tag: FD-SOI

What’s Important For IoT—Power, Performance Or Integration?
By Ed Sperling - 04 Aug, 2016 - Comments: 0

Semiconductor Engineering sat down with Steve Hardin, director of product development for AT&T's IoT Solutions Group; Wayne Dai, CEO of VeriSilicon; John Koeter, vice president of the Solutions Group at [getentity id="22035" e_name="Synopsys"]; and Rajeev Rajan, vice president for IoT at [getentity id="22819" comment="GlobalFoundries"]. What follows are excerpts of that conversation. SE:... » read more

To 7nm And Beyond
By Ed Sperling - 21 Jul, 2016 - Comments: 4

Gary Patton, chief technology officer at [getentity id="22819" comment="GlobalFoundries"], and Thomas Caulfield, senior vice president and general manager of Fab 8, sat down with Semiconductor Engineering to discuss future directions in technology, including the next rev of FD-SOI, the future of Moore’s Law, and how some very public challenges will likely unfold. SE: What do you see as the... » read more

Building Faster Chips
By Ed Sperling - 21 Jul, 2016 - Comments: 5

By Ed Sperling and Jeff Dorsch An explosion in IoT sensor data, the onset of deep learning and AI, and the commercial rollout of augmented and virtual reality are driving a renewed interest in performance as the key metric for semiconductor design. Throughout the past decade in which mobility/smartphone dominated chip design, power replaced performance as the top driver. Processors ha... » read more

No More Easy IP Money
By Brian Bailey - 14 Jul, 2016 - Comments: 2

The semiconductor intellectual property ([getkc id="43" kc_name="IP"]) industry is two decades old, but questions are still being asked about what's wrong with it and what needs to be fixed. Normally these kinds of issues are reserved for fast-moving, young industries, not one that is the backbone of semiconductors. Design reuse has become an indispensable part of the design of nearly all el... » read more

FD-SOI Strains For The Future
By Katherine Derbyshire - 11 Jul, 2016 - Comments: 0

One of the challenges facing supporters of FD-SOI is the need to provide a pathway to improved performance. While FD-SOI wafers offer some significant advantages over bulk silicon wafers, performance enhancements like strain and alternative channel materials are more difficult to implement in the thin SOI environment. On the other hand, once a fab is willing to incorporate layer transfer techni... » read more

Bulk CMOS Vs. FD-SOI
By Mark LaPedus - 19 May, 2016 - Comments: 2

The leading edge of the chip market increasingly is divided over whether to move to finFETs or whether to stay at 28nm using different materials and potentially even advanced packaging. Decisions about which approach to take frequently boil down to performance, power, form factor, cost, and the maturity of the individual technologies. All of those can vary by market, by vendor and by process... » read more

Power-Centric Chip Architectures
By Ed Sperling - 12 May, 2016 - Comments: 0

As traditional scaling runs out of steam, new chip architectures are emerging with power as the starting point. While this trend has been unfolding for some time, it is getting an extra boost and sense of urgency as design teams weigh a growing number of design challenges and options across a variety of new markets. Among the options are [getkc id="196" kc_name="multi-patterning"] and [getkc... » read more

The Week In Review: Manufacturing
By Mark LaPedus - 01 Apr, 2016 - Comments: 0

Chipmakers Lawrence Livermore National Laboratory (LLNL) has purchased a brain-inspired supercomputing platform for deep learning developed by IBM Research. LLNL will receive a 16-chip TrueNorth system from IBM. A single TrueNorth processor from IBM consists of 5.4 billion transistors wired together to create an array of 1 million digital neurons. The chip is fabricated based on a 28nm LPP pro... » read more

Manufacturing Bits: March 29
By Mark LaPedus - 29 Mar, 2016 - Comments: 0

Brain-inspired computing Lawrence Livermore National Laboratory (LLNL) has purchased a brain-inspired supercomputing platform for deep learning developed by IBM Research. Based on a neurosynaptic computer chip called IBM TrueNorth, the scalable platform will process the equivalent of 16 million neurons and 4 billion synapses. It will consume the energy equivalent of a tablet computer. ... » read more

How Many Cores? (Part 2)
By Ed Sperling - 21 Mar, 2016 - Comments: 1

New chip architectures and new packaging options—including fan-outs and 2.5D—are changing basic design considerations for how many cores are needed, what they are used for, and how to solve some increasingly troublesome bottlenecks. As reported in part one, just adding more cores doesn't necessarily improve performance, and adding the wrong size or kinds of cores wastes power. That has s... » read more

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