A fast and reconfigurable sort-in-memory system based on memristors

Sorting is a fundamental task in modern computing systems. Hardware sorters are typically based on the von Neumann architecture, and their performance is limited by the data transfer bandwidth and CMOS memory. Sort-in-memory using memristors could help overcome these limitations, but current systems still rely on comparison operations so that sorting performance remains limited. Here we describe a fast and reconfigurable sort-in-memory system that uses digit reads of one-transistor–one-resistor memristor arrays. We develop digit-read tree node skipping, which supports various data quantities and data types. We extend this approach with the multi-bank, bit-slice and multi-level strategies for cross-array tree node skipping. We experimentally show that our comparison-free sort-in-memory system can improve throughput by ×7.70, energy efficiency by ×160.4 and area efficiency by ×32.46 compared with conventional sorting systems. To illustrate the potential of the approach to solve practical sorting tasks, as well as its compatibility with other compute-in-memory schemes, we apply it to Dijkstra’s shortest path search and neural network inference with in situ pruning. A sort-in-memory system that relies on digit reads on one-transistor–one-resistor memristor arrays can offer improved throughput, energy efficiency and area efficiency compared with conventional sorting systems.