57 resultados para Aco Clusters
Resumo:
Parallel execution is a very efficient means of processing vast amounts of data in a small amount of time. Creating parallel applications has never been easy, and requires much knowledge of the task and the execution environment used to execute parallel processes. The process of creating parallel applications can be made easier through using a compiler that automatically parallelises a supplied application. Executing the parallel application is also simplified when a well designed execution environment is used. Such an execution environment provides very powerful operations to the programmer transparently. Combining both a parallelising compiler and execution environment and providing a fully automated parallelisation and execution tool is the aim of this research. The advantage of using such a fully automated tool is that the user does not need to provide any additional input to gain the benefits of parallel execution. This report shows the tool and how it transparently supports the programmer creating parallel applications and supports their execution.
Resumo:
Cluster computing has come to prominence as a cost-effective parallel processing tool for solving many complex computational problems. In this paper, we propose a new timesharing opportunistic scheduling policy to support remote batch job executions over networked clusters to be used in conjunction with the Condor Up-Down scheduling algorithm. We show that timesharing approaches can be used in an opportunistic setting to improve both mean job slowdowns and mean response times with little or no throughput reduction. We also show that the proposed algorithm achieves significant improvement in job response time and slowdown as compared to exiting approaches and some recently proposed new approaches.
Resumo:
Cluster systems are becoming more prevalent in today’s computer society and users are beginning to request that these systems be reliable. Currently, most clusters have been designed to provide high performance at the cost of providing little to no reliability. To combat this, this report looks at how a recovery facility, based on either a centralised or distributed approach could be implemented into a cluster that is supported by a check pointing facility. This recovery facility can then recover failed user processes by using checkpoints of the processes that have been taken during failure free execution.
Resumo:
In this paper, we have demonstrated how the existing programming environments, tools and middleware could be used for the study of execution performance of parallel and sequential applications on a non-dedicated cluster. A set of parallel and sequential benchmark applications selected for and used in the experiments were characterized, and experiment requirements shown.
Resumo:
IBM has announced Autonomic Computing as one of its Grand Challenges. A list of characteristics was generated to describe an autonomic computing system. Many researchers and research group have responded positively to the challenge by initiating research around one or two of the characteristics identified by IBM as the requirements for Autonomic Computing. We have addressed the IBMrsquos request to contribute to the challenge by building an autonomic operating system that possesses nearly all IBM characteristics. This paper contains our response to the IBMrsquos Autonomic Computing Challenge.
Resumo:
Present operating systems are not built to support parallel computing on clusters - they do not provide services to manage parallelism, i.e., to manage parallel processes and cluster resources. They do not provide support for both programming paradigms, Message Passing (MP) or Distributed Shared Memory (DSM). Due to poor operating systems, users must deal with computers of a cluster rather than to see this cluster as a single powerful computer. There is a need for cluster operating systems. We claim that it is possible to develop a cluster operating system that is able to efficiently manage parallelism, support MP and DSM and offer transparency. To substantiate this claim the first version of a cluster operating system managing parallelism and offering transparency, called GENESIS, has been developed.
Resumo:
The human body was used to illustrate an Autonomic Computing system that possesses self-knowledge, self-configuration, self-optimization, self-healing, and self-protection, knowledge of its environment and user friendliness properties. Autonomic Computing was identified by IBM as one of the Grand Challenges. Many researchers and research groups have responded positively to the challenge by initiating research around one or two of the characteristics
identified by IBM as the requirements for Autonomic Computing. One of the areas that could benefit from the comprehensive approach created by the Autonomic Computing vision is parallel processing on nondedicated clusters. This paper shows a general design of services and initial implementation of a system that moves parallel processing on clusters to the computing mainstream using the Autonomic Computing vision.
Resumo:
IBM has announced Autonomic Computing as one of its Grand Challenges. A list of characteristics was generated to describe an autonomic computing system. Many researchers and research group have responded positively to the challenge by initiating research around one or two of the characteristics identified by IBM as the requirements for Autonomic Computing. We have addressed the IBMs request to contribute to the challenge by building an autonomic operating system that possesses nearly all IBM characteristics. This paper contains our response to the IBMs Autonomic Computing Challenge.
Resumo:
This paper considers the need for knowledge management (KM) in regional clusters comprising many small and medium enterprises (SMEs) and the appropriate KM techniques for this form of economic organisation. Information and communication technologies offer a range of tools to help such clusters develop into electronically-linked eClusters, making KM possible on a scale not previously possible. Most KM techniques have been developed by large organisations and their relevance to SME-based clusters has received little attention. Based on our analysis of the literature, we conclude that KM approaches based on personalised rather than codified information are the most promising model for regionally-based eClusters and that Communities of Practice arising from open forms of internet collaboration are most likely to be successful in this environment. Future research will identify key issues and appropriate techniques for supporting regional clusters with electronic systems for KM.
Resumo:
This research aims at improving our understanding of backfilling job scheduling algorithms. The most frequently used algorithm, EASY-backfilling, was selected for a performance evaluation by scheduling static workloads of parallel jobs on a computer cluster. To achieve the aim, we have developed a batch job scheduler for Linux clusters, implemented several scheduling algorithms including ARCA and EASY-Backfilling, and carried out their performance evaluation by running well known MPI applications on a real cluster. Our performance evaluation carried out for EASY-Backfilling serves two purposes. First, the performance results obtained from our evaluation can be used to validate other researcherspsila results generated by simulation, and second, the methodology used in our evaluation has alleviated many problems existed in the simulations presented in the current literature.
Resumo:
The crystal structure of the novel methylene-bridged tetraorganodistannoxane {[Ph(HO)SnCH2Sn(I)Ph]O}4 (1) depends on the solvent it is crystallised from and is controlled by hydrogen bridges and interhalogen interactions.