CEO Outlook: Chiplets, Longer IC Lifetimes, More End Markets


Experts at the Table: Semiconductor Engineering sat down to discuss chiplets, longer IC lifetimes, and a spike in the number of end applications with Lip-Bu Tan, CEO of Cadence; Simon Segars, CEO of Arm; Joseph Sawicki, executive vice president of Siemens IC EDA; John Kibarian, CEO of PDF Solutions; Prakash Narain, president and CEO of Real Intent; Dean Drako, president and CEO of IC Manage; an... » read more

IC Data Hot Potato: Who Owns And Manages It?


Modern inspection, metrology, and test equipment produces a flood of data during the manufacturing and testing of semiconductors. Now the question is what to do with all of that data. Image resolutions in inspection and metrology have been improving for some time to deal with increased density and smaller features, creating a downstream effect that has largely gone unmanaged. Higher resoluti... » read more

Customizing Chips For Power And Performance


Sandro Cerato, senior vice president and CTO of the Power & Sensor Systems Business Unit at Infineon Technologies, sat down with Semiconductor Engineering to talk about fundamental shifts in chip design with the rollout of the edge, AI, and more customized solutions. What follows are excerpts of that conversation. SE: The chip market is starting to fall into three distinct buckets, the e... » read more

Cloud Vs. On-Premise Analytics


The immense and growing volume of data generated in chip manufacturing is forcing chipmakers to rethink where to process and store that data. For fabs and OSATs, this decision is not one to be taken lightly. The proprietary nature of yield, performance, and other data, and corporate policies to retain tight control of that data, have so far limited outsourcing to the cloud. But as the amount... » read more

Too Much Fab And Test Data, Low Utilization


Can there be such a thing as too much data in the semiconductor and electronics manufacturing process? The answer is, it depends. An estimated 80% or more of the data collected across the semiconductor supply chain is never looked at, from design to manufacturing and out into the field. While this may be surprising, there are some good reasons: Engineers only look at data necessary to s... » read more

Infrastructure Impacts Data Analytics


Semiconductor data analytics relies upon timely, error-free data from the manufacturing processes, but the IT infrastructure investment and engineering effort needed to deliver that data is, expensive, enormous, and still growing. The volume of data has ballooned at all points of data generation as equipment makers add more sensors into their tools, and as monitors are embedded into the chip... » read more

Why Data Format Slows Chip Manufacturing Progress


The Standard Test Data Format (STDF), a workhorse data format used to pull test results data from automated test equipment, is running out of steam after 35 years. It is unable to keep up with the explosive increase in data generated by more sensors in various semiconductor manufacturing processes. First developed in 1985 by Teradyne, STDF is a binary format that is translated into ASCII or ... » read more

Blog Review: Feb. 12


Complexity is growing by process node, by end application, and in each design. The latest crop of blogs points to just how many dependencies and uncertainties exist today, and what the entire supply chain is doing about them. Mentor's Shivani Joshi digs into various types of constraints in PCBs. Cadence's Neelabh Singh examines the complexities of verifying a lane adapter state machine in... » read more

Network Storage Optimization In Chip Design


Prathna Sekar, technical account manager at ClioSoft, explains how to manage large quantities of data, how this can quickly spin out of control as colleagues check in data during the design process, and how to reduce the amount that needs to be stored. » read more

Reducing Data At The Source


Jens Döge, group manager for image acquisition and processing in Fraunhofer IIS’ Engineering of Adaptive Systems Division, talks about how to slash the amount of data that needs to be sent to the cloud or edge for processing by focusing only on the regions of interest in an image, and how that reduces the cost of moving that data. » read more

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