Smaller, Faster, Cheaper—But Different


The old mantra of "smaller, faster, cheaper" has migrated from the chip level to the electronic system level, raising some interesting questions about where the real value is being generated. Smaller as it pertains to gate size, line widths and spaces, will continue in an almost straight line for at least the next decade. The ability to print three-dimensional features on a nanoscale using E... » read more

Deep Learning Market Forces


Last week, eSilicon participated in a deep learning event at the Computer History Museum – “ASICs Unlock Deep Learning Innovation.” Along with Samsung, Amkor Technology and Northwest Logic, we explored how our respective companies form an ecosystem to develop deep learning chips for the next generation of applications. We also had a keynote presentation on deep learning from Ty Garibay, C... » read more

Can Big Data Help Coverage Closure?


Semiconductor designs are a combination of very large numbers and very small numbers. There is a large numbers of transistors at very small sizes, and databases are often large. The chip industry has been looking at [getkc id="305" kc_name="machine learning"] to effectively manage some of this data, but so far datasets have not been properly tagged across the industry and there is a reluctan... » read more

Using Data Mining Differently


The semiconductor industry generates a tremendous quantity of data, but until very recently engineers had to sort through it on their own to spot patterns, trends and aberrations. That's beginning to change as chipmakers develop their own solutions or partner with others to effectively mine this data. Adding some structure and automation around all of this data is long overdue. Data mining h... » read more

Data Buffering’s Role Grows


Data buffering is gaining ground as a way to speed up the processing of increasingly large quantities of data. In simple terms, a data buffer is an area of physical [getkc id="22" kc_name="memory"] storage that temporarily stores data while it is being moved from one place to another. This becomes increasingly necessary in data centers, autonomous vehicles, and for [getkc id="305" kc_name=... » read more

How To Deal With The Flood Of Analog Data


Analog data from a variety of sensors and other devices is a huge problem. Here are three approaches to overcoming the problems that big analog data can cause. Approach 1: Analyze at the Edge A lot of data can be collected at the point of capture, but most of it’s uninteresting. You can save and analyze it all or you can take advantage of intelligent embedded software that constantly meas... » read more

Full-Chip Power Integrity And Reliability Signoff


As designs increase in complexity to cater to the insatiable need for more compute power — which is being driven by different AI applications ranging from data centers to self-driving cars—designers are constantly faced with the challenge of meeting the elusive power, performance and area (PPA) targets. PPA over-design has repercussions resulting in increased product cost as well as pote... » read more

Let’s Be Smart About Artificial Intelligence


Technology visionaries no less than Stephen Hawking and Elon Musk have called artificial intelligence (AI) the greatest threat facing the future of mankind. But unless we all wind up running for our lives from a “Terminator” killing machine, don’t the benefits of AI far outweigh the downsides? Looking past purely mathematic calculators from the abacus to Charles Babbage’s difference ... » read more

How Neural Networks Think (MIT)


Source: MIT’s Computer Science and Artificial Intelligence Laboratory, David Alvarez-Melis and Tommi S. Jaakkola Technical paper link MIT article General-purpose neural net training Artificial-intelligence research has been transformed by machine-learning systems called neural networks, which learn how to perform tasks by analyzing huge volumes of training data, reminded MIT research... » read more

Targeting And Tailoring eFPGAs


Robert Blake, president and CEO of Achronix, sat down with Semiconductor Engineering to discuss what's changing in the embedded FPGA world, why new levels of customization are so important, and difficulty levels for implementing embedded programmability. What follows are excerpts of that discussion. SE: There are numerous ways you can go about creating a chip these days, but many of the prot... » read more

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