Hola,
¿eres nuevo aquí?

Regístrate gratis y conecta tu empresa con financiación pública, partners y proyectos.

Tengo cuenta

Regístrate

Ver video

DistOpt-BydWorstCase

Financiado

Cerrado

Distributed Optimization Beyond Worst Case Topologies

Modern systems are increasingly dezentralized and massively distributed computations play a vital role in the systems of the future. This project aims to advance the foundational aspects of distributed computing, particularly Mess... ver más

31/07/2025

ETH Zürich

2M€

Presupuesto del proyecto: 2M€

Líder del proyecto

EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH No se ha especificado una descripción o un objeto social para esta compañía.

Fecha límite participación Sin fecha límite de participación.

Ver 2 Participantes

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2020-08-17

ERC-2020-STG: ERC STARTING GRANTS

I+D

Cerrada hace 5 años

0% 100% 100%

Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

2 Participantes

ETH Zürich

1.54M€ | Lider

BOSTLAN, S.A.

296.05K€ | Participante

Proyectos interesantes

MTM2012-31514

Software

Data Science

62K€ Cerrado

MTM2015-65317-P

Software

Data Science

40K€ Cerrado

TRA2010-21644-C03-02

Software

Data Science

48K€ Cerrado

BES-2013-063659

Software

Data Science

84K€ Cerrado

DistMaP

Software

Data Science

1M€ Cerrado

JDC2023-051006-I

Software

Data Science

72K€ Cerrado

Conecta tu I+D

¿Tienes un proyecto y buscas un partner? Gracias a nuestro motor inteligente podemos recomendarte los mejores socios y ponerte en contacto con ellos. Te lo explicamos en este video

Duración del proyecto: 59 meses Fecha Inicio: 2020-08-17
Fecha Fin: 2025-07-31

Líder del proyecto

EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH No se ha especificado una descripción o un objeto social para esta compañía.

Presupuesto del proyecto 2M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto Modern systems are increasingly dezentralized and massively distributed computations play a vital role in the systems of the future. This project aims to advance the foundational aspects of distributed computing, particularly MessagePassing algorithms for optimization problems. The strong shift towards distributed systems also lead to a flurry of works on such algorithms -- many optimization problems now have distributed algorithms with optimal worst-case performance guarantees. Generally, these guarantees cannot be improved because they match unconditional impossibility results, which prove severe limitations on the performance of distributed algorithms in some (pathological) network topologies. Real world networks, however, are never worst-case and do not share the limiting bottleneck characteristics of these pathological topologies. In fact, there is no known barrier for ultra-fast polylogarithmic-round distributed algorithms on any network of interest. This leaves an exponential gap between current worst-case-optimal algorithms and what is likely possible in many, if not all, real-world settings. Motivated by this, this project provides a program for a general toolbox and theory for MessagePassing optimization algorithms that go beyond worst-case topologies. The main and guiding high-risk high-gain goal is the development of universally optimal distributed algorithms, which are competitive with the best algorithm on any given topology. This would constitute the strongest possible form of algorithmically adjusting to non-worst-case topologies. A detailed program with many concrete and smaller stepping stones towards this ambitious breakthrough objective is provided. Many of the novel questions stemming from this program and proposal are highly interdisciplinary, crossing boundaries between information theory, distributed computing, topological graph theory, and other parts of theoretical computer science, and are fundamental and interesting in their own right.

Conecta tu I+D

Entra hoy

¿Olvidé mi contraseña?

Financiación

Empresas

CTIs/Universidades

Proyectos

Investigadores