Job Scheduling with Machine Speeds for Password Cracking Using Hashtopolis

Rudy, Jarosław; Rodwald, Przemysław

doi:10.1007/978-3-030-48256-5_51

Cited by 2 publications

(1 citation statement)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A number of scientific fields rely on high-performance computing (HPC) for running simulations and data analysis applications. For example, [1] reviews the deployment of quantum chemistry methods on HPC platforms, [2] describes flood simulation applications in the civil engineering field running on HPC architectures, and [3] considers the scheduling problem for cybersecurity applications. Scheduling plays a critical role in HPC systems, as HPC schedulers are a primary interface between users and computational resources.…”

Section: Introductionmentioning

confidence: 99%

Analytical and Numerical Evaluation of Co-Scheduling Strategies and Their Application

Kuchumov

Korkhov

2021

Computers

View full text Add to dashboard Cite

Applications in high-performance computing (HPC) may not use all available computational resources, leaving some of them underutilized. By co-scheduling, i.e., running more than one application on the same computational node, it is possible to improve resource utilization and overall throughput. Some applications may have conflicting requirements on resources and co-scheduling may cause performance degradation, so it is important to take it into account in scheduling decisions. In this paper, we formalize the co-scheduling problem and propose multiple scheduling strategies to solve it: an optimal strategy, an online strategy and heuristic strategies. These strategies vary in terms of the optimality of the solution they produce and a priori information about the system they require. We show theoretically that the online strategy provides schedules with a competitive ratio that has a constant upper limit. This allows us to solve the co-scheduling problem using heuristic strategies that approximate this online strategy. Numerical simulations show how heuristic strategies compare to the optimal strategy for different input systems. We propose a method for measuring input parameters of the model in practice and evaluate this method on HPC benchmark applications. We show the high accuracy of the measurement method, which allows us to apply the proposed scheduling strategies in the scheduler implementation.

show abstract

Section: Introductionmentioning

confidence: 99%