Neuromorphic PDE Supercomputers

Neuromorphic (brain‑inspired) hardware plus new algorithms can efficiently solve partial differential equations, the core math behind fluid dynamics, electromagnetics and structural modeling. If scalable, this approach could create a new class of energy‑efficient supercomputers optimized for scientific simulation rather than for standard neural‑net training. — A practical pathway to neuromorphic supercomputers would reshape energy and procurement choices for climate modeling, defense simulation, and industrial design, as well as redirect R&D funding toward neuroscience‑inspired computing architectures.