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What’s the future of MEMS?

June 30, 2014 Comments off

MEMS market.

MEMS market.

What does the future hold for MEMS? How can the MEMS indistry stay profitable and innovative in the next five years? The MEMS market is still in a dynamic growth with an estimated 12.3 percent CAGR over 2013-2019 in $US value, growing from $11.7 billion in 2013 to $24 billion in 2019.

This growth, principally driven by a huge expansion of consumer products, is mitigated by two main factors. First, due to a fierce competition based on pricing, the ASPs are continuously decreasing.

Second, innovation is slow and incremental, as no new devices have been successfully introduced on the market since 2003.  Fierce competition based on pricing in now ongoing putting thus extreme pressure on device manufacturers.

Some trends are still impacting MEMS business. These are:

* Decrease of price in consumer electronics; ASP of MEMS microphones.
* Component size is still decreasing.

However, successful companies are still large leaders in distinct MEMS categories, such as STMicroelectronics, Knowles, etc. But maintaining growth in consumer electronic applications remains a challenge.

The market for motion sensor in cell phones and tablets is large and continuously expanding. Discrete sensors still decline, but will still be used in some platforms (OIS function for gyros). Next, 6- and 9-axis combos should grow rapidly. Because of strong price pressure and high adoption rate, the total market will stabilize from 2015.

STMicroelectronics, InvenSense and Bosch are still leaders in 3-axis gyros and 6-axis IMUs. It seems difficult for new players to compete and be profitable in this market. The automotive, industrial and medical applications of MEMS are driving growth of MEMS business. MEMS for automotive will grow from $2.6 billion in 2012 to $3.6 billion in 2018 with 5 percent CAGR.

MEMS industry is big and growing. Strong market pull observed for sensors and actuators in cell phones, automotive, medical, industrial.

• Not limited to few devices. A new wave of MEMS is coming!
• Component and die size are still being optimized while combo approaches become mainstream. And several disruptive technology approaches are now in development to keep going in term of size and price decrease.
• But the MEMS industry has not solved a critical issue: how to increase the chance of new devices to enter the market?

–RF switch, autofocus, energy harvesting devices, fuel cells… are example of devices still under development after over 10 years of effort.
–How to help companies to go faster and safer on the market with new devices?

Is GaN-on-Si disruptive technology?


The mass adoption of GaN on Si technology for LED applications remains uncertain. Opinions regarding the chance of success for LED-On-Si vary widely in the LED industry from unconditional enthusiasm to unjustified skepticism. Although significant improvements have been achieved, there are still some technology hurdles (such as performance, yields, CMOS compatibility, etc.).

The differential in substrate cost itself is not enough to justify the transition to GaN on Si technology. The main driver lies in the ability to manufacture in existing, depreciated CMOS fabs in 6” or 8”. For Yole Développement, if technology hurdles are cleared, GaN-on-Si LEDs will be adopted by some LED makers, but it will not become an industry standard.

Yole is more optimistic about the adoption of GaN on Si technology for power GaN devices. Contrary to LED industry, where GaN on Sapphire technology is the main stream and presents a challenging target, GaN on Si will dominate the GaN based power electronics applications. Although the GaN based devices remain more expensive than Si based devices, the overall cost of GaN device for some applications are expected to be lower three years from now according to some manufacturers.

Source:  Yole Développement, France.

Source: Yole Développement, France.

In 2020, GaN could reach more than 7 percent of the overall power device market and GaN on Si will capture more than 1.5 percent of the overall power substrate volume, representing more than 50 percent of the overall GaN on Si wafer volume, subjecting to the hypothesis that the 600 V devices would take off in 2014-2015.

GaN targets a $15 billion served available device market. GaN can power 4 families of devices and related applications. These are blue and green laser diodes, LEDs, power electronics and RF (see image).

Regarding GaN-on-Si LED, there will be no more than 5 percent penetration by 2020. As for GaN-on-GaN, it will be less than 2 percent. Yole considers that the leading proponents of LED-On-Si will successful and eventually adopt Si for all their manufacturing. Those include Bridgelux/Toshiba, Lattice Power, TSMC and Samsung. It expects that Silicon will capture 4.4 percent of LED manufacturing by 2020.

GaN wafer could break through the $2000 per 4” wafer barrier by 2017 or 2018, enabling limited adoption in applications that require high lumen output other small surfaces.

Plunify’s InTime helps FPGA design engineers meet timing and area goals!


Kirvy Teo

Kirvy Teo

Engineers designing FPGA applications face many challenges. Using Plunify’s automation and analysis platform, engineers can run 100 times more builds, analyze a larger set of builds and quickly zoom in on better quality results. Using data analytics and the cloud, Plunify created new capabilities for FPGA design, with InTime being an example.

Kirvy Teo said: What happens when you need to close timing in FPGA design and still can’t get it to work? Here is a new way to solve that problem – machine learning and analytics. InTime is an expert software that helps FPGA design engineers meet timing and area goals by recommending “strategies”. Strategies are combination of settings found in the existing FPGA software. With more than 70 settings available in the FPGA software, no sane FPGA design engineer have the time or capacity to understand how these affect the design outcomes.

One of the common methods now is to try random bruteforce using seeds. This is a one-way street. If you get to your desired result, great! If not, you would have wasted a bunch of time running builds with you none the wiser. Another aspect of running seeds is that the variance of the results is usually not very big, meaning you can’t run seeds on a design with bad timing scores.

However, using InTime, all builds become part of the data that we used to recommend strategies that can give you better results, using machine learning and predictive analytics. This means you will definitely get a better answer at the end of the day, and we have seen 40 percent performance improvements on designs!

How has Plunify been doing this year so far? According to Teo, Plunify did a controlled release to selected customers in first quarter of 2014, who are mainly based in China. It is easier to guess who as we nicknamed them “BCC” – Big Chinese Corporations.

Unsurprisingly, they have different methodologies to solving timing problems and design guidelines, many of which were done to pre-empt timing problems at the later stage of the design. InTime was a great way to help them to achieve their performance targets without disrupting their tool flows.

Plunify is announcing the launch of InTime during DAC and will be looking to partner with sale organizations in US.

What’s the future path likely to be? Teo added: “Machine learning and predictive analytics are one of the hottest topics and we have yet seen it being used much in chip design. We see a lot of potential in this sector. Beyond what InTime is doing now, there are still many chip design problems that can be solved with similar techniques.

“First, there is a need to determine the type of problems that can be solved with these techniques. Second, we are re-looking at existing design problems and wondering, if I can throw 100 or 1000 machines to this problem, can I get a better result? Third, how to get that better result without even running it!

“As you know, we do offer a FPGA cloud platform on Amazon. One of the most surprising observations is that people do not know how to use all those cheap power in the cloud! FPGA design is still confined to a single machine for daily work, like email. Even if I give you 100 machines, you don’t know how to check your emails faster! We see the same thing, the only method they know is to run seeds. InTime is what they need to make use of all these resources intelligently.

Why would FPGA providers take up the solution?

The InTime software works as a desktop software which can be installed in internal data centers or desktops. It is on longer just a cloud play. It works with the current  in-house FPGA software that the customer already own. We are helping FPGA providers like Xilinx or Altera, by helping their customers with the designs. They will feel: How about “Getting better results without touching your RTL code!”

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