FPGAs Becoming More SoC-Like


FPGAs are blinged-out rockstars compared to their former selves. No longer just a collection of look-up tables (LUTs) and registers, FPGAs have moved well beyond into now being architectures for system exploration and vehicles for proving a design architecture for future ASICs. This family of devices now includes everything from basic programmable logic all the way up to complex SoC devices.... » read more

Progress And Chaos On Road To Autonomy


Progress in the development of fully autonomous vehicles is incremental and slow, but not for lack of effort. Research and development in self-driving cars is under way all around the globe, from the biggest automotive manufacturers and their Tier 1 suppliers to companies not traditionally involved in the automotive industry. Add to that fleets of startups working on sensor technologies and ... » read more

Designing Hardware For Security


By Ed Sperling and Kevin Fogarty Cyber criminals are beginning to target weaknesses in hardware to take control of devices, rather than using the hardware as a stepping stone to access to the software. This shift underscores a significant increase in the sophistication of the attackers, as evidenced by the discovery of Spectre and Meltdown by Google Project Zero in 2017 (made public in Ja... » read more

New Patterning Options Emerging


Several fab tool vendors are rolling out the next wave of self-aligned patterning technologies amid the shift toward new devices at 10/7nm and beyond. Applied Materials, Lam Research and TEL are developing self-aligned technologies based on a variety of new approaches. The latest approach involves self-aligned patterning techniques with multi-color material schemes, which are designed for us... » read more

Get Ready For Integrated Silicon Photonics


Long-haul communications and data centers are huge buyers of photonics components, and that is leading to rapid advances in the technology and opening new markets and opportunities. The industry has to adapt to meet the demands being placed on it and solve the bottlenecks in the design, development and fabrication of integrated silicon photonics. "Look at the networking bandwidth used across... » read more

The Bumpy Road To 5G


5G is coming, but not everywhere, not all at once, and not the fastest version of this technology right away. In fact, the probable scenario is that 5G will be rolled out first in densely populated urban areas, starting in 2020 or 2021, with increasingly widespread adoption over the next decade after that. But 5G is unlikely to ever completely replace 4G LTE, just as a smart phone today roll... » read more

EUV’s New Problem Areas


Extreme ultraviolet (EUV) lithography is moving closer to production, but problematic variations—also known as stochastic effects—are resurfacing and creating more challenges for the long-overdue technology. GlobalFoundries, Intel, Samsung and TSMC hope to insert [gettech id="31045" comment="EUV"] lithography into production at 7nm and/or 5nm. But as before, EUV consists of several compo... » read more

Anatomy Of An Autonomous Vehicle Crash


The rollout of autonomous vehicles will have far-reaching impacts on technology, business and social interactions, but it also will set in motion a whole new side of technology development and new legal frameworks to prove what went wrong when these vehicles are involved in an accident. This isn't just something to plan for down the road. The California Department of Motor Vehicles this week... » read more

Transistor Options Beyond 3nm


Despite a slowdown in chip scaling amid soaring costs, the industry continues to search for a new transistor type 5 to 10 years out—particularly for the 2nm and 1nm nodes. Specifically, the industry is pinpointing and narrowing down the transistor options for the next major nodes after 3nm. Those two nodes, called 2.5nm and 1.5nm, are slated to appear in 2027 and 2030, respectively, accord... » read more

Bridging Machine Learning’s Divide


There is a growing divide between those researching [getkc id="305" comment="machine learning"] (ML) in the cloud and those trying to perform inferencing using limited resources and power budgets. Researchers are using the most cost-effective hardware available to them, which happens to be GPUs filled with floating point arithmetic units. But this is an untenable solution for embedded infere... » read more

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