The AppLeS Parameter Sweep Template: User-Level Middleware for the Grid

By Henri Casanova, Graziano Obertelli, Francine Berman, R. Wolski. International Conference on Software Composition, 2000

456 citations recorded by the source corpus.

The Computational Grid is a promising platform for the efficient execution of parameter sweep applications over large parameter spaces. To achieve performance on the Grid, such applications must be scheduled so that shared data files are strategically placed to maximize reuse, and so that the application execution can adapt to the deliverable performance potential of target heterogeneous, distributed and shared resources. Parameter sweep applications are an important class of applications and would greatly benefit from the development of Grid middleware that embeds a scheduler for performance and targets Grid resources transparently. In this paper we describe a user-level Grid middleware project, the AppLeS Parameter Sweep Template (APST), that uses application-level scheduling techniques [1] and various Grid technologies to allow the efficient deployment of parameter sweep applications over the Grid. We discuss several possible scheduling algorithms and detail our software design. We then describe our current implementation of APST using systems like Globus [2], NetSolve [3] and the Network Weather Service [4], and present experimental results.

Subfields: Computer Networks and Communications, Hardware and Architecture, Information Systems and Management

View Paper: https://www.semanticscholar.org/paper/3beac7a56d10df066adf4c09940ef70e60e9090f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

In Hardware and Architecture

In Information Systems and Management

Citations in the corpus

The Anatomy of the Grid: Enabling Scalable Virtual Organizations (2001, unknown): “, 1998) and manager-worker frameworks (Casanova et al., 2000; Goux et al., 2000).”
Condor-G: A Computation Management Agent for Multi-Institutional Grids (2001, background): “An application-level scheduler for high-throughput scheduling that takes data locality information into account in interesting ways has been constructed [10].”
The Grid Economy (2005, background): “System-centric Grid resource management systems such as Legion [64], Condor [41], AppLeS PST [15], [21], NetSolve [20], PUNCH [47], and XtremWeb [17] adopt a conventional strategy, where a scheduling component decides which jobs are to be executed at which resource based on cost functions driven by ”
Simgrid: a toolkit for the simulation of application scheduling (2001, methodology): “Preliminary experiment s in [3] provide evidence of the ability of Simgrid to rank algorithms accurately, and future work will report on more extensive experimentations.”
Economic-based Distributed Resource Management and Scheduling for Grid Computing (2002, background): “Most of the related systems for Grid resource management and scheduling (such as Legion [123], Condor [79], AppLeS PST [28][42], NetSolve [41], PUNCH [85], and XtremWeb [32]) adopt a conventional strategy where a scheduling component decides which jobs are to be executed at which resource based on c”
Decoupling computation and data scheduling in distributed data-intensive applications (2002, methodology): “[12] describe an adaptive scheduling algorithm for parameter sweep applications in Grid environments that takes data storage issues into account.”
Analyzing Market-Based Resource Allocation Strategies for the Computational Grid (2001, background): “…and Winkler, 2000; Grimshaw et al., 1994; http://www.csse. monash.edu.au/~rajkumar/ecogrid/index.html; http:// www.computingportals.org/projects/economyManager. xml.html) or localized application control (Casanova et al., 2000; Berman et al., 1996; Arndt et al., 1998; Gehrinf and Reinfeld, 1996).”
On Death, Taxes, and the Convergence of Peer-to-Peer and Grid Computing (2003, background): “…is presumably, in part at least, better network connectivity, which also allows for more flexibility in Grid application design: in addition to loosely coupled applications [1, 10, 12], Grids have been used for numerical simulation [3, 43] and branch-and-bound-based optimization problems [7].”
Adaptive Computing on the Grid Using AppLeS (2003, methodology): “To date, we have developed two AppLeS templates—APST (AppLeS Parameter Sweep Template) [35], [15], which targets parameter sweep applications, and AMWAT (AppLeS Master-Worker Application Template) [36], which targets master/worker applications .”
QoS guided Min-Min heuristic for grid task scheduling (2003, background): “[18] Henri Casanova, Graziano Obertelii, Francine Berman, Rich Wolski.”