Publications de Ali Pahlevan | EPFL Graph Search

CloudProphet: A Machine Learning-Based Performance Prediction for Public Clouds

David Atienza Alonso, Ali Pahlevan, Marina Zapater Sancho, Luis Maria Costero Valero, Darong Huang

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 ...

2024

Reinforcement Learning-Based Joint Reliability and Performance Optimization for Hybrid-Cache Computing Servers

David Atienza Alonso, Ali Pahlevan, Marina Zapater Sancho, Luis Maria Costero Valero, Darong Huang

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 ...

2022

COCKTAIL: Multi-Core Co-Optimization Framework With Proactive Reliability Management

David Atienza Alonso, Ali Pahlevan, Marina Zapater Sancho, Darong Huang

High performance computing (HPC) servers aim to meet an increase in the number and complexity of tasks and, consequently, to address the energy efficiency challenge. In addition to energy efficiency, it is essential to manage lifetime limitations of power- ...

2022

MAGNETIC: Multi-Agent Machine Learning-Based Approach for Energy Efficient Dynamic Consolidation in Data Centers

David Atienza Alonso, Ali Pahlevan, Marina Zapater Sancho, Kosar Haghshenas

Improving the energy efficiency of data centers while guaranteeing Quality of Service (QoS), together with detecting performance variability of servers caused by either hardware or software failures, are two of the major challenges for efficient resource m ...

2022

ECOGreen: Electricity Cost Optimization for Green Datacenters in Emerging Power Markets

David Atienza Alonso, Ayse Kivilcim Coskun, Ali Pahlevan, Marina Zapater Sancho

Modern datacenters need to tackle efficiently the increasing demand for computing resources while minimizing energy usage and monetary costs. Power market operators have recently introduced emerging demand-response programs, in which electricity consumers ...

2021

Multi-Objective System-Level Management of Modern Green Data Centers

Ali Pahlevan

In our modern society, the average citizen has turned into a daily cloud user. Despite being virtually transparent for the user, internet services require data centers behind the scenes. Data centers burn several megawatts of power and their electricity bi ...

EPFL2019

Enhancing Two-Phase Cooling Efficiency through Thermal- Aware Workload Mapping for Power-Hungry Servers

David Atienza Alonso, Ali Pahlevan, Marina Zapater Sancho, Arman Iranfar

The power density and, consequently, power hungriness of server processors is growing by the day. Traditional air cooling systems fail to cope with such high heat densities, whereas single-phase liquid-cooling still requires high mass flowrate, high pumpin ...

IEEE and ACM Press2019

Integrating Heuristic and Machine-Learning Methods for Efficient Virtual Machine Allocation in Data Centers

David Atienza Alonso, Ali Pahlevan, Marina Zapater Sancho, Xiaoyu Qu

Modern cloud data centers (DCs) need to tackle efficiently the increasing demand for computing resources and address the energy efficiency challenge. Therefore, it is essential to develop resource provisioning policies that are aware of virtual machine (VM ...

2018

Online Efficient Bio-Medical Video Transcoding on MPSoCs Through Content-Aware Workload Allocation

David Atienza Alonso, Ali Pahlevan, Marina Zapater Sancho, Arman Iranfar

Bio-medical image processing in the field of telemedicine, and in particular the definition of systems that allow medical diagnostics in a collaborative and distributed way is experiencing an undeniable growth. Due to the high quality of bio-medical videos ...

IEEE and ACM Press2018

Energy Proportionality in Near-Threshold Computing Servers and Cloud Data Centers: Consolidating or Not?

David Atienza Alonso, Luca Benini, Ali Pahlevan, Marina Zapater Sancho, Yasir Mahmood Qureshi

Cloud Computing aims to efficiently tackle the increasing demand of computing resources, and its popularity has led to a dramatic increase in the number of computing servers and data centers worldwide. However, as effect of post-Dennard scaling, computing ...

2018

Exploiting CPU-Load and Data Correlations in Multi-Objective VM Placement for Geo-Distributed Data Centers

David Atienza Alonso, Pablo Garcia del Valle, Ali Pahlevan

Cloud computing has been proposed as a new paradigm to deliver services over the internet. The proliferation of cloud services and increasing users’ demands for computing resources have led to the appearance of geo-distributed data centers (DCs). These DCs ...

EDAA/ACM/IEEE Press2016

Towards Near-Threshold Server Processors

David Atienza Alonso, Luca Benini, Pablo Garcia del Valle, Babak Falsafi, Javier Picorel Obando, Ali Pahlevan, Arash Pourhabibi Zarandi, Marina Zapater Sancho

The popularity of cloud computing has led to a dramatic increase in the number of data centers in the world. The ever-increasing computational demands along with the slowdown in technology scaling has ushered an era of power-limited servers. Techniques suc ...

IEEE/ACM2016