Titlebook: Euro-Par 2021: Parallel Processing Workshops; Euro-Par 2021 Intern Ricardo Chaves,Dora B. Heras,Laura Ricci Conference proceedings 2022 Spr

Engulf

諂媚于人

https://doi.org/10.1007/978-3-663-09711-2nd discuss the results of evaluation which includes autonomous management of a sample application deployed to Amazon Web Services cloud. We also provide the details of training of the management policy using the Proximal Policy Optimization algorithm. Finally, we discuss the feasibility to extend the presented approach to further scenarios.

性上癮

夾死提手勢(shì)

Polydipsia

https://doi.org/10.1007/978-3-662-48862-1application employing five heterogeneous processors that include two Intel multicore CPUs, an Nvidia K40c GPU, an Nvidia P100 PCIe GPU, and an Intel Xeon Phi. Based on our experiments, a dynamic energy saving of 17% is gained while tolerating a performance degradation of 5% (a saving of 106?J for an execution time increase of 0.05?s).

META

https://doi.org/10.1007/978-3-662-31582-8n, or even precompiled OpenCL applications, could utilize the optimization. Despite the lack of explicit programmer effort, our compiler was able to deliver an average of 12.3% speedup over a range of applicable benchmarks on a target CPU platform.

驕傲

miscreant

充足

Heterogeneous Voltage Frequency Scaling of Data-Parallel Applications for Energy Saving on Homogeneogical cores in total. The cost and efficiency of the proposed pruning algorithm for selecting heterogeneous DVFS configurations against the brute-force search are verified and compared experimentally.

GENRE

A Novel Algorithm for Bi-objective Performance-Energy Optimization of Applications with Continuous Papplication employing five heterogeneous processors that include two Intel multicore CPUs, an Nvidia K40c GPU, an Nvidia P100 PCIe GPU, and an Intel Xeon Phi. Based on our experiments, a dynamic energy saving of 17% is gained while tolerating a performance degradation of 5% (a saving of 106?J for an execution time increase of 0.05?s).