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Design and Implementation of 64-bit SRAM and CAM on Cadence and Open-source environment
Author(s) -
N. Shylashree,
Yatish D. Vahvale,
N. Praveena,
A. S. Mamatha
Publication year - 2021
Publication title -
international journal of circuits, systems and signal processing
Language(s) - English
Resource type - Journals
ISSN - 1998-4464
DOI - 10.46300/9106.2021.15.65
Subject(s) - cadence , static random access memory , embedded system , computer science , computer hardware , design flow , computer architecture , engineering , electronic engineering
Low-power IC design has become a priority in recent years because of the growing proliferation of portable battery-operated devices, bringing Static Random-Access Memory (SRAM) and Content Addressable Memory (CAM) into play. In today's SoCs, embedded SRAM units have become a necessary component. There is a lack of chips in the current world and to manufacture chips there is the requirement of Electronic Design Automation(EDA) tools that can perform better. In this paper, the main motive is to showcase the performance of open-source tools available currently which can still generate the required output with no cost. In this new era of fast mobile computing, traditional SRAM cell designs are power-demanding and underperforming. Rather than lowering manufacturing costs through high-volume production, specialty memory give cost-effective alternatives through architecture. Specialty memory devices enable the designer to address issues like board area, important timing, data flow bottlenecks, and so on in ways that high-volume regular memory devices cannot. Implementation of memory devices on Cadence environment and open-source environment to check the compatibility and compare the power, area, and delay of both 64-bit SRAM and CAM also analysing and validating the results of both the memory devices in this paper. For SRAM in a cadence environment, the calculated power, area, and slack have improved values, namely 0.145mW, 1104.3um2, and positive slack of 6636. Furthermore, the power for 64-bit CAM in a cadence context is nearly identical to those for an open-source environment ~0.8mW. In an open-source environment, the calculated slack for CAM is 4.74.

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