Impact of Workload and System Parameters on Next Generation Cluster Scheduling Mechanisms
IEEE Transactions on Parallel and Distributed Systems
Scalable Parallel Computing: Technology,Architecture,Programming
Scalable Parallel Computing: Technology,Architecture,Programming
Continuous-time hidden Markov models for network performance evaluation
Performance Evaluation
Schedulability analysis of applications with stochastic task execution times
ACM Transactions on Embedded Computing Systems (TECS)
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Parallel Computing has become a powerful tool to overcome certain types of computational problems in many areas such as engineering, especially due to the increasing diversity of platforms for execution of this type of application. The use of parallel computing over LANs and WANs is an alternative in the universe of dedicated environments (parallel machines and clusters), but, in some cases, it needs to imply QoS (Quality of Service) parameters, so it can execute efficiently. In this scenario, the deployment of resource allocation scheme plays an important role in order to satisfy the QoS requirements for parallel applications. In this paper we propose and present Markovian models for resource allocation (CPU allocation) schemes in a GPOS (General Purpose Operating Systems), aiming at offering an optimization method which makes the efficient performance of parallel and interactive applications feasible.