the application a 45% of the maximum speedup is obtained whereas a 94% of that maximum speedup is attained when a tuning process is applied. In both cases efficiency is over 90%

Parallel processing DNA sequences on multicluster and grid architectures : Software overhead

A DNA sequence analysis parallelization in large databases using cluster, multi-cluster, and GRID is presented. Achievable speedup, scalability, and overhead introduced by communications are discussed, and the impact of the Grid middleware on the performance obtained with clusters is detailed. The experimental work carried out with homogeneous and heterogeneous clusters is presented, along with a comparison of the results obtained when migrating the algorithms to a GRID. Finally, current lines of work related to the study of models and paradigms for the resolution of parallel algorithms on GRID architectures are presented.Workshop de Procesamiento Distribuido y Paralelo (WPDP)Red de Universidades con Carreras en Informática (RedUNCI