The Power of Computing in Memory for Searching Algorithm

This work focuses on the critical problem of search algorithm optimization to improve efficiency in a variety of applications within the field of computing. Through the utilization of technology's ongoing advancements, namely in the area of hardware acceleration, the research delves into different approaches meant to improve search algorithm performance. It presents a methodical comparison between the hardware-based BiCAM-based search algorithm and conventional software-based search algorithms like Sequential and Binary. The Field-Programmable Gate Array (FPGA), selected for its unmatched adaptability in hardware configurations, is used for implementation. By means of a thorough analysis, the study aims to identify the advantages, disadvantages, and complexity of these algorithms. The overall objective is to contribute to the continuing conversation in computer engineering and digital circuit design by providing nuanced insights into algorithm choices that are suited to particular application objectives. Essentially, the study explores the conditions of different FPGA-based search algorithms, offering a thorough comprehension to direct well-informed decisions for the best results in a range of applications. From the obtained results, it is evident that the BiCAM consumes more power and utilizes more resources but excels in terms of time complexity, making it a favorable trade-off in certain applications where speed is of greater importance.