• A. Aarekh Verma
• B. Abhay Kumar Mourya
• C. Ankit Mishra

Ferroelectric materials are key in crafting neuromorphic devices that emulate the brain's synaptic functions, offering promising pathways for advanced computing. These materials, characterized by their ability to undergo spontaneous electric polarization reversal akin to neural synapse activity, are prime candidates for neuromorphic applications. Analytical techniques provide essential insights into these materials, enabling the development of more efficient, powerful devices. High Performance Computing (HPC) significantly contributes to this field by simulating material behaviours at the atomic level, predicting properties such as polarization switching speeds and responses to stimuli. HPC facilitates the creation of large-scale neuromorphic network models with ferroelectric synapses, essential for exploring complex neural dynamics and optimizing application performance. Moreover, HPC accelerates neural network training, particularly for spiking neural networks (SNNs), and enhances real-time data processing for AI-driven systems and smart sensors. It also plays a pivotal role in improving power efficiency and investigating new ferroelectric materials for neuromorphic architectures, exploiting their unique characteristics. Emphasizing green computing, the use of recyclable materials and energy-efficient equipment aligns with environmental sustainability goals, positioning ferroelectric materials as catalysts for revolutionizing neuromorphic computing towards eco-friendly, energy-efficient AI systems. The synergy between ferroelectric materials, HPC, and environmental sustainability paves the way for significant advancements in cognitive computing. By leveraging renewable energy sources and optimizing smart grids, this technology not only enhances energy efficiency but also fosters the development of powerful, sustainable cognitive computing systems. A new age of computing that is both efficient and impactful is being ushered in by high-performance computing, which is a crucial driver in the advancement of ferroelectric-based neuromorphic technology.

Ferroelectric Materials, Neuromorphic Technology, High Performance Computing (HPC), Energy Efficiency, Sustainability

"Advancing Neuromorphic Technology: The Role of Ferroelectric Materials and High-Performance Computing in Sustainable, Energy-Efficient AI Systems", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 11, page no.1-8, November-2024, Available :http://www.jetir.org/papers/JETIRGP06001.pdf

"Advancing Neuromorphic Technology: The Role of Ferroelectric Materials and High-Performance Computing in Sustainable, Energy-Efficient AI Systems", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 11, page no. pp1-8, November-2024, Available at : http://www.jetir.org/papers/JETIRGP06001.pdf