Abstract The emergence of quadrillion-parameter neural networks represents a transformative frontier in artificial intelligence, with the potential to address challenges ranging from climate modeling to fundamental cosmology. As large language models (LLMs) surge toward 1015 parameters, next-generation GPUs must dismantle the barriers of memory bandwidth, thermal density, and interconnect latency.  Achieving this scale, however, necessitates a radical rethinking of graphics processing unit (GPU) architectures. Future accelerators must deliver exaflop-class performance with… Read More »Revolutionizing AI Power: Designing Next-Gen GPUs for Quadrillion-Parameter Models