Meta-scheduling

Meta-scheduling or Super scheduling is a computer software technique of optimizing computational workloads by combining an organization's multiple Distributed Resource Managers into a single aggregated view, allowing batch jobs to be directed to the best location for execution.

Meta-Scheduling for MPSoCs

Meta-scheduling technique is a solution for scheduling a set of depended 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. In this work, we use it for static scheduling on adaptive TT MPSoC systems.

Meta-scheduling can be described as a technique to optimize the computational workload by combining and organizing multiple distributed resources in an integrated view. In other words, it is an extended data-flow model and quasi-static scheduling for dynamic behaviour changes.

Scenario-Based Meta-Scheduling (SBMeS)

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

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.

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 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 (NoC)) .

References

• 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

External links

• Super Scheduler project by the Asia-Pacific Science Technology Center.
• Meta-Scheduling Techniques for Energy-Efficient by Babak sorkhpour.