Meta-scheduling

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Meta-scheduling or super scheduling is a computer software technique of optimizing computational workloads by combining an organization's multiple job schedulers into a single aggregated view, allowing batch jobs to be directed to the best location for execution.^{[clarification needed]}

Meta-Scheduling for MPSoCs[]

Meta-scheduling technique is a solution for scheduling a set of dependent or independent faults with different scenarios that are mapping and modeling in an event-tree. It can be used as a dynamic or static scheduling method.

Scenario-Based Meta-Scheduling (SBMeS) for MPSoCs and NoCs[]

Scenario-based and multi-mode approaches are essential techniques in embedded-systems, e.g., design space exploration for MPSoCs and reconfigurable systems.

Scenario-based meta-scheduling (SBMeS) general model

Optimization techniques for the generation of schedule graphs supporting such a SBMeS approach have been developed and implemented.

SBMeS  can promise better performance by reducing dynamic scheduling overhead and recovering from faults.

Figure 27. Meta-visualization of an event

Schedule Gantt map

Figure 24 shows the results of each event in each 〖SM〗_x.

Implementations[]

The following is a partial list of noteworthy open source and commercial meta-schedulers currently available.

• GridWay by the Globus Alliance
• Community Scheduler Framework by Platform Computing & Jilin University
• MP Synergy by United Devices
• Moab Cluster Suite and Maui Cluster scheduler from Adaptive Computing
• DIOGENES (DIstributed Optimal GENEtic algorithm for grid applications Scheduling, started project)
• SynfiniWay's meta-scheduler.
• MeS is designed to generate schedules for anticipated changes of scenarios by Dr.-Ing. Babak Sorkhpour & Prof. Dr.-Ing.Roman Obermaisser in Chair for Embedded Systems in university of Siegen for Energy-Efficient, Robust and Adaptive Time-Triggered Systems (multi-core architectures with Networks-on-chip).

References[]

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• Schopf, Jennifer (2002). "A General Architecture for Scheduling on the Grid" (PDF). Argonne National Laboratory. Archived from the original (PDF) on 2008-09-24.

• B. Sorkhpour and R. Obermaisser. "MeSViz: Visualizing Scenario-based Meta-Schedules for Adaptive Time-Triggered Systems.". in AmE 2018-Automotive meets Electronics; 9th GMM-Symposium, 2018, pp. 1–6
• B. Sorkhpour, R. Obermaisser and A. Murshed, "Meta-Scheduling Techniques for Energy-Efficient, Robust and Adaptive Time-Triggered Systems," in Knowledge-Based Engineering and Innovation (KBEI), 2017 IEEE 4th International Conference on, Tehran, 2017.
• B. Sorkhpour, O. Roman, and Y. Bebawy, Eds., Optimization of Frequency-Scaling in Time-Triggered Multi-Core Architectures using Scenario-Based Meta-Scheduling: “in AmE 2019-Automotive meets Electronics; 10th GMM-Symposium VDE, 2019
• B. Sorkhpour. "Scenario-based meta-scheduling for energy-efficient, robust and adaptive time-triggered multi-core architectures", University of Siegen, Doctoral thesis, July 2019.

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External links[]

This section's use of external links may not follow Wikipedia's policies or guidelines. Please by removing excessive or inappropriate external links, and converting useful links where appropriate into footnote references. (February 2022) (Learn how and when to remove this template message)

• Super Scheduler project by the Asia-Pacific Science Technology Center.
• Meta-Scheduling Techniques for Energy-Efficient by Dr.-Ing. Babak sorkhpour.
• Community Scheduler Framework by Platform Computing & Jilin University
• Adaptive Computing
• DIOGENES (DIstributed Optimal GENEtic algorithm for grid applications Scheduling)
• Prof. Dr.-Ing.Roman Obermaisser
• Chair for Embedded Systems

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