Machine Learning Moves Into Fab And Mask Shop


Semiconductor Engineering sat down to discuss artificial intelligence (AI), machine learning, and chip and photomask manufacturing technologies with Aki Fujimura, chief executive of D2S; Jerry Chen, business and ecosystem development manager at Nvidia; Noriaki Nakayamada, senior technologist at NuFlare; and Mikael Wahlsten, director and product area manager at Mycronic. What follows are excerpt... » read more

What Makes A Good AI Accelerator


The rapid growth and dynamic nature of AI and machine learning algorithms is sparking a rush to develop accelerators that can be optimized for different types of data. Where one general-purpose processor was considered sufficient in the past, there are now dozens vying for a slice of the market. As with any optimized system, architecting an accelerator — which is now the main processing en... » read more

Machine Learning Invades IC Production


Semiconductor Engineering sat down to discuss artificial intelligence (AI), machine learning, and chip and photomask manufacturing technologies with Aki Fujimura, chief executive of D2S; Jerry Chen, business and ecosystem development manager at Nvidia; Noriaki Nakayamada, senior technologist at NuFlare; and Mikael Wahlsten, director and product area manager at Mycronic. What follows are excerpt... » read more

RISC-V Inches Toward The Center


RISC-V is pushing further into the mainstream, showing up across a wide swath of designs and garnering support from a long and still-growing list of chipmakers, tools vendors, universities and foundries. In most cases it is being used as a complementary processor than a replacement for something else, but that could change in the future. What makes RISC-V particularly attractive to chipmaker... » read more

Machine Learning Shifts More Work to FPGAs, SoCs


A wave of machine-learning-optimized chips is expected to begin shipping in the next few months, but it will take time before data centers decide whether these new accelerators are worth adopting and whether they actually live up to claims of big gains in performance. There are numerous reports that silicon custom-designed for machine learning will deliver 100X the performance of current opt... » read more

Processing In Memory


Adding processing directly into memory is getting a serious look, particularly for applications where the volume of data is so large that moving it back and forth between various memories and processors requires too much energy and time. The idea of inserting processors into memory has cropped up intermittently over the past decade as a possible future direction, but it was dismissed as an e... » read more

Using AI In Chip Manufacturing


David Fried, CTO at Coventor, a Lam Research Company, sat down with Semiconductor Engineering to talk about how AI and Big Data techniques will be used to improve yield and quality in chip manufacturing. What follows are excerpts of that conversation. SE: We used to think about manufacturing data in terms of outliers, but as tolerances become tighter at each new node that data may need to b... » read more

Adding NoCs To FPGA SoCs


FPGA SoCs straddle the line between flexibility and performance by combining elements of both FPGAs and ASICs. But as they find a home in more safety- and mission-critical markets, they also are facing some of the same issues as standard SoCs, including the ability to move larger and larger amounts of data quickly throughout an increasingly complex device, and the difficulty in verifying and de... » read more

Higher Performance, Lower Power Everywhere


The future of technology is all about information—not just data—at our fingertips, anywhere and at any time. But making all of this work properly will require massive improvements in both performance and power efficiency. There are several distinct pieces to this picture. One is architectural, which is possibly the simplest to understand, the most technologically challenging to realize, ... » read more

Counting On Cryptocurrency


While cryptocurrencies may still be in the infancy of market development and adoption, the semiconductor industry has certainly felt the potential of blockchain technologies. In its fourth quarter 2017 earnings conference, TSMC commented on the strong demand from cryptocurrency-related businesses since the second half of 2017. These “mining” markets are driving leading-edge business at TSMC... » read more

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