Augmented Memory Computing: Dynamically Augmented SRAM Storage for Data Intensive Applications
Haripriya Sheshadri, Shwetha Vijayakumar, Ajey Jacob, Akhilesh Jaiswal

TL;DR
This paper introduces a novel SRAM-based memory scheme that dynamically increases storage capacity by operating cells in augmented modes, enabling multi-bit storage and enhancing data-intensive application performance.
Contribution
It proposes new SRAM cell designs capable of storing multiple bits dynamically, significantly increasing on-chip memory capacity and integrating seamlessly with in-memory computing.
Findings
Feasibility demonstrated through extensive 22nm simulations.
Dual-bit 8T SRAM cell stores static and dynamic data simultaneously.
Ternary 7T SRAM cell operates in augmented mode for three-level data storage.
Abstract
In this paper, we propose a novel memory-centric scheme based on CMOS SRAM for acceleration of data intensive applications. Our proposal aims at dynamically increasing the on-chip memory storage capacity of SRAM arrays on-demand. The proposed scheme called - Augmented Memory Computing allows an SRAM cell to operate in two different modes 1) the Normal mode and 2) the Augmented mode. In the Normal mode of operation, the SRAM cell functions like a standard 6 transistor (6T) SRAM cell, storing one bit of data in static format. While in the Augmented mode, each SRAM cell can store >1 bit of data (in a dynamic fashion). Specifically, we propose two novel SRAM cells - an 8 transistor (8T) dual bit storage augmented cell and a 7 transistor (7T) ternary bit storage augmented cell. The proposed 8T dual bit SRAM cell when operated in the Augmented mode, can store a static bit of data while also,…
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Taxonomy
TopicsAdvanced Memory and Neural Computing · Phase-change materials and chalcogenides · Parallel Computing and Optimization Techniques
