On Exploiting Patterns For Robust FPGA-based Multi-accelerator Edge Computing Systems
Seyyed Ahmad Razavi, Hsin-Yu Ting, Tootiya Giyahchi, Eli Bozorgzadeh · 2022
Edge computing plays a key role in providing ser-vices for emerging compute-intensive applications while bringing computation close to end devices. FPGAs have been deployed to provide custom acceleration services due to their reconfigurability and support for multi-tenancy in sharing the computing resource. This paper explores an FPGA-based Multi-Accelerator Edge Computing System, that serves various DNN applications from multiple end devices simultaneously. To dynamically maximize the responsiveness to end devices, we propose a system framework that exploits the characteristic of applications in patterns and employs a staggering module coupled with a mixed offline/online multi-queue scheduling method to alleviate resource contention, and uncertain delay caused by network delay variation. Our evaluation shows the framework can significantly improve responsiveness and robustness in serving multiple end devices.