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arXiv · 2410.09953

Energy-Efficient and Fast Memristor-based Serial Multipliers Applicable in Image Processing

Seyed Erfan Fatemieh·Bahareh Bagheralmoosavi·Mohammad Reza Reshadinezhad
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Abstract

Memristive Processing In-Memory (PIM) is one of the promising techniques for overcoming the Von-Neumann bottleneck. Reduction of data transfer between processor and memory and data processing by memristors in data-intensive applications reduces energy consumption and processing time. Multipliers are one of the fundamental arithmetic circuits that play a significant role in data-intensive processing applications. The computational complexity of multipliers has turned them into one of the arithmetic circuits affecting PIM's efficiency and energy consumption, for example, in convolution operations. Serial material implication (IMPLY) logic design is one of the methods of implementing arithmetic circuits by applying emerging memristive technology that enables PIM in the structure of crossbar arrays. The authors propose unsigned and signed array multipliers using serial IMPLY logic in this paper. The proposed multipliers have improved significantly compared to State-Of-the Art (SOA) by applying the proposed Partial Product Units (PPUs) and overlapping computational steps. The number of computational steps, energy consumption, and required memristors of the proposed 8-bit unsigned array multiplier are improved by up to 36%, 31%, and 47% compared to the classic designs. The proposed 8-bit signed multiplier has also improved the computational steps, energy consumption, and required memristors by up to 59%, 54%, and 45%. The performance of the proposed multipliers in the applications of Gaussian blur and edge detection is also investigated, and the simulation results have shown an improvement of 31% in energy consumption and 33% in the number of computational steps in these applications.

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Seyed Erfan Fatemieh, Bahareh Bagheralmoosavi, Mohammad Reza Reshadinezhad. 2024-10-13. Energy-Efficient and Fast Memristor-based Serial Multipliers Applicable in Image Processing. https://arxiv.org/abs/2410.09953

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