Nightmare Fuel: The Hazards Of ML Hardware Accelerators


A major design challenge facing numerous silicon design teams in 2023 is building the right amount of machine learning (ML) performance capability into today’s silicon tape out in anticipation of what the state of the art (SOTA) ML inference models will look like in 2026 and beyond when that silicon will be used in devices in volume production. Given the continuing rapid rate of change in mac... » read more

Week In Review: Semiconductor Manufacturing, Test


The U.S. Commerce Department outlined proposed rules for the Chips for America Incentives Program, including additional details on national security measures applicable to the CHIPS Incentives Program included in the CHIPS and Science Act. The rules limit funding recipients from investing in the expansion of semiconductor manufacturing in foreign countries of concern, notably the People’s Rep... » read more

Options Widen For Optimizing IoT Designs


Creating a successful IoT design requires a deep understanding of the use cases, and a long list of tradeoffs among various components and technologies to provide the best solution at the right price point. Maximizing features and functions while minimizing costs is an ongoing balancing act, and the number of choices can be overwhelming. The menu includes SoC selection, OS and software proto... » read more

Trusted Sensor Technology For The Internet Of Things


“Data is the new oil” — Clive Humby, 2006 While this prediction relates to the value that can be generated from data, the focus here is on the tools at the oil well. Just as oil drilling platforms are expected to reliably produce crude oil around the clock, sensors are expected to reliably and continuously deliver high-quality data. But sensors have long since evolved from simple me... » read more

AI Becoming More Prominent In Chip Design


Semiconductor Engineering sat down to talk about the role of AI in managing data and improving designs, and its growing role in pathfinding and preventing silent data corruption, with Michael Jackson, corporate vice president for R&D at Cadence; Joel Sumner, vice president of semiconductor and electronics engineering at National Instruments; Grace Yu, product and engineering manager at Meta... » read more

Week In Review: Manufacturing, Test


TEL announced plans to build a ¥2.2 billion ($168.2 million) production and logistics center at its Tohoku Office to increase capacity. Construction of the 57,000m² facility, which will be used for manufacturing thermal processing and single-wafer deposition systems, is slated to start in spring 2024, and expected to be completed in fall 2025. Toshiba's board voted in favor of a 2 trillio... » read more

Looking Beyond TOPS/W: How To Really Compare NPU Performance


There is a lot more to understanding the true capabilities of an AI engine beyond TOPS per watt. A rather arbitrary measure of the number of operations of an engine per unit of power, the TOPS/W metric completely misses the point that a single operation on one engine may accomplish more useful work than a multitude of operations on another engine. In any case, TOPS/W is by no means the only spe... » read more

How AI Drives Faster Verification Coverage And Debug For First-Time-Right Silicon


By Taruna Reddy and Robert Ruiz These days, the question is less about what AI can do and more about what it can’t do. From talk-of-the-town chatbots like ChatGPT to self-driving cars, AI is becoming pervasive in our everyday lives. Even industries where it was perhaps an unlikely fit, like chip design, are benefiting from greater intelligence. What if one of the most laborious, time-co... » read more

A Hierarchical And Tractable Mixed-Signal Verification Methodology For First-Generation Analog AI Processors


Artificial intelligence (AI) is now the key driving force behind advances in information technology, big data and the internet of things (IoT). It is a technology that is developing at a rapid pace, particularly when it comes to the field of deep learning. Researchers are continually creating new variants of deep learning that expand the capabilities of machine learning. But building systems th... » read more

Getting Smarter About Tool Maintenance


Chipmakers have begun to shift to predictive maintenance for process tools, but the hefty investment in analytics and engineering efforts means it will take some time for smart maintenance to become a widespread practice. Semiconductor manufacturers need to maintain a diverse set of equipment to process the flow of wafers, dies, packaged parts, and boards running through factories. OSAT and ... » read more

← Older posts Newer posts →