Managing energy consumption in FPGA-based edge computing systems with soft-core CPUs
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Abstract
Edge computing, characterized by processing data closer to its source, has emerged as a promising paradigm to address the challenges of latency, bandwidth, and privacy in the Internet of Things (IoT) era. At the same time, Field-Programmable
Gate Arrays (FPGAs) have gained significant attention in edge computing due to their ability to reconfigure design, low power consumption, and high performance. However, the energy consumption of FPGA-based edge computing systems remains a critical concern, particularly in resource-constrained environments where power efficiency is crucial. This paper presents an energy-efficient edge computing system focusing on job scheduling and power management optimization. We review existing techniques and methodologies for optimizing energy consumption in computing systems, including FPGA-based edge devices, identify key challenges and opportunities for future enhancement and propose a flexible, low-power system design with soft-core CPUs.
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This work is licensed under a Creative Commons Attribution 4.0 International License.
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Accepted 2025-02-27
Published 2025-05-21
References
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