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Experiments play an important role in parallel and distributed computing. Simulation is a common experimental technique that relies on abstractions of the tested application and execution environment but offers reproducibility of results and fast exploration of numerous scenarios. This article focuses on setting up the experimental environment of a simulation run. First we analyze the requirements...
Task scheduling is one of the most prominent problems in the era of parallel computing. We find scheduling algorithms in every domain of computer science, e.g., mapping multiprocessor tasks to clusters, mapping jobs to grid resources, or mapping fine-grained tasks to cores of multicore processors. Many tools exist that help understand or debug an application by presenting visual representations of...
Many scientific applications can be structured as Parallel Task Graphs (PTGs), i.e., graphs of data-parallel tasks. Adding data-parallelism to a task-parallel application provides opportunities for higher performance and scalability, but poses scheduling challenges. We study the off-line scheduling of multiple PTGs on a single, homogeneous cluster. The objective is to optimize performance and fairness...
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