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.Comment: Accepted for presentation at DATE 2024 (multi-partner project
session