Condor-G: a computation management agent for multi-institutional grids

Frey, Jaime; Tannenbaum, Todd; Livny, Miron; Foster, Ian; Tuecke, Steven

doi:10.1109/hpdc.2001.945176

Cited by 606 publications

(516 citation statements)

References 18 publications

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“…All of these techniques suffer from at least one of the following problems: i) low scalability (e.g.,Condor [21], Condor-G [22], BOINC [23] and etc.,), ii) low efficiency for structured environments(e.g., Globus [24], Routing Indices (RI) [25], etc.,), iii) inadequate resource descriptions and matching for many-core environments where hardware devices are the resources to be propagated (e.g., NodeWiz [26] , Mercury [27] and SWORD [28]). …”

Section: Related Workmentioning

confidence: 99%

Dynamic, scalable and flexible resource discovery for large-dimension many-core systems

Zarrin

Aguiar

Barraca

2015

Future Generation Computer Systems

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This is the accepted version of the paper.This version of the publication may differ from the final published version. Abstr act Future large scale systems will execute novel operating systems running across many chips with many cores. In this highly distributed environment, resource discovery is an important building block. Resource discovery aims to match the application's demands to the existing (distributed) resources, by discovering and f nding resources at run-time, and then selecting the best resource that matches the application running requirements. The main contribution of this paper is the design and evolution of a highly scalable, highly f exible, resource discovery model for such heterogeneous environments. The model is based on self-organizing processing resources in the system according to a hierarchical resource description where each group of resources has a local directory that collects and keeps the information of the underlying resource members (cores) in dif erent layers. Operationally, at each layer, it consists of a peer-to-peer architecture of modules that, by interacting with each other, provide a global view of the resource availability in a large, dynamic and heterogeneous distributed environment. The proposed resource discovery model provides the adaptability and f exibility to perform complex querying by supporting a large set of signif cant querying features (such as multi-dimensional, range and aggregate querying) while supporting exact and partial matching, both for static and dynamic object contents. The paper demonstrates by simulation how the proposed model can deal with issues such as scalability, ef ciency and adaptability of resource discovery in future many-core systems which are the major challenges in the current state of the art. The simulation show that the proposed resource discovery model can be applied to arbitrary scales of dynamicity, both in terms of complexity and of scale, positioning this proposal as a good architecture for future many-core systems. Permanent repository link

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Section: Related Workmentioning

confidence: 99%

Dynamic, scalable and flexible resource discovery for large-dimension many-core systems

Zarrin

Aguiar

Barraca

2015

Future Generation Computer Systems

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“…The research conducted in this paper will be beneficial for this work. Other relevant efforts are, for example, [7,5] …”

Section: Related Work In the Grid Communitymentioning

confidence: 99%

Software, Component, and Service Deployment in Computational Grids

Laszewski

Blau

Bletzinger

et al. 2002

Lecture Notes in Computer Science

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Abstract. Grids comprise an infrastructure that enables scientists to use a diverse set of distributed remote services and resources as part of complex scientific problem-solving processes. We analyze some of the challenges involved in deploying software and components transparently in Grids. We report on three practical solutions used by the Globus Project. Lessons learned from this experience lead us to believe that it is necessary to support a variety of software and component deployment strategies. These strategies are based on the hosting environment.

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“…Most research efforts have been focusing on designing grid middleware, examples include the Globus Toolkit [17], Legion [13], Condor-G [18], and UNICORE [12]. While these middleware provide convenient mechanisms for resource sharing and the needed security support, they demand the applications to be either developed with special library, or executed in application/service containers.…”

Section: Related Workmentioning

confidence: 99%

InstantGrid: A Framework for On-Demand Grid Point Construction

Yin

Lee

et al. 2004

Lecture Notes in Computer Science

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This paper proposes the InstantGrid framework for on-demand construction of grid points. The framework comprises the following components: (1) a centralized model of software management using an application-centric software grouping scheme; (2) proactive configuration of grid middleware, which shortens the time in composing and switching between execution environments; (3) performance optimization techniques using I/O caching and discriminative file sharing mechanisms; and (4) an in-memory execution mode that enables a machine to participate in grid without affecting the OS/data stored in the permanent storage. Compared with traditional approaches, this new framework is designed to substantially simplify software management in grid systems, and is capable to instantly turn any computer (be it a cluster node or a desktop PC) into a grid-ready platform with the desired execution environment. The advanced features also facilitate ad-hoc formation of grid platforms in computers having idle resources. We describe a reference implementation of InstantGrid for constructing Linux-based grid points. Experimental results demonstrate that a 256-node grid point with commodity grid middleware can be constructed in 5 minutes from scratch.

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Condor-G: a computation management agent for multi-institutional grids

Cited by 606 publications

References 18 publications

Dynamic, scalable and flexible resource discovery for large-dimension many-core systems

Dynamic, scalable and flexible resource discovery for large-dimension many-core systems

Software, Component, and Service Deployment in Computational Grids

InstantGrid: A Framework for On-Demand Grid Point Construction

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