8T SRAM Cell as a Multi-bit Dot Product Engine for Beyond von-Neumann Computing
Akhilesh Jaiswal, Indranil Chakraborty, Amogh Agrawal, Kaushik Roy

TL;DR
This paper demonstrates how standard 8T SRAM arrays can be configured to perform multi-bit analog-like dot product computations, offering a potential solution to the von-Neumann bottleneck without modifying existing SRAM structures.
Contribution
The authors propose two configurations to enable multi-bit dot product operations in standard 8T SRAM arrays without altering the cell design.
Findings
Enables analog-like dot product computation using standard SRAM arrays.
Preserves standard SRAM read-write functionality while acting as a dot product accelerator.
Provides a practical approach to in-memory computing with existing memory technology.
Abstract
Large scale digital computing almost exclusively relies on the von-Neumann architecture which comprises of separate units for storage and computations. The energy expensive transfer of data from the memory units to the computing cores results in the well-known von-Neumann bottleneck. Various approaches aimed towards bypassing the von-Neumann bottleneck are being extensively explored in the literature. Emerging non-volatile memristive technologies have been shown to be very efficient in computing analog dot products in an in-situ fashion. The memristive analog computation of the dot product results in much faster operation as opposed to digital vector in-memory bit-wise Boolean computations. However, challenges with respect to large scale manufacturing coupled with the limited endurance of memristors have hindered rapid commercialization of memristive based computing solutions. In this…
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