Optimizing AI Systems


Inserting AI and machine learning into chips adds a whole new dimension of complexity, and creates a variety of potential problems, including deadlocks, loss of performance, and difficulty in achieving closure on many fronts. Gajinder Panesar, fellow at Siemens EDA, talks with Semiconductor Engineering about what’s changed and how to optimize these new devices and systems by monitoring them f... » read more

Design For Test Data


As design pushes deeper into data-driven architectures, so does test. Geir Eide, director for product management of DFT and Tessent Silicon Lifecycle Solutions at Siemens Digital Industries Software, talks with Semiconductor Engineering about a subtle but significant shift for designing testability into chips so that test data can be used at multiple stages during a device’s lifetime. » read more

Monitoring Performance From Inside A Chip


Deep data, which is generated inside the chip rather than externally, is becoming more critical at each new process node and in advanced packages. Uzi Baruch, chief strategy officer at proteanTecs, talks with Semiconductor Engineering about using that data to identify potential problems before they result in failures in the field, and why it's essential to monitor these devices throughout their... » read more

Silicon Lifecycle Management


How do you track, measure and ensure reliability over the lifetime of a chip, regardless of how or where it is used? Steve Pateras, senior director of marketing for test products at Synopsys, drills down into the impact of hardware-software co-design, over-the-air updates, the expected lifetime of designs, and how the various monitors and sensors are used to track environmental, structural and ... » read more

Using ML In Manufacturing


How to prevent early life failures by applying machine learning to different use cases, and how to interpret models for different tradeoffs on reliability. Jeff David, vice president of AI solutions at PDF Solutions, digs down into how to utilize data to improve reliability. » read more

Ensuring HBM Reliability


Igor Elkanovich, CTO of GUC, and Evelyn Landman, CTO of proteanTecs, talk with Semiconductor Engineering about difficulties that crop up in advanced packaging, what’s redundant and what is not when using high-bandwidth memory, and how continuous in-circuit monitoring can identify potential problems before they happen. » read more

Cleaning Data For Final Test


John O’Donnell, CEO of yieldHUB, talks about why data integrity is so critical for final test, what can cause it to be less-than-perfect, what’s needed to improve the quality of that data, and how that impacts the overall yield in a fab. » read more

Using Big Data For Yield And Reliability


John O’Donnell, CEO of yieldHUB, talks about the importance of clean data for traceability, yield improvement and device reliability, where and how it gets cleaned, and why that needs to be accompanied by domain expertise. » read more

Scan Diagnosis


Jayant D’Souza, product manager at Mentor, a Siemens Business, explains the difference between scan test and scan diagnosis, what causes values in a scan test to change, how this can be used to hone in on the actual cause of a failure in a design, and how to utilize test hardware more efficiently. » read more

Testing Autonomous Vehicles


Jeff Phillips, head of automotive marketing at National Instruments, talks about how to ensure that automotive systems are reliable and safe, how test needs to shift to adapt to continual updates and changes, and why this is particularly challenging in a world where there is no known right answer. » read more

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