tag: ChipAgents

Toward Agentic Verification
By Brian Bailey - 28 May, 2026 - Comments: 1

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

Confusion Grows With More Interconnect Options And Tradeoffs
By Liz Allan - 18 May, 2026 - Comments: 0

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
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

Foundry Capacity Is Limiting Who Competes At Leading Edge Nodes
By Ann Mutschler - 30 Apr, 2026 - Comments: 0

Key Takeaways: Leading-edge node access is increasingly reserved for hyperscalers, squeezing smaller chip developers. Chiplets and advanced packaging offer a path forward, but raise cost, complexity, and risk — especially for smaller teams. Chip architecture is now driven as much by capacity, yield, and economics as by technical goals. The benefits of device scaling are sl... » read more

NoC Coherency Challenges Balloon With AI SoCs And Chiplets
By Liz Allan - 30 Apr, 2026 - Comments: 0

Key Takeaways Data movement, congestion, and energy efficiency are key determiners of whether compute is usable. Different processors bring various coherency challenges. For example, a cache-coherent NoC for CPUs is expensive and harder to verify than an I/O-coherent NoC for an accelerator. Designers need to balance top-down performance with bottom-up physical engineering to effect... » read more

Startup Funding: Q1 2026
By Jesse Allen - 13 Apr, 2026 - Comments: 0

The new year started off with a bang for private semiconductor companies, with 18 garnering mega funding rounds exceeding $100 million, and two, Rapidus and Cerebras, reaching the $1 billion mark. Predictably, the vast majority of those are either designing chips primarily for AI inference workloads or attempting to overcome bandwidth limitations by improving interconnects from the chip level t... » read more

A New Era For Co-Processing
By Brian Bailey - 09 Apr, 2026 - Comments: 0

Key Takeaways: There is no single processor capable of executing everything efficiently, meaning that multiple processors are required. Maximum efficiency is gained by minimizing the movement of data. Architects must maximize efficiency for today's workloads, while also adding enough flexibility to handle tomorrow's. New processor architectures are rapidly evolving thanks to... » read more

Data Boom Puts Pressure On NoCs, Fabrics
By Liz Allan - 26 Mar, 2026 - Comments: 0

Key Takeaways: NoC challenges, such as wiring congestion, timing closure, and performance, must be considered in tandem with topology and placement. Topologies can be customized to meet an application’s specific data flow needs, with a system containing multiple topologies to suit different data or zones. What is challenging for one type of system, such as an SoC, switch, or AI chi... » read more

AI Won’t Kill Verification IP, But It Will Redefine It
By Ann Mutschler - 26 Mar, 2026 - Comments: 0

Key Takeaways AI will enhance, not replace, verification IP by automating test generation and debug. Verification IP’s core value will increasingly lie in trust, accountability, and system-level realism, especially as designs become more complex, multi-die, and security-sensitive. AI shifts verification bottlenecks from execution to specification quality, raising expectations for c... » read more

AI Design Reshapes Data Management
By Ann Mutschler - 16 Mar, 2026 - Comments: 0

Key takeaways: Integrating AI into chip workflows is pushing companies to overhaul their data management strategies, shifting from passive storage to active, structured, and machine-readable systems. As training and inference workloads grow, data movement, congestion, and energy efficiency become the dominant challenges, often surpassing raw compute capability. Proprietary and comple... » read more

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