Using Manufacturing Data To Boost Reliability


As chipmakers turn to increasingly customized and complex heterogeneous designs to boost performance per watt, they also are demanding lower defectivity and higher yields to help offset the rising design and manufacturing costs. Solving those issues is a mammoth multi-vendor effort. There can be hundreds of process steps in fabs and packaging houses. And as feature sizes continue to shrink, ... » read more

Speeding Up Scan-Based Volume Diagnosis


In the critical process known as new-product bring-up, it’s a race to get new products to yield as quickly as possible. But the interplay between increasingly complex aspects of designs and process makes it difficult to find root causes of yield issues so they can be fixed quickly. Advanced processes have very high defectivity, and learning must be fast and effective. While progress has be... » read more

Optimizing System Performance At Runtime


Silicon lifecycle management (SLM) is one of the hottest emerging topics in the semiconductor industry. Chip and system developers face relentless demands for ever greater performance, reliability, functional safety, and security along with lower power consumption and silicon cost. Key applications driving these demands include data centers, autonomous vehicles, complex consumer devices such as... » read more

Big Payback For Combining Different Types Of Fab Data


Collecting and combining diverse data types from different manufacturing processes can play a significant role in improving semiconductor yield, quality, and reliability, but making that happen requires integrating deep domain expertise from various different process steps and sifting through huge volumes of data scattered across a global supply chain. The semiconductor manufacturing IC data... » read more

Improving Energy And Power Efficiency In The Data Center


Energy costs in data centers are soaring as the amount of data being generated explodes, and it's being made worse by an imbalance between increasingly dense processing elements that are producing more heat and uneven server utilization, which requires more machines to be powered up and cooled. The challenge is to maximize utilization without sacrificing performance, and in the past that has... » read more

Week In Review: Design, Low Power


Infineon Technologies acquired Syntronixs Asia, which specializes in precision electroplating, a key process in the assembly process of semiconductors. Syntronixs Asia has a workforce of more than 500 people and has been a major service provider for Infineon since 2009. “Through this acquisition, we have made another important step to strengthen the resilience of our supply chain,” said Tho... » read more

Why It’s So Difficult — And Costly — To Secure Chips


Rising concerns about the security of chips used in everything from cars to data centers are driving up the cost and complexity of electronic systems in a variety of ways, some obvious and others less so. Until very recently, semiconductor security was viewed more as a theoretical threat than a real one. Governments certainly worried about adversaries taking control of secure systems through... » read more

Advanced Packaging For Automotive Chips


Multiple types of chips may be better than one for dealing with large amounts and different types of data, but in automotive applications it's not entirely clear how or even whether they should be packaged together. The biggest problem with electronics in vehicles is the extreme range of temperatures, both within and outside of vehicles. Without adequate cooling, chips can age prematurely, s... » read more

Meeting Processor Performance And Safety Requirements For New ADAS & Autonomous Vehicle Systems


By Fergus Casey and Srini Krishnaswami Innovation in today’s automotive industry is accelerating as companies race to be the market leader in safety and autonomous vehicles. With vehicle control moving from humans to the vehicles’ active safety systems, more sensors – cameras, radar, lidar, etc. – are being added to automotive systems. More sensors require more computational performa... » read more

Will Markets For ML Models Materialize?


Developers are spending increasing amounts of time and effort in creating machine-learning (ML) models for use in a wide variety of applications. While this will continue as the market matures, at some point some of these efforts might be seen as reinventing models over and over. Will developers of successful models ever have a marketplace in which they can sell those models as IP to other d... » read more

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