No abstract

International audienceA high-performance file system is normally a key point for large cluster installations, where hundreds or even thousands of nodes frequently need to manage large volumes of data. While most solutions usually make use of dedicated hardware and/or specific distribution and replication protocols , the NFSP (NFS Parallel) project aims at improving performance within a standard NFS client/server system. In this paper we investigate the possibilities of a replica-tion model for the NFS server which is based on Lasy Release Consistency (LRC). A prototype has been built upon the user-level NFSv2 server and a performance evaluation is carried out

Enhancing the quality of weather and climate forecasts are central scientific research objectives worldwide. However, simulations of the atmosphere, usually demand high processing power and large storage resources. In this context, we present the GBRAMS project, that applies grid computing to speed up the generation of a regional model climatology for Brazil. A grid infrastructure was built to perform long-term integrations of a mesoscale numerical model (BRAMS), managing a queue of up to nine independent jobs submitted to three clusters spread over Brazil. Three distinct middlewares, Globus Toolkit, OurGrid and OAR/CIGRI, were compared in their ability to manage these jobs, and results on the usage of each node of the grid are provided. We analyze the impact of the resulted climatology in the accuracy of climate forecast, showing model bias removal which indicates correctness of the generated climatology. Our central contribution are how to use grid computing to speed-up climatology generation and the middleware impact on this enterprise.

Parallel I/O in cluster computing is one of the most important issues to be tackled as clusters grow larger and larger. Many solutions have been proposed for the problem and, while effective in terms of performance, they usually represent a considerable amount of hacking into a "traditional" Beowulf cluster installation. In this paper, we investigate a parallel solution based on NFS, which reduces the level of intrusion in the file server installation, keeps the client side untouched, and still provides an improved level of performance and scalability for parallel applications. We compare our proposal to other existing file systems using known benchmarks, and demonstrate that it is a valid alternative for general-purpose cluster computing.

No abstract

The leveraging of existing storage space in a cluster is a desirable characteristic of a parallel file system. While undoubtedly an advantage from the point of view of resource management, this possibility may face the administrator with a wide variety of alternatives for configuring the file server, whose optimal layout is not always easy to devise. Given the diversity of parameters such as the number of processors on each node and the capacity and topology of the network, decisions regarding the locality of server components like metadata servers and I/O servers have a direct impact on performance and scalability. In this paper, we explore the capabilities of the dNFSp file system on a large cluster installation, observing how scalable the system behaves in different scenarios and comparing it to a dedicated parallel file system. Our obtained results show that the design of dNFSp allows for a scalable and resource-saving configuration for clusters with a large number of nodes.

O uso da tecnologia Myrinet como um padrão em agregados torna necessário o desenvolvimento de bibliotecas de comunicação que explorem suas características. Esse artigo apresenta a modelagem e a implementação do ambiente DECK para Myrinet, utilizando a API do sistema GM. Serão apresentadas as características do DECK, do GM e será detalhada a implementação mostrando os mecanismos utilizados para que se pudesse alcançar o zero-copy.

This paper presents the design and implementation of DECK-SCI, a multithreaded communication library that fully exploits the high-performance capabilities of the SCI technology. We compare DECK-SCI, in terms of performance, to a commercially distributed MPI implementation and to a freely available MPICH distribution, both specifically designed for SCI clusters.