Loop scheduling on parallel and distributed systems has been thoroughly investigated in the past. However, none of these studies considered the multi-core architecture feature for emerging grid systems. Although there have been many studies proposed to employ the hybrid MPI and OpenMP programming model to exploit different levels of parallelism for a distributed system with multi-core computers, none of them were aimed at parallel loop self-scheduling. Therefore, this paper investigates how to employ the hybrid MPI and OpenMP model to design a parallel loop selfscheduling scheme adapted to the multi-core architecture for emerging grid systems. Three different featured applications are implemented and evaluated to demonstrate the effectiveness of the proposed scheduling approach. The experimental results show that the proposed approach outperforms the previous work for the three applications and the speedups range from 1.13 to 1.75.
This paper presents a Platform of Extensible Workflow Simulation Service (Pewss), which we have developed to provide a cloud service for aiding research work in workflow scheduling. The simulation has been a major tool for performance evaluation and comparison in workflow scheduling research. However, researchers usually have to develop their own simulation programs with limited functionality, simply outputting summarized performance results. Pewss has been developed for easing and improving current practices in conducting performance simulations during studying of existing workflow scheduling algorithms or designing of new scheduling algorithms. Pewss has been designed based on the Software as a Service (SaaS) model, adopting a multiuser Web-based client/server architecture. Conducting simulation experiments on Pewss, researchers simply have to implement the scheduling algorithm under study instead of a whole simulation environment, allowing them to focus on their research work without spending unnecessary efforts on the simulation implementation details. Pewss provides the visualization of a workflow execution schedule based on simulation results, offering a convenient way for researchers to gain an insight into the effectiveness, characteristics, and performance bottleneck of scheduling algorithms. As a multiuser environment, Pewss also provides functionality for researchers to facilitate comparative performance analysis and collaborative research works effectively. Pewss has been used in our research work on task-parallel workflow scheduling and has been planned to be extended to support other types of workflow scheduling research problems, eg, mixed-parallel workflows.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.