Publication

Structured and tiled-based pruning of Deep Learning models targeting FPGA implementations

Publications associées (38)

Performance Characterization of HTAP Workloads

Anastasia Ailamaki, Sandhya Dwarkadas, Utku Sirin

Hybrid Transactional and Analytical Processing (HTAP) systems have become popular in the past decade. HTAP systems allow running transactional and analytical processing workloads on the same data and hardware. As a result, they suffer from workload interfe ...

IEEE COMPUTER SOC2021

Image Compression and Quality Assessment using Convolutional Neural Networks

Pinar Akyazi

The rapid development of digital imaging and video has placed visual contents in the heart of our lives. Digital multimedia span a vast number of areas from business to leisure, including but not limited to education, medicine, accessibility, training, adv ...

EPFL2020

Multi-Objective Management of Multiprocessor Systems: From Heuristics to Reinforcement Learning

Arman Iranfar

In my thesis, I reveal several already-existing and emerging challenges in multi-objective management of multiprocessor systems, and address them through novel solutions, from heuristics to RL, depending on the complexity of the problem. Conventional multi ...

EPFL2020

(Geometry Aware) Deep Learning-based Omnidirectional Image Compression

Yamin Sepehri

Omnidirectional images are the spherical visual signals that provide a wide, 360◦, view of a scene from a specific position. Such images are becoming increasingly popular in fields like virtual reality and robotics. Compared to conventional 2D images, the ...

2020

Towards Continuous and Ambulatory Blood Pressure Monitoring: Methods for Efficient Data Acquisition for Pulse Transit Time Estimation

Lara Orlandic

We developed a prototype for measuring physiological data for pulse transit time (PTT) estimation that will be used for ambulatory blood pressure (BP) monitoring. The device is comprised of an embedded system with multimodal sensors that streams high-throu ...

2020

A Standalone FPGA-Based Miner for Lyra2REv2 Cryptocurrencies

Alexios Konstantinos Balatsoukas Stimming, Pascal Giard, Michiel Van Beirendonck

Lyra2REv2 is a hashing algorithm that consists of a chain of individual hashing algorithms, and it is used as a proof-of-work function in several cryptocurrencies. The most crucial and exotic hashing algorithm in the Lyra2REv2 chain is a specific instance ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Graph-based image representation learning

Renata Khasanova

Though deep learning (DL) algorithms are very powerful for image processing tasks, they generally require a lot of data to reach their full potential. Furthermore, there is no straightforward way to impose various properties, given by the prior knowledge a ...

EPFL2019

Lossy compression of quality scores in differential gene expression: A first assessment and impact analysis

Ana Angelica Hernandez Lopez

High-throughput sequencing of RNA molecules has enabled the quantitative analysis of gene expression at the expense of storage space and processing power. To alleviate these prob- lems, lossy compression methods of the quality scores associated to RNA sequ ...

2018

DCT Learning-Based Hardware Design for Neural Signal Acquisition Systems

Volkan Cevher, Cosimo Aprile, Yusuf Leblebici, Luca Baldassarre

This work presents an area and power efficient encoding system for wireless implantable devices capable of monitoring the electrical activity of the brain. Such devices are becoming an important tool for understanding, real-time monitoring, and potentially ...

2017

Fully Quantized Distributed Gradient Descent

n major distributed optimization system, the main bottleneck is often the communication between the different machines. To reduce the time dedicated to communications, some heuristics have been developed to reduce the precision of the messages sent and hav ...

2017

Graph Chatbot

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Connectez-vous pour utiliser Chat avec Graph Search