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Why the AI era is forcing a redesign of the entire compute backbone
Guest Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now The past few decades have seen almost unimaginable advances in compute performance and efficiency, enabled by Moore’s Law and underpinned by scale-out commodity hardware and loosely coupled software. This […]
We are now witnessing a decisive shift towards specialized hardware — including ASICs, GPUs, and tensor processing units (TPUs) — that deliver orders of magnitude improvements in performance per dollar and per watt compared to general-purpose CPUs. However, even HBM faces fundamental limitations: The physical chip perimeter restricts total dataflow, and moving massive datasets at terabit speeds creates significant energy constraints. This drive for extreme density and tightly coordinated computation fundamentally alters the optimal design for infrastructure, demanding a radical rethinking of physical layouts and dynamic power management to prevent performance bottlenecks and maximize efficiency.
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