Predicting semiconductor business trends after Moore’s law: Dr. Wally Rhines

Predicting Semiconductor Business Trends After Moore’s Law is a book written by Dr. Walden C. Rhines, CEO, Rhines Consultants and CEO Emeritus, Siemens PLM Software and Mentor, a Siemens Business. It is a SemiWiki project.

In the book, he begins with how the semiconductor learning curve provides a roadmap. According to him, Texas Instruments’ (TI) unique approach for semiconductors lay in the use of the learning curve to drive a pricing strategy early in the life of a new component.

Dr. Wally Rhines

While Moore’s Law is becoming obsolete, the learning curve will never be. Instead, the cumulative number of transistors produced will stop moving so quickly to the right on the logarithmic scale. Then, the prices will not decrease as rapidly, as they have in the past. The visible effect of improved learning will diminish.

A graph shows how the cumulative unit volume of transistors used in memory components is increasing much faster than unit volume of transistors in other types of chips.

He says that if the EDA industry doesn’t keep its learning curve parallel to the semiconductor industry learning curve, the cost of EDA software as a percent of semiconductor revenue would increase. There would have to be cost reductions elsewhere in the semiconductor supply chain to offset it.

About Moore’s Law
Dr. Rhines goes on to say that ‘Moore’s Law’ has been extrapolated for more than 50 years. It is not a ‘law’. It is an empirical observation that became self-fulfilling after some adjustments. He cites revisions by Gordon Moore to the Moore’s Law, at least twice, in 1975 and 1997. And, later, in 2003. These repeated revisions affirm that “Moore’s Law” was not actually a law of nature, but an interesting, if temporary, phenomenon.

Dr. Rhines says that today, many people worry that the inevitable end of Moore’s Law will leave us with a stagnant semiconductor industry, with no guideposts to drive new silicon technology directions. Fortunately, these people need not worry. The learning curve is valid forever (when measured in constant currency, corrected for governmentally-induced inflation) as long as free market economics prevail, i.e., negligible trade barriers, no regulatory price controls, etc.

In 1825, Benjamin Gompertz proposed a mathematical model for time series that looks like an ‘S-curve’. The Gompertz Curve has been used for a variety of time dependent models, including the growth of tumors, population growth and financial market evolution.

The actual rate of growth of shipments of silicon transistors is predicted to increase until about 2038. At that time, the Gompertz Curve suggests that the increase in the rate of growth will become zero, and the rate of increase will be less each year, until we reach saturation, sometime in the 2050 or 2060 timeframe. By then, we should have developed lots of alternatives.

In another chapter, there is a graph detailing how the top 50 semiconductor companies’ share of the market has decreased 10 points in 10 years. He adds that it’s difficult for semiconductor companies to re-invent themselves as new growth markets emerge. Large semiconductor companies tend to grow at about the overall semiconductor market average growth rate, while the new entrants grow much faster, albeit from a smaller revenue base. Gradually, these small companies climb the ranks on their way to top 10.

Elsewhere, he talks about how EDA has evolved to an extent that the complex chips with tens of billions of transistors frequently produce first pass functional prototypes from the manufacturer.

International semiconductor competition
Later, he touches upon the international semiconductor competition. Semiconductor industry evolution was largely a US phenomenon. Japan became a significant competitor, especially in the late 1970s, and early 1980s. Then came Korea. Next, there was the evolution of worldwide leadership in the silicon foundry business by Taiwan, which is truly remarkable. TSMC also recognized the value of being a dedicated foundry, with no products of its own to compete with its customers.

Despite China’s rise as the world’s largest assembler of consumer electronic equipment, the Chinese semiconductor industry has evolved slowly. The largest Chinese semiconductor foundry, SMIC, is said to be two technology nodes behind TSMC in manufacturing capability, as of 2019. The Chinese government is dedicated to changing this situation.

China has done the expected. They have focused upon developing non-US capabilities for all their components. Since China buys more than 50 percent of all semiconductor components in the world, and uses more than 15 percent of the world’s semiconductor supply in equipment designed by Chinese companies, this is now a big problem for the US semiconductor industry. It is probably not reversible.

While China’s direction is not likely to change, we still have the possibility of convincing the rest of the world that the US can be treated as a reliable supplier. Hopefully, there will be policies articulated by the US that convey that confidence, and restore the US position as a leader in free trade.

AI, edge computing and 5G
Towards the end of this engrossing book, Dr. Rhines touches upon artificial intelligence (AI). He says, and I agree, that AI is not a new technology. Here is the cover of High Technology magazine in July 1986. Dr. Rhines is the person on the left, and George Heilmeier, former head of DARPA, is on the right. “We tried hard in the 1980s, but the infrastructure had not developed to a level where AI would provide profitable opportunities,” he added.

Today we have overcome all these limitations. AI and ML have taken on a life of their own. They have become limited, however, by the processing power available. Traditional von Neuman general-purpose computing architectures are inadequate to handle the complex AI algorithms. The result: a new generation of computer architecture is evolving.

On edge computing, he says that the edge nodes will require mixed technologies. Simulating digital logic connected to analog, RF and other technologies is not easy. A whole new family of EDA tools is required.

One of the great opportunities for the semiconductor industry is the increased number of base stations required to support the infrastructure of 5G and the larger number of antennas in a phone. It’s likely that about a dozen companies will lead the way in supplying the complex image processing subsystems required for autonomous vehicles.

May I take this opportunity to thank Dr. Wally Rhines for sending me a copy of this superb book. Friends, you can read this too on SemiWiki. It’s really a brilliant read! Enjoy! 🙂