A System Development Kit for Big Data Applications on FPGA-based Clusters: The EVEREST Approach
/ Authors
Christian Pilato, S. Banik, Jakub Beránek, F. Brocheton, J. Castrillón, Riccardo Cevasco, R. Cmar, S. Curzel, Fabrizio Ferrandi, Karl F. A. Friebel
and 21 more authors
A. Galizia, M. Grasso, Paulo Silva, Jan Martinovic, Gianluca Palermo, Michele Paolino, Antonio Parodi, Antonio Parodi, F. Pintus, R. Polig, D. Poulet, F. Regazzoni, Burkhard Ringlein, Roberto Rocco, K. Slaninová, T. Slooff, Stephanie Soldavini, Felix Suchert, Mattia Tibaldi, B. Weiss, Christoph Hagleitner
/ 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 hard-ware accelerators since FPG As 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.
Journal: 2024 Design, Automation & Test in Europe Conference & Exhibition (DATE)