Personne
Luis Maria Costero Valero
Publications associées (7)
CloudProphet: A Machine Learning-Based Performance Prediction for Public Clouds
David Atienza Alonso, Marina Zapater Sancho, Luis Maria Costero Valero, Darong Huang, Ali Pahlevan
Computing servers have played a key role in developing and processing emerging compute-intensive applications in recent years. Consolidating multiple virtual machines (VMs) inside one server to run various applications introduces severe competence for limi ...
2024Is the powersave governor really saving power?
David Atienza Alonso, Luis Maria Costero Valero, Darong Huang
A frequency scaling governor is critical for the performance management of cloud servers, as it enhances energy efficiency and helps to control operational temperatures, thereby ensuring system reliability. However, our in-depth analysis of the application ...
2024Intermediate Address Space: virtual memory optimization of heterogeneous architectures for cache-resident workloads
David Atienza Alonso, Marina Zapater Sancho, Luis Maria Costero Valero, Darong Huang, Qunyou Liu
The increasing demand for computing power and the emergence of heterogeneous computing architectures have driven the exploration of innovative techniques to address current limitations in both the compute and memory subsystems. One such solution is the use ...
2024Dynamic power budget redistribution under a power cap on multi-application environments
We present a two-level implementation of an infrastructure that allows performance maximization under a power-cap on multi-application environments with minimal user intervention. At the application level, we integrate BAR (Power Budget-Aware Runtime Sched ...
ELSEVIER2023Reinforcement Learning-Based Joint Reliability and Performance Optimization for Hybrid-Cache Computing Servers
David Atienza Alonso, Marina Zapater Sancho, Luis Maria Costero Valero, Darong Huang, Ali Pahlevan
Computing servers play a key role in the development and process of emerging compute-intensive applications in recent years. However, they need to operate efficiently from an energy perspective viewpoint, while maximizing the performance and lifetime of th ...
2022Resource Management for Power-Constrained HEVC Transcoding Using Reinforcement Learning
David Atienza Alonso, Marina Zapater Sancho, Luis Maria Costero Valero, Arman Iranfar
The advent of online video streaming services along with the users' demand for high-quality contents require High Efficiency Video Coding (HEVC), which provides higher quality and compression at the cost of increased complexity. On one hand, HEVC exposes a ...
2020MAMUT: Multi-Agent Reinforcement Learning for Efficient Real-Time Multi-User Video Transcoding
David Atienza Alonso, Marina Zapater Sancho, Luis Maria Costero Valero, Arman Iranfar
Real-time video transcoding has recently raised as a valid alternative to address the ever-increasing demand for video contents in servers' infrastructures in current multi-user environments. High Efficiency Video Coding (HEVC) makes efficient online trans ...
IEEE2019