Publications associées à ARM (entreprise)

X-HEEP: An Open-Source, Configurable and Extendible RISC-V Microcontroller

David Atienza Alonso, Miguel Peon Quiros, José Angel Miranda Calero, Simone Machetti, Pasquale Davide Schiavone, Thomas Christoph Müller, Rubén Rodríguez Álvarez, Benoît Walter Denkinger, Ruben Rodriguez, Saverio Nasturzio

In this work, we present eXtendible Heterogeneous Energy-Efficient Platform (X-HEEP), a configurable and extendible single-core RISC-V-based ultra-low-power microcontroller. X-HEEP can be used standalone as a low-cost microcontroller, or it can be integrat ...

New York2023

Exploring brain-inspired multi-core heterogeneous hardware templates for low-power biomedical embedded systems

Benoît Walter Denkinger

The miniaturization of integrated circuits (ICs) and their higher performance and energy efficiency, combined with new machine learning algorithms and applications, have paved the way to intelligent, interconnected edge devices. In the medical domain, they ...

EPFL2023

Instruction-Level Power Side-Channel Leakage Evaluation of Soft-Core CPUs on Shared FPGAs

Mathias Josef Payer, Mirjana Stojilovic, Shashwat Shrivastava, Ognjen Glamocanin, Jinwei Yao, Nour Ardo

Side-channel disassembly attacks recover CPU instructions from power or electromagnetic side-channel traces measured during code execution. These attacks typically rely on physical access, proximity to the victim device, and high sampling rate measuring in ...

2023

Dynamic SIMD Parallel Execution on GPU from High-Level Dataflow Synthesis

Marco Mattavelli, Simone Casale Brunet, Aurélien François Gilbert Bloch

Developing and fine-tuning software programs for heterogeneous hardware such as CPU/GPU processing platforms comprise a highly complex endeavor that demands considerable time and effort of software engineers and requires evaluating various fundamental comp ...

MDPI2022

A Deep-Learning Approach to Side-Channel Based CPU Disassembly at Design Time

Mirjana Stojilovic

Side-channel CPU disassembly is a side-channel attack that allows an adversary to recover instructions executed by a processor. Not only does such an attack compromise code confidentiality, it can also reveal critical information on the system’s internals. ...

IEEE2022

Genome Sequence Alignment - Design Space Exploration for Optimal Performance and Energy Architectures

David Atienza Alonso, Marina Zapater Sancho, Yasir Mahmood Qureshi, José Manuel Herruzo Ruiz

Next generation workloads, such as genome sequencing, have an astounding impact in the healthcare sector. Sequence alignment, the first step in genome sequencing, has experienced recent breakthroughs, which resulted in next generation sequencing (NGS). As ...

2020

Real-Time Personalized Atrial Fibrillation Prediction on Multi-Core Wearable Sensors

David Atienza Alonso, Amir Aminifar, Miguel Peon Quiros, Adriana Arza Valdes, Elisabetta De Giovanni

In the recent Internet-of-Things (IoT) era where biomedical applications require continuous monitoring of relevant data, edge computing keeps gaining more and more importance. These new architectures for edge computing include multi-core and parallel compu ...

2021

AiiDA 1.0, a scalable computational infrastructure for automated reproducible workflows and data provenance

Nicola Marzari, Giovanni Pizzi, Nicolas Frank Mounet, Martin Uhrin, Andrea Cepellotti, Boris Kozinsky, Fernando Gargiulo, Christoph Leopold Talirz, Leonid Kahle, Aliaksandr Yakutovich

The ever-growing availability of computing power and the sustained development of advanced computational methods have contributed much to recent scientific progress. These developments present new challenges driven by the sheer amount of calculations and d ...

2020

High Performance Computing for gravitational lens modeling: Single vs double precision on GPUs and CPUs

Jean-Paul Richard Kneib, Markus Rexroth, Christoph Ernst René Schäfer

Strong gravitational lensing is a powerful probe of cosmology and the dark matter distribution. Efficient lensing software is already a necessity to fully use its potential and the performance demands will only increase with the upcoming generation of tele ...

ELSEVIER2020

Methods for strong gravitational lens detection and analysis using machine learning and high performance computing

Christoph Ernst René Schäfer

The study of strong gravitational lenses is a relatively new scientific field in astronomy with many applications in cosmology. Its unique observables allow astronomers to trace dark matter, determine the expansion of the universe and study galaxy evolutio ...

EPFL2020