ARCHIVES

Original Article

Hardware-Efficient Triple Modular Redundancy via Shared Arithmetic Resources

B. Gayathiri1 N. Peramlatha2
1 VLSI Design, Vandayar Engineering College, Thanjavur, Tamilnadu, India. 2 Assistant Professor, Vandayar Engineering College, Thanjavur, Tamilnadu, India.

Published Online: July-August 2026

Pages: 01-06

Abstract

Conventional Triple Modular Redundancy (TMR) provides robust fault masking by triplicating functional logic and applying a two-out-of-three majority voter. Although this approach is effective against single faults and transient upsets, full replication of multiplier- intensive datapaths results in large area, power, and thermal overhead. This paper proposes a hardware-efficient resource-sharing TMR architecture that preserves the voting semantics of TMR while replacing three dedicated multipliers with a single low-power shared Booth-Wallace multiplier. The three redundant datapaths retain independent local logic, registers, and control state, while a round-robin arbiter and time-division multiplexing scheduler coordinate access to the shared arithmetic resource through request, grant, and done handshaking. Analytical evaluation indicates that the design can reduce normalized area from approximately 3.0x to 1.4-1.5x and normalized power from approximately 3.0x to 1.1-1.3x compared with conventional full TMR, while preserving deterministic masking of one faulty replica. The proposed approach is suitable for energy-constrained and mission-critical systems such as nanosatellites, portable avionics, embedded sensor processors, and implantable medical electronics.

Related Articles

2026

AI-Based Stomach Cancer Detection Using Biomarkers, Medical Images, and Voice Analysis

2026

Hydrogen-Efficient Eco-Driving and Route Planning for Fuel-Cell Electric Vehicles Using Multi-Objective Optimization Under Traffic and Terrain Uncertainty

2026

A Data-Driven Machine Learning Framework for Assessing Patent Commercial Value and Technological Significance

2026

Evaluating Student Academic Performance Through a Benchmark of Fuzzy Reasoning Models

2026

A Hybrid Soft Computing Approach for Managing Uncertainty in Data Analytics

2026

Soft Computing Approaches for Robust Analysis of Imbalanced and Noisy Data

Share Article

X
LinkedIn
Facebook
WhatsApp

Or copy link

https://www.theijire.com/archives/10.59256/ijire.20260704001

*Instagram doesn't support direct link sharing from web. Copy the link and share it in your Instagram story or post.