AI may accelerate semiconductor design, but users still need formal proof, semantic continuity, and auditable workflows to trust automation.
As AI chips move to stacked, chiplet-based architectures, EDA vendors are reworking mature tools for cross-domain analysis, faster exploration, and agentic AI assistance.
Specialization and orchestration are becoming more important as the role of AI agents in chip design widens, but coordination ...
A mixture of expert agentic AI systems can focus on their tasks with or without a commanding general, but challenges remain ...
Digital twins and thermal sensors; agentic AI workflows; physical AI needs new silicon; RF design changes.
Unified Compression and Streaming Fabric (SF) provide a practical implementation methodology capable of scaling from individual IP blocks to large AI accelerators containing hundreds of millions of ...
Researchers at the University of Wisconsin–Madison and Marist University published a technical paper titled “Demystifying ...
Researchers at UCLA published a technical paper titled “Can Agents Design Better Chips with a Higher Level Abstraction?” ...
All chip designers know that they must take special care to avoid metastability problems when they have multiple, asynchronous clock domains. In contrast, a design in which all clocks are synchronous ...
Package twins must track what manufacturing actually builds, not just design intent. Missing process and supplier data can ...
Researchers at Georgia Tech, Nvidia Research, and Stanford University published a technical paper titled “BOOST: Concurrent Access to Host Memory and HBM to Accelerate LLM Inference.” Abstract Excerpt ...
A scalable LPDDR-based memory platform optimized for edge AI inferencing.
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