tag: AI

Using AI To Monitor Dashboards In Chips And Systems
By Ed Sperling - 06 May, 2026 - Comments: 0

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

Research Bits: May 5
By Jesse Allen - 05 May, 2026 - Comments: 0

AI power prediction Researchers from MIT and the MIT-IBM Watson AI Lab developed a prediction tool that can quickly tell data center operators how much power will be consumed by running a particular AI workload on a certain processor or AI accelerator chip. It can be applied to a wide range of hardware configurations. The lightweight estimation model captures the power usage pattern of a GP... » read more

Designing Chips In The Context Of Rapidly Evolving AI
By Ann Mutschler - 04 May, 2026 - Comments: 0

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

Transforming DRC Closure At Advanced Nodes
By James Paris - 30 Apr, 2026 - Comments: 0

If you’re working on SoCs at 2 nm or below, you know DRC is a different beast these days. Early in the design, it’s common for DRC runs to dump hundreds of millions—or even billions—of violations at your feet. And that’s when everything is changing fast: block interfaces aren’t fixed and constraints are shifting with every new iteration. Making sense of these massive result sets, fi... » read more

Creating Agentic EDA Methodologies
By Brian Bailey - 30 Apr, 2026 - Comments: 1

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

When Semiconductor Materials Misbehave
By Gregory Haley - 27 Apr, 2026 - Comments: 0

Key Takeaways Material behavior in production depends on the process context that no development environment can fully replicate. In advanced packaging, the interactions that cross domain boundaries are increasingly where failures originate. The most accurate materials data is also the most commercially sensitive, leaving simulation models calibrated against generic inputs rather tha... » read more

Can Edge AI Keep Up?
By Ann Mutschler - 23 Apr, 2026 - Comments: 0

Key Takeaways: Model development is outpacing silicon design cycles, so edge AI architectures must prioritize adaptability. The required cadence for model updates is highly application-dependent and is closely tied to product lifetime and operational risk. Adaptability can conflict with power, performance, and area targets, so effective heterogeneous architectures and robust softwa... » read more

Silicon Photonics Lights The Way To More Efficient Data Centers
By Katherine Derbyshire - 16 Apr, 2026 - Comments: 0

Key Takeaways Photonic interconnects potentially increase bandwidth density while significantly reducing power consumption. AI workloads are driving their adoption in data centers. On the other hand, photonic interconnects require a variety of different materials, introducing process compatibility and thermal and mechanical stress issues. Integrated electro-optical I/O modules are th... » read more

The Thermal And Power Realities Of The AI Era
By Rafael Tudela - 16 Apr, 2026 - Comments: 0

The rapid growth of AI has created a surge in the global energy consumption at a rate never seen before. Today, data centers account for approximately 415 terawatt-hours (TWh) of electricity globally. To put this into perspective, the annual energy consumption of the United Kingdom in 2023 measured at 309 TWh. The International Energy Agency (IEA) projects data centers’ energy consumption wil... » read more

AI Growing Impact On Chip Design And EDA Tools
By Ed Sperling - 15 Apr, 2026 - Comments: 0

Key Takeaways Many workflows in the data center are customer-specific, which is part of the reason there is so much interest in agentic AI-enabled tools. Large systems companies are pressing EDA vendors for performance improvements to keep pace with their AI workflows. The makeup of design teams is changing as AI infiltrates more of the chip design process. Experts at the Ta... » read more

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