Leveraging FPGA-Based Design for High-Performance Embedded Computing

Abstract

Field-Programmable Gate Arrays (FPGAs) have become essential in high-performance embedded computing (HPEC), offering advantages like reconfigurability and parallel processing. This article explores how FPGA-based design enhances computational performance in embedded systems. It starts with an overview of FPGA architecture and design considerations, then examines specific applications where FPGAs excel, such as signal processing, machine learning inference, and real-time data analytics. The article also addresses challenges in FPGA implementation, like power consumption and design complexity, and discusses strategies to overcome these issues. Case studies illustrate the effectiveness of FPGA solutions in different HPEC scenarios, showcasing performance benchmarks and comparative analyses. The conclusion reflects on future directions and emerging trends in FPGA-based embedded computing, emphasizing ongoing research and potential advancements.