EVEREST: A design environment for extreme-scale big data analytics on heterogeneous platforms

@article{Pilato2021EVERESTAD,
  title={EVEREST: A design environment for extreme-scale big data analytics on heterogeneous platforms},
  author={C. Pilato and S. Bohm and F. Brocheton and Jer{\'o}nimo Castrill{\'o}n and Riccardo Cevasco and V. Cima and R. Cmar and D. Diamantopoulos and Fabrizio Ferrandi and J. Martinovic and G. Palermo and Michele Paolino and A. Parodi and Lorenzo Pittaluga and Daniel Raho and F. Regazzoni and K. Slaninov{\'a} and C. Hagleitner},
  journal={2021 Design, Automation \& Test in Europe Conference \& Exhibition (DATE)},
  year={2021},
  pages={1320-1325}
}
  • C. Pilato, S. Bohm, +15 authors C. Hagleitner
  • Published 2021
  • Computer Science
  • 2021 Design, Automation & Test in Europe Conference & Exhibition (DATE)
High-Performance Big Data Analytics (HPDA) applications are characterized by huge volumes of distributed and heterogeneous data that require efficient computation for knowledge extraction and decision making. Designers are moving towards a tight integration of computing systems combining HPC, Cloud, and IoT solutions with artificial intelligence (AI). Matching the application and data requirements with the characteristics of the underlying hardware is a key element to improve the predictions… Expand

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