Publication

Greedy Scheduling for Distributed Computing Clusters

Publications associées (29)

2D Nanosystems: Applications of 2D Semiconductors for In-Memory Computing

Machine learning and data processing algorithms have been thriving in finding ways of processing and classifying information by exploiting the hidden trends of large datasets. Although these emerging computational methods have become successful in today's ...

EPFL2023

REMOTE: Re-thinking Task Mapping on Wireless 2.5D Systems-on-Package for Hotspot Removal

David Atienza Alonso, Giovanni Ansaloni, Marina Zapater Sancho, Darong Huang, Rafael Medina Morillas

2.5D Systems-on-Package (SoPs) are composed by several chiplets placed on an interposer. They are becoming increasingly popular as they enable easy integration of electronic components in the same package and high fabrication yields. Nevertheless, they int ...

2023

Post-Moore's Law Fusion: High-Bandwidth Memory, Accelerators, and Native Half-Precision Processing for CPU-Local Analytics

Anastasia Ailamaki, Viktor Sanca

Modern data management systems aim to provide both cutting-edge functionality and hardware efficiency. With the advent of AI-driven data processing and the post-Moore Law era, traditional memory-bound scale-up data management operations face scalability ch ...

2023

Reliable Microsecond-Scale Distributed Computing

Athanasios Xygkis

The landscape of computing is changing, thanks to the advent of modern networking equipment that allows machines to exchange information in as little as one microsecond. Such advancement has enabled microsecond-scale distributed computing, where entire dis ...

EPFL2023

Equivariant Neural Architectures for Representing and Generating Graphs

Clément Arthur Yvon Vignac

Graph machine learning offers a powerful framework with natural applications in scientific fields such as chemistry, biology and material sciences. By representing data as a graph, we encode the prior knowledge that the data is composed of a set of entiti ...

EPFL2023

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

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

David Atienza Alonso, Benoît Walter Denkinger, Miguel Peon Quiros

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

Design Space Exploration for Partitioning Dataflow Program on CPU-GPU Heterogeneous System

Marco Mattavelli, Simone Casale Brunet, Aurélien François Gilbert Bloch

Dataflow programming is a methodology that enables the development of high-level, parametric programs that are independent of the underlying platform. This approach is particularly useful for heterogeneous platforms, as it eliminates the need to rewrite ap ...

SPRINGER2023

Removing Algorithmic Discrimination (With Minimal Individual Error)

Rachid Guerraoui, El Mahdi El Mhamdi, Le Nguyen Hoang, Alexandre David Olivier Maurer

We address for the first time the problem of correcting group discriminations within a score function, while minimizing the individual error. Each group is described by a probability density function on the set of profiles. We first solve the problem analy ...

2022