Why Chip Design AI Benchmarks Must Go Beyond Functional Correctness

T2Covered by 1 source · first reported by Semiconductor Engineering / SemiWiki / EE Times / EE Journal / Electronics Weekly at 21 Oct, 13:00 UTC

Demand for custom silicon is rising as physical AI, data centers, automotive systems, and edge devices require architectures optimized for specific workloads, memory bandwidth, latency, and energy efficiency. Delivering these designs requires teams to coordinate heterogeneous compute blocks…

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Sources

• T2Why Chip Design AI Benchmarks Must Go Beyond Functional CorrectnessSemiconductor Engineering / SemiWiki / EE Times / EE Journal / Electronics Weekly21 Oct, 13:00