The only solution is an electronic design automation (EDA) toolset that can accurately predict chip behavior before any wafers are run, and even before the fab is ready. This enables the very first ...

Most conversations about AI start and end with compute. But every training run and every inference query is ultimately a data problem, and data must live somewhere. Memory, and increasingly, the ...

Warpage is becoming a bigger constraint as package, interposer, and panel sizes grow. Negative thermal expansion (NTE) ...

Increasingly complex chip designs require more test data than those developed at older nodes and on single planar dies. The ...

A scalable LPDDR-based memory platform optimized for edge AI inferencing.

How advanced NoC architectures and coherent subsystem IP can address the industry's next-gen scalability, safety, and ...

First-silicon success falls; engineering capacity; minimum clock period; optimizing PyTorch; counterfeit electronics.

Package twins must track what manufacturing actually builds, not just design intent. Missing process and supplier data can ...

Intel may be the marquee name, but materials suppliers, packaging hubs, and quantum startups will determine whether the region becomes a true semiconductor ecosystem.

Cost per token is causing EDA design budgets to balloon; what comes next isn’t entirely clear yet. Discussions have shifted ...

Researchers at National Yang Ming Chiao Tung University and TSMC published a technical paper titled “High contrast EUV ...

As computing systems evolve to meet the demands of AI, data centers, and high-performance workloads, the challenge is no ...