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APJ Abdul Kalam Technological University , Kerala , India
APJ Abdul Kalam Technological University , Kerala , India
The research environment is promptly looking at the extensive development of memristor devices in industrial applications. Future technology is eagerly waiting for the upcoming developments in memristor-based devices. Memristor regulates the current flow in devices and the amount of previously flowed charges, which are stored as memory in applications. Any electronics design that employs computational technologies uses semiconductor memory. However, reading certain bits from the memory cell is time-consuming, while the same in the CMOS Content-Addressable Memories (CAM) zone is efficient. To overcome these limitations, a CMOS-Memristor Associative Memory Cell (MemCAM) is proposed, which is a multibit cell and merges the advantages of both memristor and CMOS logic. In Content Addressable Memory, the memories are not organized in chronological order and are associative. Non-volatile memory devices are getting popular in the era because of the developments in technology. Memristor memory devices acquired comparable features with existing memories like SRAM and DRAM, such as durability, consistency, and power compatibility with CMOS logic. Because each of the aforesaid memory devices has limitations, MEMCAM, a hybrid memory device, is used for improved data searching performance and reliability, as well as faster approaches. The integration of a FinFET-based circuit into the MemCAM structure enhances the efficiency and processing speed in various applications. This technique aims at the optimization of power dissipation with a tradeoff on area and analysis of characteristics like power consumption and delay, Noise Margin, and Frequency response. By combining the high-speed search capabilities of CMOS CAM with the low-power advantages of memristors and FinFET technology, this proposed system aims to develop hybrid memory architectures for next-generation computing systems, including artificial intelligence, machine learning, and high-performance processors.
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