Distributed Accelerator Utilization
Distributed Accelerator Utilization is a systematic framework that optimizes the allocation, coordination, and efficiency of heterogeneous hardware accelerators across geographically separated nodes in a distributed computing environment by enabling adaptive workload distribution, resource virtualization, and cross-node communication transparency.
6
Publications
95
Citations
28
Authors
5
Institutions
Publications per year
2017–2026
3
6
Pathways: Asynchronous Distributed Dataflow for ML
Paul Barham, Aakanksha Chowdhery, Jeff Dean et al. · arXiv (Cornell University) · 2022 · 37 citations · Full text
S. Pardi, Guglielmo De Nardo, G. Russo · Nuclear and Particle Physics Proceedings · 2016 · 11 citations · Full text
Computing, Computer Science, Physics +16
On-line machine learning accelerator on digital RRAM-crossbar
Leibin Ni, Hantao Huang, Hao Yu · 2016 · 11 citations
1–5 of 6
28
1 publications · 15 citations
1
h-index
1
h-index
1
h-index
1
h-index
Laboratoire de Physique des 2 Infinis Irène Joliot-Curie, France
1 publications · 11 citations
1
h-index
1–5 of 28
5
Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas
Madrid, Spain
1 h-index
1 publications
10 citations
Istituto Nazionale di Fisica Nucleare, Sezione di Napoli
Naples, Italy
1 h-index
3 publications
33 citations

University of Naples Federico II
Naples, Italy
1 h-index
2 publications
22 citations
Port d'Informació Científica
Barcelona, Spain
1 h-index
1 publications
10 citations
Nanyang Technological University
Singapore, Singapore
1 h-index
3 publications
33 citations
1–5 of 5
Repository · 2 publications · 52 citations
2
h-index
1 publications · 11 citations
1
h-index
1 publications · 10 citations
1
h-index
Repository · 1 publications · 11 citations
1
h-index
1–4