Advancements in FPGA-Based Design and Applications
DOI:
https://doi.org/10.56472/ICCSAIML25-169Keywords:
Field-Programmable Gate Arrays (FPGAs), FPGA architectures, High-Level Synthesis (HLS), machine learning acceleration, embedded processors, Digital Signal Processing (DSP), power consumption, design considerations, future directionsAbstract
Field-Programmable Gate Arrays (FPGAs) have evolved significantly, offering customizable hardware solutions that cater to a wide array of applications. This paper provides a comprehensive overview of recent advancements in FPGA-based design and their diverse applications. We explore the evolution of FPGA architectures, highlighting the integration of embedded processors, Digital Signal Processing (DSP) blocks, and high-speed interfaces that have expanded their capabilities. The shift towards High-Level Synthesis (HLS) tools has further enhanced design productivity by enabling designers to work with high-level languages such as C/C++. Additionally, we delve into the role of FPGAs in accelerating machine learning tasks, particularly in domains like autonomous driving and healthcare, emphasizing their high parallelism and low latency. The paper also addresses design considerations, including resource utilization, power consumption, and the challenges associated with balancing adaptability and performance. Finally, we discuss future directions, emphasizing the need for ongoing research to overcome existing challenges and fully harness the potential of FPGA-based systems
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