Cost-effective computational modeling of fault tolerant optimization of FinFET-based sram cells

Abstract

In the area of computational memory management, energy efficiency and proper utilization of memory cell area is being constantly investigated. However, record of research manuscript in this regards are quite less compared to other related research topic in computer science. We reviewed existing techniques of upgrading the performance of FinFET-based SRAM and found that adoption of computational modeling for optimization is quite a few to find. Hence, we model the problem of leakage power minimization as linear optimization problem and develop a technique that ensures better fault tolerance operation of FinFET-based SRAM using enhanced particle swarm optimization. We minimize the computational complexity of the algorithm compared to conventional evolutionary technique and other performance upgrading system found in recent times. Our algorithm has better control over convergence rate, energy dissipation, and capability to ensure fault tolerance.