Auto-tuning techniques have been used in the design of routines in recent years. The goal is to develop routines which automatically adapt to the conditions of the computational system in such a way that efficient executions ...

[EN] Tuning and optimising the operations executed in deep learning frameworks is a fundamental task in accelerating the processing of deep neural networks (DNNs). However, this optimisation usually requires extensive ...

[EN] In this paper three PID auto-tuning algorithms which are mainly focused on the disturbance rejection problem are compared. The algorithms differ in both the experiments carried out to obtain information of the process ...