27. Neuromorphic Computing: R&D Initiatives in Premier Indian Academic Labs

Structural Mechanics

Indian researchers at institutions like the Indian Institute of Science (IISc) and various IITs are developing neuromorphic computing architectures. These systems design silicon-based hardware that mimics the neural structure of the human brain. By utilizing memristor-based crossbar arrays to process analog signals directly, neuromorphic chips can perform complex AI tasks—such as real-time pattern recognition and sensory processing—at a fraction of the power required by conventional digital CPUs and GPUs.

Conventional Architecture (Von Neumann Bottleneck):
[CPU/GPU] <======== High Power Data Bus ========> [Memory Chip]

Neuromorphic Architecture:
[In-Memory Compute: Synaptic Memristor Arrays (No Data Transfer, Ultra-Low Power)]

Data-Driven Metrics

• Power Efficiency: Neuromorphic test chips operate with energy efficiency metrics on the order of picojoules per synaptic operation, a 100x improvement over conventional architectures.
• Array Density: Local research labs have fabricated memristive arrays capable of storing multiple resistance states per cell, enabling analog in-memory computing.
• Application Focus: Targeted use cases include low-power medical implants, edge-computing devices for autonomous drones, and localized satellite sensory processing.

Strategic Vector

The Science and Engineering Research Board (SERB) should establish a dedicated foundry access fund to help researchers tape out and test their neuromorphic designs at overseas commercial semiconductor foundries.