ABSTRACT
In recent years, digital computing in memory (CIM) has been an efficient and high-performance solution in artificial intelligence (AI) edge inference. Nevertheless, digital CIM based on non-volatile memory (NVM) is less discussed for the sophisticated intrinsic physical and electrical behavior of non-volatile devices. In this paper, we propose a fully digital non-volatile CIM (DNV-CIM) macro with compressed coding look-up table (LUT) multiplier (CCLUTM) using the 40 nm technology, which is highly compatible with the standard commodity NOR Flash memory. We also provide a continuous accumulation scheme for machine learning applications. When applied to a modified ResNet18 network trained under the CIFAR-10 dataset, the simulations indicate that the proposed CCLUTM-based DNV-CIM can achieve a peak energy efficiency of 75.18 TOPS/W with 4-bit multiplication and accumulation (MAC) operations.
ABSTRACT
We describe an algorithm based on motion-planning techniques to determine the existence of an accessible route through a facility for a wheeled mobility device. The algorithm is based on LaValle's work on rapidly exploring random trees and is enhanced to take into consideration the particularities of the accessible route domain. Specifically, the algorithm is designed to allow performance-based analysis and evaluation of a facility. Furthermore, the parameters of a wheeled mobility device can be varied without recompilation, thus allowing standards writers, facility designers, and wheeled mobility device manufacturers to vary them accordingly. The algorithm has been implemented in a computer tool that works within a computer-aided design and drafting environment.
