Interruptible Algorithms for Multiproblem Solving
Spyros Angelopoulos, Alejandro Lopez-Ortiz

TL;DR
This paper develops new methods for designing and analyzing interruptible algorithms that solve multiple problems simultaneously on parallel processors, providing near-optimal schedules and bounds on performance.
Contribution
Introduces new performance measures for multiproblem interruptible algorithms and presents schedules with provable near-optimal performance bounds.
Findings
Proposed the deficiency measure for evaluating schedules.
Constructed schedules within a small factor of optimal performance.
Established lower bounds on schedule deficiency for single and multiple processors.
Abstract
In this paper we address the problem of designing an interruptible system in a setting in which problem instances, all equally important, must be solved concurrently. The system involves scheduling executions of contract algorithms (which offer a trade-off between allowable computation time and quality of the solution) in m identical parallel processors. When an interruption occurs, the system must report a solution to each of the problem instances. The quality of this output is then compared to the best-possible algorithm that has foreknowledge of the interruption time and must, likewise, produce solutions to all problem instances. This extends the well-studied setting in which only one problem instance is queried at interruption time. In this work we first introduce new measures for evaluating the performance of interruptible systems in this setting. In particular, we…
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