A System Development Kit for Big Data Applications on FPGA-based Clusters: The EVEREST Approach
Abstract
Modern big data workflows are characterized by computationally intensive kernels. The simulated results are often combined with knowledge extracted from AI models to ultimately support decision-making. These energy-hungry workflows are increasingly executed in data centers with energy-efficient hardware accelerators since FPGAs are well-suited for this task due to their inherent parallelism. We present the H2020 project EVEREST, which has developed a system development kit (SDK) to simplify the creation of FPGA-accelerated kernels and manage the execution at runtime through a virtualization environment. This paper describes the main components of the EVEREST SDK and the benefits that can be achieved in our use cases.
Cite
@article{arxiv.2402.12612,
title = {A System Development Kit for Big Data Applications on FPGA-based Clusters: The EVEREST Approach},
author = {Christian Pilato and Subhadeep Banik and Jakub Beranek and Fabien Brocheton and Jeronimo Castrillon and Riccardo Cevasco and Radim Cmar and Serena Curzel and Fabrizio Ferrandi and Karl F. A. Friebel and Antonella Galizia and Matteo Grasso and Paulo Silva and Jan Martinovic and Gianluca Palermo and Michele Paolino and Andrea Parodi and Antonio Parodi and Fabio Pintus and Raphael Polig and David Poulet and Francesco Regazzoni and Burkhard Ringlein and Roberto Rocco and Katerina Slaninova and Tom Slooff and Stephanie Soldavini and Felix Suchert and Mattia Tibaldi and Beat Weiss and Christoph Hagleitner},
journal= {arXiv preprint arXiv:2402.12612},
year = {2024}
}
Comments
Accepted for presentation at DATE 2024 (multi-partner project session)