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
Why Chip Design AI Benchmarks Must Go Beyond Functional Correctness
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, complex interconnects, and multiple domains while closing increasingly demanding power, performance, and area (PPA) targets. AI offers […] The post Why Chip Design AI Benchmarks Must Go Beyond Functional Correctness appeared first on EE Times .
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