Network‐based concurrent computing on the PVM system

Geist, G.A.; Sunderam, Vaidy S.

doi:10.1002/cpe.4330040403

Cited by 198 publications

(64 citation statements)

References 16 publications

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“…In addition to shared memory, another popular programming model for loosely synchronized parallel machines is message-passing. Popular message passing libraries such as PVM [Geist and Sunderam 1992] and MPI [Message Passing Interface Forum 1994] contain implementations of barriers as a fundamental synchronization service.…”

Section: Synchronizationmentioning

confidence: 99%

Distributed application configuration, management, and visualization with plush

Albrecht

Tuttle

Braud

et al. 2011

ACM Trans. Internet Technol.

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Support for distributed application management in large-scale networked environments remains in its early stages. Although a number of solutions exist for subtasks of application deployment, monitoring, and maintenance in distributed environments, few tools provide a unified framework for application management. Many of the existing tools address the management needs of a single type of application or service that runs in a specific environment, and these tools are not adaptable enough to be used for other applications or platforms. To this end, we present the design and implementation of Plush, a fully configurable application management infrastructure designed to meet the general requirements of several different classes of distributed applications. Plush allows developers to specifically define the flow of control needed by their computations using application building blocks. Through an extensible resource management interface, Plush supports execution in a variety of environments, including both live deployment platforms and emulated clusters. Plush also uses relaxed synchronization primitives for improving fault tolerance and liveness in failure-prone environments. To gain an understanding of how Plush manages different classes of distributed applications, we take a closer look at specific applications and evaluate how Plush provides support for each.

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Section: Synchronizationmentioning

confidence: 99%

Distributed application configuration, management, and visualization with plush

Albrecht

Tuttle

Braud

et al. 2011

ACM Trans. Internet Technol.

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“…Each task is assumed to be non-preemptible, and have a fixed resource requirement "shape" (in terms of the number of processors required over a time period). The non-malleability assumption is true of most current-day parallel applications written in a message-passing style using systems such as PVM [7] or MPI [9]: these applications can execute on a range of machine sizes, but require that the number of processors assigned to the application remain unchanged over the entire lifetime. We also assume that information about all tasks of the job is available upon job arrival.…”

Section: Scheduling Formulationmentioning

confidence: 99%

Exploiting Application Tunability for Efficient, Predictable Parallel Resource Management

Chang¹,

Karamcheti²,

Kedem³

1998

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Parallel computing is becoming increasing central and mainstream, driven both by the widespread availability of commodity SMP and high-performance cluster platforms, as well as the growing use of parallelism in general-purpose applications such as image recognition, virtual reality, and media processing. In addition to performance requirements, the latter computations impose soft real-time constraints, necessitating efficient, predictable parallel resource management. Unfortunately, traditional resource management approaches in both parallel and real-time systems are inadequate for meeting this objective; the parallel approaches focus primarily on improving application performance and/or system utilization at the cost of arbitrarily delaying a given application, while the real-time approaches are overly conservative sacrificing system utilization in order to meet application deadlines.In this paper, we propose a novel approach for increasing parallel system utilization while meeting application soft real-time deadlines. Our approach exploits the application tunability found in several general-purpose computations. Tunability refers to an application's ability to trade off resource requirements over time, while maintaining a desired level of output quality. In other words, a large allocation of resources in one stage of the computation's lifetime may compensate, in a parameterizable manner, for a smaller allocation in another stage. We first describe language extensions to support tunability in the Calypso programming system, a component of the MILAN metacomputing project, and evaluate their expressiveness using an image processing application. We then characterize the performance benefits of tunability, using a synthetic task system to systematically identify its benefits and shortcomings. Our results are very encouraging: application tunability is convenient to express, and can significantly improve parallel system utilization for computations with predictability requirements.

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“…To help with the program development under a distributed computing environment, a number of software tools have been developed: PVM, Theoretical Chemistry Message Passing Tool Kit (TCMSG), Parasoft Express (EXPRESS), Network Linda (LINDA), and Message Passing Interface (MPI). PVM [13,14] is chosen here since it has a large user group with possibly the best support for heterogeneous environment.…”

Section: Introductionmentioning

confidence: 99%

Parallelization of 3-D ADI Scheme on Telegraph Problem using Domain Decomposition with PVM

SimonUzezi¹,

Shariffudin²

2012

IJAIS

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A parallel implementation of 3-D Alternating Direction Implicit (3-D ADI) method on 3-D Telegraph problem on a distributed computing environment through Parallel Virtual Machine (PVM) is reported. The numerical method is implicit and is based on a splitting strategy which is applied alternately at each half time step. The parallelization is implemented by a Domain Decomposition (DD) strategy on a distributed system with Single Program Multiple Data (SPMD) model on a PVM platform. The parallelization strategy and performance are discussed. Different strategies to improve the computational efficiency are proposed.

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Network‐based concurrent computing on the PVM system

Cited by 198 publications

References 16 publications

Distributed application configuration, management, and visualization with plush

Distributed application configuration, management, and visualization with plush

Exploiting Application Tunability for Efficient, Predictable Parallel Resource Management

Parallelization of 3-D ADI Scheme on Telegraph Problem using Domain Decomposition with PVM

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