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

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

More Massive Still: Why AI Infrastructure Demands A Unified Design Approach


At the recent Data Center World 2026 in Washington, D.C., one message came through louder than ever: AI infrastructure is scaling faster than any system we’ve built before—and the industry can no longer afford to design it in silos. The workshop: “More Massive Still! Delivering AI-Driven Scale in the Face of Historic Constraints” captured this perfectly: the industry is shifting fr... » read more

Blog Review: June 24


Cadence's Veena Parthan shows how finite element analysis simulations for crash testing can surpass the limitations of physical testing and offer insights into a wider array of crash scenarios that were once impossible to explore. Siemens' Haitham Eissa and Amr Khafagy warn that once-passive dummy fill structures have begun to influence design performance significantly as the industry progre... » read more

Chip Industry Week In Review


Dealmaking Amkor inked a 10-year agreement with TSMC to provide advanced packaging and test services in Arizona, tying TSMC’s U.S. fab expansion to domestic OSAT capacity. Trump said in a post that Apple will partner with Intel on chip design and production in the U.S., marking a second reported win for the chipmaker this month. Intel Foundry will also reportedly manufacture 3 million... » 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

Blog Review: June 17


Cadence's Rajan Jani explains NVMe's Controller Memory Buffer feature, which exposes on-controller memory directly to the host system to reduce latency, improve PCIe fabric efficiency, and increase performance in multi-switch topologies. Siemens' Linus Tauro shares how to run an SSN datapath at double the I/O data rate by implementing a BusFrequencyMultiplier and BusFrequencyDivider pair. ... » read more

Chip Industry Week In Review


Notable deals Cadence and Intel Foundry inked a multi-year agreement to advance design technology co-optimization and create PDKs for Intel Foundry's 14A process. Nvidia and SK hynix announced a multi-year partnership to co-develop memory technology for AI infrastructure and physical AI. Teradyne unveiled an integrated test cell solution with TEL that supports known-good device scree... » read more

DDR5 MRDIMM: A Transformational Evolution For DDR5 DIMM


DDR5 is the latest generation of DDR server memory capable of supporting data rates of up to 9,200 Mbps, which is a huge leap over the previous generation of DDR memories. It is used in a wide variety of applications, with the huge server and data center market being the key driver behind the adoption of DDR5-based memory systems. As systems move towards more CPU cores, bandwidth, and capacity,... » read more

Building Edge AI with IP Solutions


As AI inference moves from centralized cloud infrastructure into vehicles, factories, medical devices, and industrial systems, the decisive design challenge shifts from model quality to field-ready implementation. Deployed edge AI systems must perform reliably under a range of constraints, including fixed power budgets, stringent latency requirements, limited or intermittent cloud connectivity,... » read more

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