2026-06-01T14:54:52Zhttps://riuma.uma.es/rest/oai/request

oai:riuma.uma.es:10630/184472026-02-03T12:28:17Zcom_10630_2254col_10630_37959

00925njm 22002777a 4500 dc López Albelda, Bernabé author González-Linares, José María author Guil-Mata, Nicolás author 2019-09-24 Nowadays GPU clusters are available in almost every data processing center. Their GPUs are typically shared by different applications that might have different processing needs and/or different levels of priority. As current GPUs do not support hardware-based preemption mechanisms, it is not possible to ensure the required Quality of Service (QoS) when application kernels are offloaded to devices. In this work, we present an efficient software preemption mechanism with low overhead that evicts and relaunches GPU kernels to provide support to different preemptive scheduling policies. We also propose a new fairness-based scheduler named Fair and Responsive Scheduler, (FRS), that takes into account the current value of the kernels slowdown to both select the new kernel to be launched and establish the time interval it is going to run (quantum). https://hdl.handle.net/10630/18447 Programación de ordenadores Proceso electrónico de datos Tasks Fairness Scheduler for GPU