ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2302.07946
  4. Cited By
Experimenting with Emerging RISC-V Systems for Decentralised Machine
  Learning

Experimenting with Emerging RISC-V Systems for Decentralised Machine Learning

15 February 2023
Gianluca Mittone
Nicolò Tonci
Robert Birke
Iacopo Colonnelli
Doriana Medić
Andrea Bartolini
Roberto Esposito
Emanuele Parisi
Francesco Beneventi
Mirko Polato
Massimo Torquati
Luca Benini
Marco Aldinucci
ArXivPDFHTML

Papers citing "Experimenting with Emerging RISC-V Systems for Decentralised Machine Learning"

4 / 4 papers shown
Title
Exploring energy consumption of AI frameworks on a 64-core RV64 Server CPU
Exploring energy consumption of AI frameworks on a 64-core RV64 Server CPU
Giulio Malenza
Francesco Targa
Adriano Marques Garcia
Marco Aldinucci
Robert Birke
27
0
0
03 Apr 2025
Correct orchestration of Federated Learning generic algorithms:
  formalisation and verification in CSP
Correct orchestration of Federated Learning generic algorithms: formalisation and verification in CSP
Ivan Prokić
S. Ghilezan
Simona Kasterovic
M. Popovic
M. Popovic
I. Kastelan
FedML
28
3
0
26 Jun 2023
Fedstellar: A Platform for Decentralized Federated Learning
Fedstellar: A Platform for Decentralized Federated Learning
Enrique Tomás Martínez Beltrán
Á. Gómez
Chao Feng
Pedro Miguel Sánchez Sánchez
Sergio López Bernal
Gérome Bovet
M. Pérez
Gregorio Martínez Pérez
Alberto Huertas Celdrán
FedML
18
40
0
16 Jun 2023
FedML: A Research Library and Benchmark for Federated Machine Learning
FedML: A Research Library and Benchmark for Federated Machine Learning
Chaoyang He
Songze Li
Jinhyun So
Xiao Zeng
Mi Zhang
...
Yang Liu
Ramesh Raskar
Qiang Yang
M. Annavaram
Salman Avestimehr
FedML
168
564
0
27 Jul 2020
1