AID: Accuracy Improvement of Analog Discharge-Based in-SRAM Multiplication Accelerator

04/15/2022
by   Saeed Seyedfaraji, et al.
0

This paper presents a novel circuit (AID) to improve the accuracy of an energy-efficient in-memory multiplier using a standard 6T-SRAM. The state-of-the-art discharge-based in-SRAM multiplication accelerators suffer from a non-linear behavior in their bit-line (BL, BLB) due to the quadratic nature of the access transistor that leads to a poor signal-to-noise ratio (SNR). In order to achieve linearity in the BLB voltage, we propose a novel root function technique on the access transistor's gate that results in accuracy improvement of on average 10.77 dB SNR compared to state-of-the-art discharge-based topologies. Our analytical methods and a circuit simulation in a 65 nm CMOS technology verify that the proposed technique consumes 0.523 pJ per computation (multiplication, accumulation, and preset) from a power supply of 1V, which is 51.18 have performed an extensive Monte Carlo based simulation for a 4x4 multiplication operation, and our novel technique presents less than 0.086 standard deviations for the worst-case incorrect output scenario.

READ FULL TEXT

page 1

page 5

research
10/11/2021

C3PU: Cross-Coupling Capacitor Processing Unit Using Analog-Mixed Signal In-Memory Computing for AI Inference

This paper presents a novel cross-coupling capacitor processing unit (C3...
research
03/02/2021

SME: ReRAM-based Sparse-Multiplication-Engine to Squeeze-Out Bit Sparsity of Neural Network

Resistive Random-Access-Memory (ReRAM) crossbar is a promising technique...
research
05/04/2020

An Experimental Study of Reduced-Voltage Operation in Modern FPGAs for Neural Network Acceleration

We empirically evaluate an undervolting technique, i.e., underscaling th...
research
08/30/2021

MultPIM: Fast Stateful Multiplication for Processing-in-Memory

Processing-in-memory (PIM) seeks to eliminate computation/memory data tr...
research
07/31/2017

Multiscale Co-Design Analysis of Energy, Latency, Area, and Accuracy of a ReRAM Analog Neural Training Accelerator

Neural networks are an increasingly attractive algorithm for natural lan...
research
03/20/2019

A 68 uW 31 kS/s Fully-Capacitive Noise-Shaping SAR ADC with 102 dB SNDR

This paper presents a 17 bit analogue-to-digital converter that incorpor...

Please sign up or login with your details

Forgot password? Click here to reset