I/O Design Challenges Grow In AI Data Centers And HPC Clusters


Key Takeaways: A designer’s choice of I/O connectors and interconnect protocols can be the difference between a massively profitable AI chip and a flop. I/O tradeoffs impact airflow, cooling, rack design, power coming into the rack, and other critical aspects of HPC chip design. Reliability is paramount, so standards must be followed, and I/Os need redundant pins. Other innovations... » read more

Verification Methodologies Struggle To Keep Up With AI


Key Takeaways:  The rapid development of AI has resulted in new capabilities being provided to verification teams, beyond their ability to rationally insert them into accepted methodologies.  There is a lot of uncertainty about who will benefit the most from this technology. Is AI a junior engineer replacement or an enhancer?  The biggest benefits will come when AI helps engineers... » read more

Executive Outlook: Agentic AI’s Impact On Chip Design


Key Takeaways: Agentic AI has the potential to make engineers more productive, speed time to market, and automate some of the drudge work. The big challenge for design and verification engineers is where and whether they trust AI to get everything right, because there is no margin for error in semiconductors. Having humans in the loop will likely be the rule rather than the exception... » read more

Designing Chips That Can Explain Themselves


Key Takeaways: On-die telemetry gives architects a path to replace worst-case design margin with measured silicon behavior, improving PPA without compromising resilience. As monitor density and control-loop speed increase, observability must be architected hierarchically across local hardware response, on-die processing, and fleet-level learning. The real payoff is architectural: str... » read more

Swapping Out Chiplets: I/Os Vs. Compute


Key Takeaways: Companies can save time and money by swapping out a compute, memory, or I/O chiplet to gain technology improvements, while keeping the other dies stable. Chip architects may choose to keep their I/Os stable and swap out compute to move from a 5nm process node to 3nm to achieve performance and power improvements, or swap out memory from LPDDR5X to LPDDR6. Swapping out... » read more

Observability Is Essential For Modern Silicon


Experts At The Table: In-silicon observability — also known as on-die or on-chip visibility — is becoming increasingly important for managing the performance, reliability, and security of today’s high-performance systems. Semiconductor Engineering sat down to discuss this with Andy Nightingale, vice president of product management and marketing at Arteris; Nandan Nayampally, chief commerc... » read more

Options Grow For Standardizing Data Movement And Sharing Resources


Semiconductor Engineering sat down to discuss memory interfaces, interconnects, and memory access scaling with Madhumita Sanyal, senior director of technical product management at Synopsys; Swadesh Choudhary, senior principal engineer at Intel; Siamak Tavallaei, senior principal engineer at Samsung SSI; and Mohsen Asad, senior director of technology at Credo. What follows are excerpts of a disc... » read more

Confusion Grows With More Interconnect Options And Tradeoffs


Key Takeaways: Designers are frequently evaluating 5 or more different interconnects in a single system, each with a distinct purpose. While chip-to-chip (PCIe) and die-to-die (UCIe, BoW) technologies seem to be solving a similar problem, in practice they bring different challenges. PCIe, CXL, NVLink, and UALink are all active in the hyperscaler space, but Ethernet-based technologies... » 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

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