Yiming Han

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—Cloud computing infrastructure offers the computing resources as a homogeneous collection of virtual machine instances by different hardware configurations, which is transparent to end users. In fact, the computational powers of these virtual machine instances are different and behaves as a heterogeneous environment. Thus, scheduling and load balancing for(More)
—Loops are the largest source of parallelism in many scientific applications. Parallelization of irregular loop applications is a challenging problem to achieve scalable performance on large-scale multi-core clusters. Previous research proposed an effective Master-Worker model on clusters for distributed self-scheduling schemes that apply to parallel loops(More)
—Cloud systems have demonstrated the powerful computation and storage capability in many scientific applications. In this paper, we propose a hierarchical distributed loop self-scheduling scheme to achieve good load balancing by applying weighted self-scheduling scheme on a heterogeneous cloud system. This scheme also considers the distribution of the(More)
Cloud systems have demonstrated the powerful computation and storage capability in many scientific applications. In this paper, we propose a class of scalable distributed loop self-scheduling schemes to achieve good load balancing and scalability. We implemented these schemes on a large-scale cluster and on a heterogeneous cloud system. The schemes consider(More)
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