Design data management, traceability, and revision control are critical for multi-chiplet heterogeneous integration.
A mixture of expert agentic AI systems can focus on their tasks with or without a commanding general, but challenges remain ...
Specialization and orchestration are becoming more important as the role of AI agents in chip design widens, but coordination ...
AI may accelerate semiconductor design, but users still need formal proof, semantic continuity, and auditable workflows to trust automation.
Digital twins and thermal sensors; agentic AI workflows; physical AI needs new silicon; RF design changes.
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.
Why design teams must organize before they optimize and how to utilize a purpose-built foundation for AI-ready data management across the chip design lifecycle.
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?” ...
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 ...
More capable robots require systems that realize capabilities through appropriate paradigms, compose them across time, distribute them across heterogeneous compute, and govern them under explicit ...
Even though the benefits are accepted, a combined hardware/software development flow is hampered by a lot of challenges.
Some results have been hidden because they may be inaccessible to you
Show inaccessible results