Graph processing is increasingly adopted to solve problems that span many application domains, including scientific computing, social networks, and big-data analytics. These applications present particular features (h...
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(纸本)9798350342543
Graph processing is increasingly adopted to solve problems that span many application domains, including scientific computing, social networks, and big-data analytics. These applications present particular features (huge working sets and irregular scalability) that make the default Linux scheduler, which adopts a time-sharing policy to provide a fair scheduler, perform poorly when co-locating multiple graph applications in the same processor. This work focuses on maximizing processor utilization, which is a major concern of current data centers. To this end, we propose AFAIR, a flexible scheduling policy that allocates multiple graph applications on the same processor and assigns a fraction of the cores exclusively to each application instead of sharing them. Moreover, AFAIR dynamically adds/removes cores to the running applications, adapting the number of threads used for parallel execution to balance memory load. This allows AFAIR to achieve almost perfect fairness, on average 95%.
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