RT Conference Proceedings
T1 Tasks Fairness Scheduler for GPU
A1 López Albelda, Bernabé
A1 González-Linares, José María
A1 Guil-Mata, Nicolás
K1 Programación de ordenadores
K1 Proceso electrónico de datos
AB 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).
YR 2019
FD 2019-09-24
LK https://hdl.handle.net/10630/18447
UL https://hdl.handle.net/10630/18447
LA eng
NO Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 19 ene 2026