Optimal Fair-Workload Scheduling: A Case Study at Glorytek

Static Workload Balance Scheduling; Continuous Case

This article studies a static scheduling method based on workload balancing in the continuous case. An equation is presented for the case when the workload, as continuous function is equally distributed onto processors based on integrals. A sufficient condition is also established for the fully covering property. Finally, some computational results are given to prove that the continuous case is...

Fair Boosting: a Case Study

We study the classical AdaBoost algorithm in the context of fairness. We use the Census Income Dataset (Lichman, 2013) as a case study. We empirically evaluate the bias and error of four variants of AdaBoost relative to an unmodified AdaBoost baseline, and study the trade-offs between reducing bias and maintaining low error. We further define a new notion of fairness and measure it for all of o...

The Case for Fair Multiprocessor Scheduling

Partitioning and global scheduling are two approaches for scheduling real-time tasks on multiprocessors. Though partitioning is sub-optimal, it has traditionally been preferred; this is mainly due to the fact that well-understood uniprocessor scheduling algorithms can be used on each processor. In recent years, global-scheduling algorithms based on the concept of “proportionate fairness” (Pfair...

The case for fair multiprocessor scheduling

Optimal workload allocation model for scheduling divisible data grid applications

Problem statement: In many data grid applications, data can be decomposed into multiple independent sub-datasets and distributed for parallel execution and analysis. Approach: This property had been successfully employed by using Divisible Load Theory (DLT), which had been proved as a powerful tool for modeling divisible load problems in data-intensive grid. Results: There were some scheduling ...