Titlebook: Euro-Par 2018: Parallel Processing Workshops; Euro-Par 2018 Intern Gabriele Mencagli,Dora B. Heras,Stephen L. Scott Conference proceedings

人造

Klaus von Rosenstiel,Hans Rundfeldtcheduling of all submitted containers and for efficient management, on the fly, of the resources allocation. The key idea is to make the specification on resources demand less rigid and to ask the system to decide on the precise number of resources to allocate to a container. Our framework is implem

仇恨

粘土

Innovative

TPICDS: A Two-Phase Parallel Approach for Incremental Clustering of Data Streamstation of a recently developed prototype-based algorithm into three existing parallel frameworks. Based on the evaluation of performance, the paper then presents a customised pipeline framework that combines incremental and two-phase learning into a balanced approach that dynamically allocates the a

semiskilled

Cost of Fault-Tolerance on Data Stream Processingincreasing amount of data produced every day, data streaming engines run on top of a distributed system. In this setting failures will likely happen. Current distributed data streaming engines like Apache Flink provide fault tolerance. In this paper we evaluate the impact on performance of fault tol

烤架

Autonomic and Latency-Aware Degree of Parallelism Management in SParlism to increase performance. However, programmers are often facing a trade-off between coding productivity and performance when introducing parallelism. SPar was created for balancing this trade-off to the application programmers by using the . attributes’ annotation mechanism. In SPar and other pr

chapel

CHASM

Antarctic

A Resource Allocation Framework with Qualitative and Quantitative SLA Classesk is proposed in the context of containers with two qualitative and two quantitative SLAs classes to meet the needs of users. The two qualitative classes represent the satisfaction time criterion, and the reputation criterion. Moreover, the two quantitative classes represent the criterion over the n