Decentralized List Scheduling
Marc Tchiboukdjian, Nicolas Gast, Denis Trystram

TL;DR
This paper investigates decentralized list scheduling for parallel processing, analyzing the additional costs and performance guarantees when distributing the task list among processors, and provides bounds and experimental validation.
Contribution
It introduces a general methodology to analyze distributed list scheduling, deriving bounds on makespan and improving existing results for various task models.
Findings
Scheduling time for independent tasks is W/m plus a log W term.
The additional scheduling cost is proportional to log W, which is shown to be optimal.
Simulations confirm the theoretical bounds and distribution of makespan.
Abstract
Classical list scheduling is a very popular and efficient technique for scheduling jobs in parallel and distributed platforms. It is inherently centralized. However, with the increasing number of processors, the cost for managing a single centralized list becomes too prohibitive. A suitable approach to reduce the contention is to distribute the list among the computational units: each processor has only a local view of the work to execute. Thus, the scheduler is no longer greedy and standard performance guarantees are lost. The objective of this work is to study the extra cost that must be paid when the list is distributed among the computational units. We first present a general methodology for computing the expected makespan based on the analysis of an adequate potential function which represents the load unbalance between the local lists. We obtain an equation on the evolution of…
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Taxonomy
TopicsOptimization and Search Problems · Scheduling and Optimization Algorithms · Distributed systems and fault tolerance
