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Task-RM: A Resource Manager for Energy Reduction in Task-Parallel Applications under Quality of Service Constraints

2022; Association for Computing Machinery; Volume: 19; Issue: 1 Linguagem: Inglês

10.1145/3494537

1544-3973

Muhammad Waqar Azhar, Miquel Pericàs, Per Stenström,

Distributed and Parallel Computing Systems

Improving energy efficiency is an important goal of computer system design. This article focuses on a general model of task-parallel applications under quality-of-service requirements on the completion time. Our technique, called Task-RM , exploits the variance in task execution-times and imbalance between tasks to allocate just enough resources in terms of voltage-frequency and core-allocation so that the application completes before the deadline. Moreover, we provide a solution that can harness additional energy savings with the availability of additional processors. We observe that, for the proposed run-time resource manager to allocate resources, it requires specification of the soft deadlines to the tasks. This is accomplished by analyzing the energy-saving scenarios offline and by providing Task-RM with the performance requirements of the tasks. The evaluation shows an energy saving of 33% compared to race-to-idle and 22% compared to dynamic slack allocation (DSA) with an overhead of less than 1%.