A System Development Kit for Big Data Applications on FPGA-based Clusters: The EVEREST Approach
<|reference_start|>A System Development Kit for Big Data Applications on FPGA-based Clusters: The EVEREST Approach: 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.<|reference_end|>
@article{pilato2024a,
    title={A System Development Kit for Big Data Applications on FPGA-based
  Clusters: The EVEREST Approach},
    author={Christian Pilato, Subhadeep Banik, Jakub Beranek, Fabien Brocheton,
  Jeronimo Castrillon, Riccardo Cevasco, Radim Cmar, Serena Curzel, Fabrizio
  Ferrandi, Karl F. A. Friebel, Antonella Galizia, Matteo Grasso, Paulo Silva,
  Jan Martinovic, Gianluca Palermo, Michele Paolino, Andrea Parodi, Antonio
  Parodi, Fabio Pintus, Raphael Polig, David Poulet, Francesco Regazzoni,
  Burkhard Ringlein, Roberto Rocco, Katerina Slaninova, Tom Slooff, Stephanie
  Soldavini, Felix Suchert, Mattia Tibaldi, Beat Weiss, Christoph Hagleitner},
    journal={arXiv preprint arXiv:2402.12612},
    year={2024},
    archivePrefix={arXiv},
    eprint={2402.12612},
    primaryClass={cs.AR}
}