David Atienza Alonso

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Several techniques have been recently proposed to adapt Big-Data streaming applications to existing many core platforms. Among these techniques, online reinforcement learning methods have been proposed that learn how to adapt at run-time the throughput and ...

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 ...

While possessing the potential to replace conventional air-cooled heat sinks, inter-tier microchannel liquid cooling of 3D ICs also creates the problem of increased thermal gradients from the fluid inlet to outlet ports [1, 2]. These cooling-induced therma ...

Coarse-Grained Reconfigurable Arrays (CGRAs) are a programmable architectural solution that efficiently supports the execution of computation-intensive application functions (kernels). Compilers for CGRAs typically focus on optimizing the mapping of single ...

We consider the problem of energy-efficient on-line scheduling for slice-parallel video decoders on multicore systems. We assume that each of the processors are Dynamic Voltage Frequency Scaling (DVFS) enabled such that they can independently trade off per ...

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 ...

The increasing complexity of transformer models in artificial intelligence expands their computational costs, memory usage, and energy consumption. Hardware acceleration tackles the ensuing challenges by designing processors and accelerators tailored for t ...

Thermal management is a critical challenge in the design of high performance multi-processor system-on-chips (MPSoCs). Therefore, accurate and fast thermal modeling tools are necessary for efficiently analyzing the thermal profiles of MPSoCs. This paper ad ...

Epilepsy, a major neurological disease, requires careful diagnosis and treatment. However, the detection of epileptic seizures remains a significant challenge. Current clinical practice relies on expert analysis of EEG signals, a process that is time-consu ...

Today, epilepsy is one of the most common chronic diseases affecting more than 65 million people worldwide and is ranked number four after migraine, Alzheimer’s disease, and stroke. Despite the recent advances in anti-epileptic drugs, one-third of the epil ...

Obstructive Sleep Apnea (OSA) is one of the main under-diagnosed sleep disorder. It is an aggravating factor for several serious cardiovascular diseases, including stroke. There is, however, a lack of medical devices for long-term ambulatory monitoring of ...

Embedded systems confront two opposite goals: low-power operation and high performance. The current trend to reach these goals is toward heterogeneous platforms, including multi-core architectures with heterogeneous cores and hardware accelerators. The lat ...

Background and Objective: Event-based analog-to-digital converters allow for sparse bio-signal acquisition, enabling local sub-Nyquist sampling frequency. However, aggressive event selection can cause the loss of important bio-markers, not recoverable with ...

3D stacked chips have become a promising integration technology for modern systems. The complexity reached in multi-processor systems has increased the communication delays between processing cores, and an effective way to diminish this impact on communica ...

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- ...

Nowadays, multi-core Systems-on-Chip (SoCs) are typically required to execute multiple complex applications, which demand a large set of heterogeneous hardware cores with different sizes. In this context, the popularity of dynamically reconfigurable platfo ...

A multi-core architecture with ultra-low power consumption is needed for a wide variety of applications, especially in the bio-medical domain. In this patent, an ultra-low power multi-core architecture is presented: it is composed of one or more cores, sev ...

With the emergence of wearable and non-intrusive med- ical devices, one major challenge is the real-time analysis of the acquired signals in real-life and ambulatory con- ditions. This paper presents a lightweight algorithm for on-line heart beat classific ...

Three-dimensional (3D) stacking is an attractive method for designing large manycore chips as it provides high transistor integration densities, improves manufacturing yield due to smaller chip area, reduces wirelength and capacitance, and enables heteroge ...

Due to stringent energy and performance constraints, edge AI computing often employs heterogeneous systems that utilize both general-purpose CPUs and accelerators. Analog in-memory computing (AIMC) is a well-known AI inference solution that overcomes compu ...

David Atienza Alonso

Chat with Graph Search

Big-Data Streaming Applications Scheduling Based on Staged Multi-armed Bandits

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

Thermal Balancing of Liquid-Cooled 3D-MPSoCs Using Channel Modulation

An MLIR-based Compilation Framework for CGRA Application Deployment

Markov Decision Process Based Energy-Efficient On-Line Scheduling for Slice Parallel Video Decoders on Multicore Systems

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

Accelerator-driven Data Arrangement to Minimize Transformers Run-time on Multi-core Architectures

Optimal Multi-Processor SoC Thermal Simulation via Adaptive Differential Equation Solvers

Resource-Efficient Continual Learning for Personalized Online Seizure Detection

e-Glass: A Wearable System for Real-Time Detection of Epileptic Seizures

Online Obstructive Sleep Apnea Detection on Medical Wearable Sensors

Acceleration of Control Intensive Applications on Coarse-Grained Reconfigurable Arrays for Embedded Systems

Event-based sampled ECG morphology reconstruction through self-similarity

Through Silicon Via-Based Grid for Thermal Control in 3D Chips

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

A Mapping Flow for Dynamically Reconfigurable Multi-Core System-on-Chip Design

Ultra-Low Power Multicore Architecture For Parallel Biomedical Signal Processing

Real-Time Probabilistic Heart Beat Classification and Correction for Embedded Systems

Attaining Single-Chip, High-Performance Computing Through 3D Systems with Active Cooling

Which Coupled is Best Coupled? An Exploration of AIMC Tile Interfaces and Load Balancing for CNNs