The Experts below are selected from a list of 34539 Experts worldwide ranked by ideXlab platform
Sivarama P Dandamudi - One of the best experts on this subject based on the ideXlab platform.
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distributed hierarchical Workstation Cluster co ordination scheme
Parallel Computing in Electrical Engineering, 2000Co-Authors: Jemal H Abawajy, Sivarama P DandamudiAbstract:When a set of geographically distributed autonomous Clusters of Workstations are combined into a single large-scale virtual distributed system, a control mechanism for coordinating the activities of the combined system for effective utilisation of the resources is indispensable. This paper presents a co-ordination mechanism suitable for scheduling and distributing services across the host of such large-scale virtual distributed systems. The proposed scheme is scalable and reliable. Also, it combines both centralised and decentralised co-ordination mechanisms while eliminating/minimising their drawbacks.
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time space sharing distributed job scheduling policy in a Workstation Cluster environment
Parallel Computing in Electrical Engineering, 2000Co-Authors: Jemal H Abawajy, Sivarama P DandamudiAbstract:This paper presents an algorithm for scheduling communication-intensive parallel applications in Workstation Clusters environment. The proposed scheduling policy combines the best attributes of both space-sharing and time-sharing principles and coexists with local schedulers (e.g., the Windows NT scheduler), which both provides coordinated scheduling and can generalise to provide a wide range of resource abstractions.
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parallel job scheduling policy for Workstation Cluster environments
Cluster Computing, 2000Co-Authors: Jemal H Abawajy, Sivarama P DandamudiAbstract:As Workstation Clusters (WC) become more commonly usedfor parallel jobs, there is a growing awareness for the needof job scheduling policies. There have been a fair number ofstudies on how to schedule parallel applications on parallelsystems and a good survey in the area can be found in [5]. Ithas been shown that the best solution to the processorallocation problem in a distributed multiprocessorenvironment is an adaptive scheduling policy that can adjustload distribution based on runtime scheduling algorithms[2,3]. The main idea of adaptive space-sharing policies isthat the number of processors assigned to a job is acompromise between the user’s request and what the systemcan provide. Note that there are differences in thearchitecture of the multiprocessor systems and WC-baseddistributed systems. For example, the processors in themultiprocessors systems are usually homogenous whereasthose of WC are usually heterogeneous. This change ofarchitectural environment requires important differences inthe decisions made by the system scheduling policy. Mostof adaptive scheduling policies for WC-based systemsprovide only rudimentary facilities for partitioning, i.e.,space sharing, the processors among parallel jobs. Inaddition, parallel applications targeted to WC are typicallyresource-intensive, i.e. they require more resources than areavailable at a single site. However, existing adaptivescheduling policies cannot accommodate this requirement.This is because they may assign 1 processor to a job in theextreme cases [2] or lead to a
Jemal H Abawajy - One of the best experts on this subject based on the ideXlab platform.
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distributed hierarchical Workstation Cluster co ordination scheme
Parallel Computing in Electrical Engineering, 2000Co-Authors: Jemal H Abawajy, Sivarama P DandamudiAbstract:When a set of geographically distributed autonomous Clusters of Workstations are combined into a single large-scale virtual distributed system, a control mechanism for coordinating the activities of the combined system for effective utilisation of the resources is indispensable. This paper presents a co-ordination mechanism suitable for scheduling and distributing services across the host of such large-scale virtual distributed systems. The proposed scheme is scalable and reliable. Also, it combines both centralised and decentralised co-ordination mechanisms while eliminating/minimising their drawbacks.
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time space sharing distributed job scheduling policy in a Workstation Cluster environment
Parallel Computing in Electrical Engineering, 2000Co-Authors: Jemal H Abawajy, Sivarama P DandamudiAbstract:This paper presents an algorithm for scheduling communication-intensive parallel applications in Workstation Clusters environment. The proposed scheduling policy combines the best attributes of both space-sharing and time-sharing principles and coexists with local schedulers (e.g., the Windows NT scheduler), which both provides coordinated scheduling and can generalise to provide a wide range of resource abstractions.
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parallel job scheduling policy for Workstation Cluster environments
Cluster Computing, 2000Co-Authors: Jemal H Abawajy, Sivarama P DandamudiAbstract:As Workstation Clusters (WC) become more commonly usedfor parallel jobs, there is a growing awareness for the needof job scheduling policies. There have been a fair number ofstudies on how to schedule parallel applications on parallelsystems and a good survey in the area can be found in [5]. Ithas been shown that the best solution to the processorallocation problem in a distributed multiprocessorenvironment is an adaptive scheduling policy that can adjustload distribution based on runtime scheduling algorithms[2,3]. The main idea of adaptive space-sharing policies isthat the number of processors assigned to a job is acompromise between the user’s request and what the systemcan provide. Note that there are differences in thearchitecture of the multiprocessor systems and WC-baseddistributed systems. For example, the processors in themultiprocessors systems are usually homogenous whereasthose of WC are usually heterogeneous. This change ofarchitectural environment requires important differences inthe decisions made by the system scheduling policy. Mostof adaptive scheduling policies for WC-based systemsprovide only rudimentary facilities for partitioning, i.e.,space sharing, the processors among parallel jobs. Inaddition, parallel applications targeted to WC are typicallyresource-intensive, i.e. they require more resources than areavailable at a single site. However, existing adaptivescheduling policies cannot accommodate this requirement.This is because they may assign 1 processor to a job in theextreme cases [2] or lead to a
David E Dougherty - One of the best experts on this subject based on the ideXlab platform.
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a comparative study of pvm Workstation Cluster implementations of a two phase subsurface flow model
Advances in Water Resources, 1994Co-Authors: Margare J Eppstei, David E DoughertyAbstract:Abstract Four versions of a message-passing, distributed-memory, distributed-disk multicomputer application for simulating two-phase fluid flow in porous media are studied. The FORTRAN 77 finite element code, solved in parallel using an iterative domain-decomposition method, was ported from a shared-memory multiprocessor implementation to a network of heterogeneous computers using the PVM (Parallel Virtual Machine) software system. Issues concerning the calculation of speedups in Cluster computing are discussed, and the performance of the four versions is compared. Parallel efficiencies of up to nearly 60% were achieved using 17 homogeneous networked Workstations; speedups were comparable to the shared-memory implementation. We conclude that network multicomputing using PVM is an attractive alternative to hardware multiprocessors for large-grained parallel implementations of computationally intensive problems in hydrology.
E V Krishnamurthy - One of the best experts on this subject based on the ideXlab platform.
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scalable performance in Workstation Cluster influence of a programming paradigm
International Conference on Parallel Processing, 2002Co-Authors: V K Murthy, E V KrishnamurthyAbstract:Scalable performance can be obtained in a network Cluster of Workstations by proper choice of programming paradigm and software tools such as PVM/MPI. However, the ratio of message transmission time to computation time plays a crucial role. For regular problems such as matrix computations this ratio can be easily inferred. However, for more complex problems such as evolutionary computations this ratio cannot be arrived at unless the programmer has very good problem domain knowledge.
Gunna Ataas - One of the best experts on this subject based on the ideXlab platform.
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scalability of a Workstation Cluster architecture for video on demand applications
Lecture Notes in Computer Science, 2000Co-Authors: Pete H Hughes, Gunna AtaasAbstract:Video-on-demand (VoD) applications require architectures which are scalable over a wide range of capacity. Two of the most promising architectures for VoD are massively parallel symmetrical computers based on distributed memory (MPP) and Clusters of Workstations interconnected by a high-performance network. The work described here investigates the scalability of a prototype Cluster architecture and compares it with a commercially available hypercube MPP system. Measurement experiments using emulated workloads were carried out for increasing loads, and the effects on capacity of encoding-mode and user interactions were explored. Static analysis, supported by simulation results was used to make projections over a range of configurations and technology assumptions. Sample results are presented which chart scalability on two hierarchic levels.
