Building Multi-Agent Systems For ASIC Flows


If one AI agent can solve a problem in a certain amount of time, can multiple agents solve it faster? The answer is yes, but only if the agents have well-defined roles and targets. This is where orchestrators fit in, and why they are so critical to agentic AI. Kexun Zhang, head of research at ChipAgents, talks about what exactly AI agents are, how they can be used to solve big problems that wou... » read more

PCIe Benefits From AI, Despite Scaling Protocols


Key takeaways: PCIe remains a critical technology for non-AI processing. For AI, PCIe will be strengthened by scale-out, agentic AI, and even some scale-up. CXL is seeing uptake, and some even think it could participate in AI processing. PCIe has been the go-to network for most data traffic moving from a processor to devices located elsewhere, which is also what the new data... » read more

2026 ASMC – Building the Core Pillars for AI in Semiconductors


Abstract: This presentation outlines a practical pathway for semiconductor manufacturers to move beyond AI experimentation and achieve scalable, value-driven implementation. As rising process complexity, massive data volumes, and talent constraints make AI a strategic necessity, this presentation highlights why over 70% of AI initiatives stall, primarily due to fragmented data, legacy system... » read more

Disturbance In Verification


When writing my recent story about agentic verification, there was one quote from Abhi Kolpekwar, senior vice-president and general manager at Siemens EDA, that really struck a chord. He was talking about the additional token costs that would be consumed when a verification engineer starts asking the agents to do what was considered to be part of their job. "Consider the total cost of owners... » read more

Toward Agentic Verification


Key Takeaways: Agentic verification provides flow orchestration for common repetitive tasks. Capabilities will expand when tools can learn from a larger context, including the specification. Design houses need to fully understand the costs and benefits and plan accordingly. Agentic verification is more than a buzzword. It is a pivotal moment in the evolution of verification ... » read more

Building AI Without Guardrails


Key Takeaways: AI governance is broadly recognized as essential, but today it remains fragmented, largely aspirational, and lacking enforceable mechanisms for accountability, runtime assurance, and global interoperability. Because AI innovation is advancing too quickly for governments or standards bodies to keep pace, practical AI governance is most likely to emerge first from high‑ri... » read more

Using AI To Monitor Dashboards In Chips And Systems


Key Takeaways: New types of dashboards are being used in conjunction with AI to make sense of large quantities of data. These dashboards can be used to quickly identify and fix power and heat-related problems, such as hotspots or voltage droop. Future dashboards will likely be much more customizable for different users or applications. Chipmakers are starting to use AI to ma... » read more

Designing Chips In The Context Of Rapidly Evolving AI


Key Takeaways: Agentic edge AI drives long-lived, tool-mediated loops with variable demands for compute, tokens, and memory. Edge PPA is dominated by memory hierarchy and data movement, forcing tight feature triage and robust RAS. Rapid model churn (multimodal, MoE, new formats) requires programmable, headroom-rich compute, interconnect, and runtime. Experts At The Table: Ch... » read more

Creating Agentic EDA Methodologies


Key takeaways Agentic methodologies need to be able to reason across multiple data formats and abstractions. It is not clear how much data from previous designs is useful in new designs. Standards may help, but the lack of them may only impact cost. The relationship between tools and methodologies is bidirectional. Tools enable methodologies, and methodologies are dependent ... » read more

Leveraging Agentic AI Techniques to Improve Formal Verification (Infineon, et al.)


A new technical paper, "Agentic AI-based Coverage Closure for Formal Verification," was published by researchers at Infineon and the NIT Jalandhar. Abstract "Coverage closure is a critical requirement in Integrated Chip (IC) development process and key metric for verification sign-off. However, traditional exhaustive approaches often fail to achieve full coverage within project timelines.... » read more

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