• A. Abhay kumar Mourya
• B. Manshi Singh
• C. Ankit Mishra

This article examines the benefits of integrating neuromorphic technology with fog computing and high-performance computing (HPC) to improve energy economy and computational capability via synergistic effects. Neuromorphic hardware differs from typical systems by using spiking neural networks (SNNs) to imitate the brain's energy-efficient processing. Fog and edge computing aims to reduce data sensitivity and processing time by bringing computational resources near IoT devices. This collaborative technology strives to minimize energy use, by green energy goals. Furthermore, it highlights the need for computing efficiency, especially in managing intricate tasks with little energy use. Integrating high-performance computing (HPC) with neuromorphic technology guarantees fast response times and efficient processing for real-time decision-making, learning, and adaptive processing. The capacity to adapt is essential for tasks such as grid optimization and renewable energy management. In addition, the study emphasizes the potential of high-performance computing (HPC) and neuromorphic technologies in properly forecasting renewable energy supplies and climate trends. The study demonstrates a beneficial and prospective method to improve the skills of self-driving car systems by using neuromorphic technology, in conjunction with fog and edge computing. Neuromorphic chips enable the efficient and low-power processing of sensory data, such as visual inputs from cameras and radar signals, within a collaborative architecture. The expansion of computational resources outside of centralized data centers brought about by fog computing makes it possible to make decisions more quickly via the use of scattered processing activities. The use of edge computing further boosts this potential by moving processing closer to the source of the data, which in turn reduces latency and enables real-time response.

Synergizing Neuromorphic Technology with Fog and High-Performance Computing for Enhanced Energy Efficiency and Real-Time Processing

"Synergizing Neuromorphic Technology with Fog and High-Performance Computing for Enhanced Energy Efficiency and Real-Time Processing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 11, page no.62-70, November-2024, Available :http://www.jetir.org/papers/JETIRGP06007.pdf

"Synergizing Neuromorphic Technology with Fog and High-Performance Computing for Enhanced Energy Efficiency and Real-Time Processing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 11, page no. pp62-70, November-2024, Available at : http://www.jetir.org/papers/JETIRGP06007.pdf