Karen Heyman is a Technology Editor for Semiconductor Engineering. With a focus on the semiconductor industry, Karen covers topics such as emerging technologies, memory systems, artificial intelligence, and design workflows. Her articles provide insights into the latest developments and trends shaping the future of the technology landscape.
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Karen's coverage revolves around the manufacturing, design, and engineering aspects of advanced technologies. She frequently covers industry-specific topics such as in-memory compute, AI, EDA (Electronic Design Automation), SRAM (Static Random-Access Memory), sensor technology, and 3D design.
Given her focus on these technical areas with substantial press release coverage and government announcements, Karen may be interested in receiving pitches related to new product launches or significant technological advancements within these fields. Additionally, she may welcome expert commentary on the practical applications of emerging technologies or insights into future trends impacting manufacturing processes.
As Karen does not have a specific geographic focus but rather focuses on industry-specific developments worldwide, it would benefit outreach efforts to provide information that is globally relevant within the realm of advanced technology and manufacturing.
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New approaches to software-defined hardware involve a rethinking of model-based software engineering.
Limited power budgets, thermal issues, and increased demand to process more data faster are turning up some novel solutions.
By: Karen Heyman
Rethinking traditional workflows by shifting left can help solve persistent problems caused by process and thermal variations.
By: Karen Heyman
The small sizes and tight tolerances of embedded devices create big problems for reliability.
CFD, multiphysics, and digital twins play increasing role in planning for and addressing heat within and between server racks.
Automatically mitigating thermal issues becomes a top priority in heterogeneous designs.
By: Karen Heyman
Transport Level Security relies on the encryption algorithms that PQS puts at risk.
Current work on adding AI to enhance EDA tools centers on copilots. Present and future ideas focus on letting engineers do much more with the same or fewer resources.
Known as the workhorse technology for long-haul communications, photonics now plays a very different kind of role.
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