Concept

Blackfin

Publications associées (15)

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

David Atienza Alonso, Miguel Peon Quiros, Benoît Walter Denkinger

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 ...

2023

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

Gem5-X : A Many-Core Heterogeneous Simulation Platform for Architectural Exploration and Optimization

David Atienza Alonso, Marina Zapater Sancho, William Andrew Simon, Yasir Mahmood Qureshi

The increasing adoption of smart systems in our daily life has led to the development of new applications with varying performance and energy constraints, and suitable computing architectures need to be developed for these new applications. In this paper, ...

2021

System-level Design of Adaptive Wearable Sensors for Health and Wellness Monitoring

Elisabetta De Giovanni

In recent years, population aging and the consequent higher incidence of noncommunicable diseases, have increased the need for long-term health monitoring. Moreover, as healthcare cost is projected to grow substantially by 2030 in OECD countries, the deman ...

EPFL2021

Survey of Precision-Scalable Multiply-Accumulate Units for Neural-Network Processing

Christian Enz, Vincent Frédéric Camus

The current trend for deep learning has come with an enormous computational need for billions of Multiply-Accumulate (MAC) operations per inference. Fortunately, reduced precision has demonstrated large benefits with low impact on accuracy, paving the way ...

IEEE2019

Perspective on training fully connected networks with resistive memories: Device requirements for multiple conductances of varying significance

Giorgio Cristiano, Massimo Giordano

Novel Deep Neural Network (DNN) accelerators based on crossbar arrays of non-volatile memories (NVMs)-such as Phase-Change Memory or Resistive Memory-can implement multiply-accumulate operations in a highly parallelized fashion. In such systems, computatio ...

2018

Hardware/Software Co-Design of Ultra-Low Power Biomedical Monitors

Ruben Braojos Lopez

Ongoing changes in world demographics and the prevalence of unhealthy lifestyles are imposing a paradigm shift in healthcare delivery. Nowadays, chronic ailments such as cardiovascular diseases, hypertension and diabetes, represent the most common causes o ...

EPFL2016

1kHz 2D silicon retina motion sensor platform

Dario Floreano

This paper proposes an optical motion sensor aimed towards small robotic platforms. It incorporates a 20×20 pixel continuous-time CMOS silicon retina vision sensor with pixels that have local gain control and adapt to background lighting and a DSP microcon ...

IEEE2014

Design of Digital SoC for Operation at High Temperatures

Radisav Cojbasic

There is a growing demand for Systems-on-Chip, integrating microprocessors, on-chip memories, data converters and a variety of sensors, which are capable of reliable operation at high temperatures. For instance, modern aircraft industry demands microcontro ...

EPFL2014

Review and Classification of Gain Cell eDRAM Implementations

Andreas Peter Burg, Adam Shmuel Teman, Pascal Andreas Meinerzhagen

With the increasing requirement of a high-density, high-performance, low power alternative to traditional SRAM, Gain Cell (GC) embedded DRAMs have gained a renewed interest in recent years. Several industrial and academic publications have presented GC mem ...

2012

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