FPGA Graduates To First-Tier Status


Robert Blake, president and CEO of Achronix, sat down with Semiconductor Engineering to talk about fundamental shifts in compute architectures and why AI, machine learning and various vertical applications are driving demand for discrete and embedded FPGAs. SE: What’s changing in the FPGA market? Blake: Our big focus is developing the next-generation architecture. We started this projec... » read more

Making Sure A Heterogeneous Design Will Work


An explosion of various types of processors and localized memories on a chip or in a package is making it much more difficult to verify and test these devices, and to sign off with confidence. In addition to timing and clock domain crossing issues, which are becoming much more difficult to deal with in complex chips, some of the new devices are including AI, machine learning or deep learning... » read more

Looking Beyond The CPU


CPUs no longer deliver the same kind of of performance improvements as in the past, raising questions across the industry about what comes next. The growth in processing power delivered by a single CPU core began stalling out at the beginning of the decade, when power-related issues such as heat and noise forced processor companies to add more cores rather than pushing up the clock frequency... » 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

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

Gaps In Verification Metrics


As design complexity has exploded, the verification effort has likewise grown exponentially, with many different types of verification being applied to different classes of design. A recent panel discussion with leading chipmakers examined this topic in an effort to shed light on design health and quality, measuring the success of verification, knowing when verification is complete, being on... » 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

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

← Older posts