JOURNAL ARTICLE

RISC-Vlim, a RISC-V Framework for Logic-in-Memory Architectures

Andrea ColuccioAntonia IevaFabrizio RienteMassimo Ruo RochMarco OttaviMarco Vacca

Year: 2022 Journal:   Electronics Vol: 11 (19)Pages: 2990-2990   Publisher: Multidisciplinary Digital Publishing Institute

Abstract

Most modern CPU architectures are based on the von Neumann principle, where memory and processing units are separate entities. Although processing unit performance has improved over the years, memory capacity has not followed the same trend, creating a performance gap between them. This problem is known as the "memory wall" and severely limits the performance of a microprocessor. One of the most promising solutions is the "logic-in-memory" approach. It consists of merging memory and logic units, enabling data to be processed directly inside the memory itself. Here we propose an RISC-V framework that supports logic-in-memory operations. We substitute data memory with a circuit capable of storing data and of performing in-memory computation. The framework is based on a standard memory interface, so different logic-in-memory architectures can be inserted inside the microprocessor, based both on CMOS and emerging technologies. The main advantage of this framework is the possibility of comparing the performance of different logic-in-memory solutions on code execution. We demonstrate the effectiveness of the framework using a CMOS volatile memory and a memory based on a new emerging technology, racetrack logic. The results demonstrate an improvement in algorithm execution speed and a reduction in energy consumption.

Keywords:
Computer science Registered memory Flat memory model Memory map Interleaved memory Memory refresh Computer memory Extended memory Memory management Semiconductor memory Memory address Sense amplifier Conventional memory Microprocessor Computer architecture Uniform memory access Parallel computing Embedded system Computer hardware

Metrics

6
Cited By
0.65
FWCI (Field Weighted Citation Impact)
36
Refs
0.64
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Memory and Neural Computing
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Ferroelectric and Negative Capacitance Devices
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Semiconductor materials and devices
Physical Sciences →  Engineering →  Electrical and Electronic Engineering

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