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Author's Latest Posts


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

A New Era For Co-Processing


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

All Software Is Hardware-Dependent


I was lucky in my early career that I found two sets of great mentors. The first happened recently after graduating when I joined the Hilo development team. Members of that team included Phil Moorby, Simon Davdimann, Peter Flake, and others. They all had very different coding personalities, but most importantly, they worked as a team and used good foundational processes. One outcome of that ... » read more

Memory Wall Gets Higher


Key Takeaways An increasing percentage of the chip area is consumed by the same amount of SRAM for each node shrink. The problem is not limited to leading-edge AI, as it will eventually impact even small MCUs and MPUs. Architectural changes may be required. Stacking SRAM chiplets on logic is possible but expensive. SRAM is a vital piece of all computing systems, but its fail... » read more

AI Power on the Edge


Key takeaways Power and thermal become primary design considerations, not just optimizations. Hardware architectures need to be developed from the ground up. Hardware/software/model co-development is essential. Implementing AI on the edge is driven by a different set of metrics than training or even inference in the cloud. It makes power a first-class citizen, if not the mos... » read more

Follow The AI Leader


In the 1980s, a common expression was "nobody ever got fired for buying IBM." It was considered the safe option, long after new technologies had emerged. While it may not have been the most advanced option available, it remained the safe bet. It had an established ecosystem, and it was a known quantity. But who or what is the safe bet when it comes to AI? Who has the necessary data? Who has ... » read more

Using Data And AI More Effectively In EDA


Key Takeaways The data being produced by EDA tools tends to be for human consumption and has weak semantics. Agents are attempting to create actionable information from unstructured data. The Model Context Protocol may provide AI with access to better data. Semiconductor design generates a lot of data, but how much of that is useful or currently being used by AI tools? And h... » read more

Minimum Energy Per Query


Key Takeaways Extracting heat from a chip faster is a short-term fix to a bigger problem. The longer-term challenge is how to reduce the amount of energy used per query. Data movement, guardbanding, and software inefficiency are key targets for the future. Heat is a serious problem within AI chips, and it is limiting how much processing can be done. The solution is either to... » read more

The Verification Conundrum


When constrained random test pattern generation became the de facto way to verify designs, reference models became necessary to check that a design was producing the correct output. These were often distributed across several models, such as checkers, scoreboards and assertions. Another model that had to be created was the coverage model. It was required because you had to know if a generate... » read more

Does Your RISC-V Core Meet The Standard?


Key Takeaways Architectural conformance and implementation verification are necessary but different for RISC-V designs, yet few verification engineers have experience on the conformance side. While RISC-V enables flexibility, there is a potential for ecosystem fragmentation. It is mathematically impossible to test every instruction combination, so engineers are moving beyond just "bl... » read more

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