Advanced Memory Controller Architecture for Enhancing Computational SRAM Efficiency

Static random access memory plays a critical role in modern computing architecture due to its superior speed and low latency. Design and implementation of advanced memory controller architecture for enhancing the efficiency of Computational SRAM using pipelining technique,this mainly describes the importance of the memory architecture within a system to improve the overall performances. By enabling computation within the memory itself and lowering the overhead associated with data movement, in-memory computing (IMC) seeks to close the performance gap between processors and memory. Existing designs, however have issues with data locality management, power consumption, and memory access. In order to increase the efficiency of IMC systems, this study proposes a pipelined Data Management Unit (DMU) coupled with Computational SRAM (C-SRAM). By utilizing pipelining techniques, the suggested architecture minimizes latency and power consumption while optimizing computation and data transfer concurrently in comparison to traditional memory architectures. The suggested method is a potential strategy for energy-efficient IMC systems since it shows notable advantages over current memory controllers.

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Published
2025-05-23
DOI
https://doi.org/10.1109/iccc64910.2025.11077353
Primary Topic
Advanced Memory and Neural Computing
Type
article
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article

Advanced Memory Controller Architecture for Enhancing Computational SRAM Efficiency

O P Amritha, H S Gopika, E Resmi
Advanced Memory and Neural Computing
article

Advanced Memory Controller Architecture for Enhancing Computational SRAM Efficiency

O P Amritha, H S Gopika, E Resmi
article en

Abstract

Static random access memory plays a critical role in modern computing architecture due to its superior speed and low latency. Design and implementation of advanced memory controller architecture for enhancing the efficiency of Computational SRAM using pipelining technique,this mainly describes the importance of the memory architecture within a system to improve the overall performances. By enabling computation within the memory itself and lowering the overhead associated with data movement, in-memory computing (IMC) seeks to close the performance gap between processors and memory. Existing designs, however have issues with data locality management, power consumption, and memory access. In order to increase the efficiency of IMC systems, this study proposes a pipelined Data Management Unit (DMU) coupled with Computational SRAM (C-SRAM). By utilizing pipelining techniques, the suggested architecture minimizes latency and power consumption while optimizing computation and data transfer concurrently in comparison to traditional memory architectures. The suggested method is a potential strategy for energy-efficient IMC systems since it shows notable advantages over current memory controllers.

University of Kerala (IN), APJ Abdul Kalam Technological University (IN)
Affordable and clean energy
Openalex Percentile: Top 82%
Advanced Memory and Neural Computing
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Advanced Memory Controller Architecture for Enhancing Computational SRAM Efficiency — O P Amritha, H S Gopika, et al. · (2025) | TGRS Research Map | TGRS