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Marina Zapater Sancho

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Related publications (59)

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PowerCool: Simulation of Cooling and Powering of 3D MPSoCs with Integrated Flow Cell Arrays

David Atienza Alonso, Marina Zapater Sancho, Arvind Raj Mahankali Sridhar, Mohamed Mostafa Sabry Aly, Artem Andreev

Integrated Flow-Cell Arrays (FCAs) represent a combination of integrated liquid cooling and on-chip power generation, converting chemical energy of the flowing electrolyte solutions to electrical energy. The FCA technology provides a promising way to addre ...

Institute of Electrical and Electronics Engineers2017

Enabling Optimal Power Generation of Flow Cell Arrays in 3D MPSoCs with On-Chip Switched Capacitor Converters

David Atienza Alonso, Marina Zapater Sancho, Alexandre Sébastien Julien Levisse, Halima Najibi

Flow cell arrays (FCAs) provide efficient on-chip liquid cooling and electrochemical power generation capabilities in three-dimensional multi-processor systems-on-chip (3DMPSoCs). When connected to power delivery networks (PDNs) of chips, the current flowi ...

IEEE2020

A Machine Learning-Based Strategy for Efficient Resource Management of Video Encoding on Heterogeneous MPSoCs

David Atienza Alonso, Marina Zapater Sancho, Arman Iranfar, William Andrew Simon

The design of new streaming systems is becoming a major area of research to deploy services targeted in the Internet-of-Things (IoT) era. In this context, the new High Efficiency Video Coding (HEVC) standard provides high efficiency and scalability of qual ...

2018

Definition Of A Transparent Constraint-Based Modeling And Simulation Layer For The Management Of Complex Systems

Marina Zapater Sancho

Modeling and Simulation (M&S) is one of the most multifaceted topics present today in both industry and academia. However, we are involved in a new M&S paradigm. Systems are becoming more complex and new simulation needs arise and have to be studied. As a ...

IEEE2019

Machine Learning-Based Quality-Aware Power and Thermal Management of Multistream HEVC Encoding on Multicore Servers

David Atienza Alonso, Marina Zapater Sancho, Arman Iranfar

The emergence of video streaming applications, together with the users’ demand for high-resolution contents, has led to the development of new video coding standards, such as High Efficiency Video Coding (HEVC). HEVC provides high efficiency at the cost of ...

2018

3D-ICE 3.0: efficient nonlinear MPSoC thermal simulation with pluggable heat sink models

David Atienza Alonso, Marina Zapater Sancho

The increasing power density in modern high-performance multi-processor system-on-chip (MPSoC) is fueling a revolution in thermal management. On the one hand, thermal phenomena are becoming a critical concern, making accurate and efficient simulation a nec ...

2021

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

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

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

Full System Exploration of On-Chip Wireless Communication on Many-Core Architectures

David Atienza Alonso, Giovanni Ansaloni, Marina Zapater Sancho, Yasir Mahmood Qureshi, Joshua Alexander Harrison Klein, Rafael Medina Morillas

In order to develop sustainable and more powerful information technology (IT) infrastructures, the challenges posed by the "memory wall" are critical for the design of high-performance and high-efficiency many-core computing systems. In this context, recen ...

IEEE2022

Bank on Compute-near-Memory: Design Space Exploration of Processing-near-Bank Architectures

Giovanni Ansaloni, Marina Zapater Sancho, Rafael Medina Morillas

Near-DRAM computing strategies advocate for providing computational capabilities close to where data is stored. Although this paradigm can effectively address the memoryto-processor communication bottleneck, it also presents new challenges: The strict reso ...

Institute of Electrical and Electronics Engineers (IEEE)2024

Memory chip or memory array for wide-voltage range in-memory computing using bitline technology

David Atienza Alonso, Marina Zapater Sancho, Alexandre Sébastien Julien Levisse, Marco Antonio Rios, William Andrew Simon

A random access memory having a memory array having a plurality of local memory groups, each local memory group including a plurality of bitcells arranged in a bitcell column, a pair of local bitlines operatively connected to the plurality of bitcells, a p ...

2021

Multi-Agent Reinforcement Learning for Hyperparameter Optimization of Deep Convolutional Neural Networks

David Atienza Alonso, Marina Zapater Sancho, Arman Iranfar

Nowadays, Deep Convolutional Neural Networks (DCNNs) play a significant role in many application domains, such as, computer vision, medical imaging, and image processing. Nonetheless, designing a DCNN, able to defeat the state of the art, is a manual, chal ...

2021

A Machine Learning-Based Framework for Throughput Estimation of Time-Varying Applications in Multi-Core Servers

David Atienza Alonso, Marina Zapater Sancho, Arman Iranfar

2019

Associativity-agnostic in-cache computing memory architecture optimized for multiplication

David Atienza Alonso, Marina Zapater Sancho, Alexandre Sébastien Julien Levisse, Marco Antonio Rios

A random access memory array including a plurality of local memory group ways, each local memory group way including, a plurality of local memory groups, each local memory group including, a memory column including a plurality of memory cells, a pair of lo ...

2021

Dynamic Thermal Management with Proactive Fan Speed Control Through Reinforcement Learning

David Atienza Alonso, Marina Zapater Sancho, Arman Iranfar, Gabor Andras Csordas

Dynamic Thermal Management (DTM) has become a major challenge since it directly affects Multiprocessors Systems-on-chip (MPSoCs) performance, power consumption, and reliability. In this work, we propose a transient fan model, enabling adaptive fan speed co ...

IEEE2020

HackRF plus GNU Radio: A software-defined radio to teach communication theory

Marina Zapater Sancho, José Luis Ayala Rodrigo

In this paper, an alternative to the traditional methodology related to signal processing-like subjects is proposed. These are subjects that require a deep mathematical and theoretical basis, but the practical goal is not often emphasized, which drives stu ...

SAGE PUBLICATIONS LTD2019

The RECIPE approach to challenges in deeply heterogeneous high performance systems

David Atienza Alonso, Marina Zapater Sancho

RECIPE (REliable power and time-ConstraInts-aware Predictive management of heterogeneous Exascale systems) is a recently started project funded within the H2020 FETHPC programme, which is expressly targeted at exploring new High-Performance Computing (HPC) ...

ELSEVIER2020

Work-in-Progress: A Machine Learning-Based Approach for Power and Thermal Management of Next-Generation Video Coding on MPSoCs

David Atienza Alonso, Marina Zapater Sancho, Arman Iranfar

2017

Blade: An in-Cache Computing Architecture for Edge Devices

David Atienza Alonso, Marina Zapater Sancho, Alexandre Sébastien Julien Levisse, Marco Antonio Rios, William Andrew Simon, Yasir Mahmood Qureshi

Area and power constrained edge devices are increasingly utilized to perform compute intensive workloads, necessitating increasingly area and power efficient accelerators. In this context, in-SRAM computing performs hundreds of parallel operations on spati ...

2020

Reliable Power and Time-Constraints-Aware Predictive Management of Heterogeneous Exascale Systems

David Atienza Alonso, Leila Cammoun, Marina Zapater Sancho, Leila Faiza Ben Hamida Cammoun

ASSOC COMPUTING MACHINERY2018