Core Algorithms of the Maui Scheduler

By David B. Jackson, Q. Snell, M. Clement. Job Scheduling Strategies for Parallel Processing, 2001

464 citations recorded by the source corpus.

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

View Paper: https://www.semanticscholar.org/paper/abd1549962d6eb668a49dc2da5d977b7e9fe3e52

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

1. Dror G. Feitelson
2. Larry Rudolph
3. Uwe Schwiegelshohn
4. Dan Tsafrir
5. Yoav Etsion
6. Miron Livny
7. Michael Abd-El-Malek
8. Benjamin C. Reed

In Hardware and Architecture

1. Dror G. Feitelson
2. Larry Rudolph
3. Uwe Schwiegelshohn
4. Dan Tsafrir
5. Yoav Etsion
6. Michael Abd-El-Malek
7. Benjamin C. Reed
8. A. Yoo

In Information Systems

1. Michael Abd-El-Malek
2. Benjamin C. Reed
3. A. Yoo
4. John Wilkes
5. Sharad K. Agarwal
6. Mark Grondona
7. Miron Livny
8. Carlo Curino

Citations in the corpus

• Parallel Job Scheduling - A Status Report (2004, background): “They are frequently combined with the Maui scheduler [27].”
• Backfilling Using System-Generated Predictions Rather than User Runtime Estimates (2007, background): “However, the default of most parallel schedulers (e.g., Maui/Moab [15] and IBM's load-leveler [18]) has remained plain EASY [7], and it has been estimated that 90 percent to 95 percent of the installations do not change this default configuration [14].”
• SLURM: Simple Linux Utility for Resource Management (2003, methodology): “Additional environment variables are appended to the user’s environment before it is sent to the remote , ! ! ' detailing the job’s resources, such as the SLURM job id (42) and the allocated nodes (dev[6-7]).”
• Apache Hadoop YARN: yet another resource negotiator (2013, methodology): “To address some of its multi-tenancy issues, Yahoo! developed and deployed Hadoop on Demand (HoD), which used Torque[7] and Maui[20] to allocate Hadoop clusters on a shared pool of hardware.”
• Distributed computing in practice: the Condor experience (2005, unknown): “A wide variety of powerful batch execution systems such as LoadLeveler [21] (a descendant of Condor), LSF [22], Maui [23], NQE [24], and PBS [25] spread throughout academia and business.”
• Condor and the Grid (2003, background): “A wide variety of powerful batch execution systems such as LoadLeveler [21] (a descendant of Condor), LSF [22], Maui [23], NQE [24], and PBS [25] spread throughout academia and business.”
• Omega: flexible, scalable schedulers for large compute clusters (2013, background): “A N D CLE ME N T, M. Core al­gorithms of the Maui scheduler.”