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Fast and Scalable Memristive In-Memory Sorting with Column-Skipping Algorithm
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Fast and Scalable Memristive In-Memory Sorting with Column-Skipping Algorithm
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Fast and Scalable Memristive In-Memory Sorting with Column-Skipping Algorithm
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Paper
Fast and Scalable Memristive In-Memory Sorting with Column-Skipping Algorithm
2022
Overview
Memristive in-memory sorting has been proposed recently to improve hardware sorting efficiency. Using iterative in-memory min computations, data movements between memory and external processing units can be eliminated for improved latency and energy efficiency. However, the bit-traversal algorithm to search the min requires a large number of column reads on memristive memory. In this work, we propose a column-skipping algorithm with help of a near-memory circuit. Redundant column reads can be skipped based on recorded states for improved latency and hardware efficiency. To enhance the scalability, we develop a multi-bank management that enables column-skipping for dataset stored in different memristive memory banks. Prototype column-skipping sorters are implemented with a 1T1R memristive memory in 40nm CMOS technology. Experimented on a variety of sorting datasets, the length-1024 32-bit column-skipping sorter with state recording of 2 demonstrates up to 4.08x speedup, 3.14x area efficiency and 3.39x energy efficiency, respectively, over the latest memristive in-memory sorting.
Publisher
Cornell University Library, arXiv.org
Subject
