Gordon Moore, Intel co-founder and creator of Moore's Law, dies aged 94

Gordon Moore, Intel co-founder and creator of Moore's Law, dies aged 94

Published, 14 hours ago  in the BBC. 

Silicon Valley pioneer and philanthropist Gordon Moore has died aged 94 in Hawaii.

Mr Moore started working on semiconductors in the 1950s and co-founded the Intel Corporation.

He famously predicted that computer processing powers would double every year - later revised to every two - an insight known as Moore's Law.

That "law" became the bedrock for the computer processor industry and influenced the PC revolution.

Two decades before the computer revolution began, Moore wrote in a paper that integrated circuits would lead "to such wonders as home computers - or at least terminals connected to a central computer - automatic controls for automobiles, and personal portable communications equipment".

He observed, in the 1965 article, that thanks to technological improvements the number of transistors on microchips had roughly doubled every year since integrated circuits were invented a few years earlier.

His prediction that this would continue became known as Moore's Law, and it helped push chipmakers to target their research to make this come true.

After Moore's article was published, memory chips became more efficient and less expensive at an exponential rate. ...   '

Big Trouble with Interconnects

Technical issues with transistors in Chip Fabs influence Moore's Law.

Big Trouble in Little Interconnects   

in IEEE Spectrum by Samuel K. Moore / January 02, 2023

Interconnects—those sometimes nanometers-wide metal wires that link transistors into circuits on an IC—are in need of a major overhaul. And as chip fabs march toward the outer reaches of Moore’s Law, interconnects are also becoming the industry’s choke point.

“For some 20-25 years now, copper has been the metal of choice for interconnects. However we’re reaching a point where the scaling of copper is slowing down,” IBM’s Chris Penny, told engineers last month at the IEEE International Electron Device Meeting (IEDM). “And there is an opportunity for alternative conductors.”

Ruthenium is a leading candidate, but it’s not as simple as swapping one metal for another, according to research reported at IEDM 2022. The processes of how they’re formed on a chip must be turned upside down. These new interconnects will need a different shape and a higher density. These new interconnects will also need better insulation, lest signal-sapping capacitance take away all their advantage.

Even where the interconnects go is set to change, and soon. But studies are starting to show, the gains from that shift come with a certain cost.

Ruthenium, top vias, and air gaps

Among the replacements for copper, ruthenium has gained a following. But research is showing that the old formulas used to build copper interconnects are a disadvantage to ruthenium. Copper interconnects are built using what’s called a damascene process. First chip makers use lithography to carve the shape of the interconnect into the dielectric insulation above the transistors. Then they deposit a liner and a barrier material, which prevents copper atoms from drifting out into the rest of the chip to muck things up. Copper then fills the trench. In fact, it overfills it, so the excess must be polished away.  ....  '

More Laws of Computing

 Not so much laws, but rather general indications of past trends that may usefully hold in the future. or not.  Here some proposals for mew laws.Good for tracking against new data.  

Moore’s Not Enough: ​4 New laws of Computing Moore’s and Metcalfe’s conjectures are taught in classrooms every day—these four deserve consideration, too  by ADENEKAN DEDEKE in IEEE Spectrum.  Below an intro, much more at the link.

MOORE'S LAW METCALFE'S LAW COMPUTING

I teach technology and information-systems courses at Northeastern University, in Boston. The two most popular laws that we teach there—and, one presumes, in most other academic departments that offer these subjects—are Moore’s Law and Metcalfe’s Law. Moore’s Law, as everyone by now knows, predicts that the number of transistors on a chip will double every two years. One of the practical values of Intel cofounder Gordon Moore’s legendary law is that it enables managers and professionals to determine how long they should keep their computers. It also helps software developers to anticipate, broadly speaking, how much bigger their software releases should be.

Metcalfe’s Law is similar to Moore’s Law in that it also enables one to predict the direction of growth for a phenomenon. Based on the observations and analysis of Robert Metcalfe, co-inventor of the Ethernet and pioneering innovator in the early days of the Internet, he postulated that the value of a network would grow proportionately to the number of its users squared. A limitation of this law is that a network’s value is difficult to quantify. Furthermore, it is unclear that the growth rate of every network value changes quadratically at the power of two. Nevertheless, this law as well as Moore’s Law remain a centerpiece in both the IT industry and academic computer-science research. Both provide tremendous power to explain and predict behaviors of some seemingly incomprehensible systems and phenomena in the sometimes inscrutable information-technology world.

King Camp Gillette reduced the price of the razors, and the demand for razor blades increased. The history of IT contains numerous examples of this phenomenon, too.

I contend, moreover, that there are still other regularities in the field of computing that could also be formulated in a fashion similar to that of Moore’s and Metcalfe’s relationships. I would like to propose four such laws.

Law 1. Yule’s Law of Complementarity

I named this law after George Udny Yule (1912), who was the statistician who proposed the seminal equation for explaining the relationship between two attributes. I formulate this law as follows:   .... ' 

Intel and Quantum for Moore's Law Push

 Where the advances should come from:

Intel Eyes Quantum Realm For Breakthroughs To Propel Moore's Law Beyond 2025  In HotHardWare

A couple months ago, Intel CEO Pat Gelsinger said he would exhaust the periodic table if necessary to keep Moore's Law relevant into the future. We'll see if the engineers at Intel have to actually do that or not. Either way, Intel is confident it can propel Moore's Law beyond 2025 by tapping advances in chip packaging and pursuing breakthroughs in quantum physics.

Lest anyone thought Gelsinger was merely being hyperbolic, Intel doubled down on its "relentless pursuit of Moore's Law" during the 2021 IEEE International Electron Devices Meeting (IEDM) event, where the chip maker outlined a path to a more than 10x interconnect density improvement in packaging with hybrid bonding, as well as 30-50 percent area improvement in transistor scaling. Intel also discussed the need for "new concepts in physics" in order to "one day revolutionize computing."

"At Intel, the research and innovation necessary for advancing Moore’s Law never stops. Our Components Research Group is sharing key research breakthroughs at IEDM 2021 in bringing revolutionary process and packaging technologies to meet the insatiable demand for powerful computing that our industry and society depend on," said Robert Chau, Intel Senior Fellow and general manager of Components Research. "This is the result of our best scientists’ and engineers’ tireless work. They continue to be at the forefront of innovations for continuing Moore’s Law."

Intel credited a number of previous innovations for breaking the previous barriers of Moore's Law, including strained silicon, Hi-K metal gates, FinFET transistors, RibbonFET, and packaging innovations such as EMIB and Foveros Direct. But those will only take chip design so far.

Stacking multiple transistors will be key in "mastering the coming post-FinFET era" as Intel looks beyond RibbonFET. This is at the heart of its claimed 30-50 percent logic scaling improvement. But it's also researching how novel materials only a few atoms thick can take the company into the angstrom era.  ...' 

Decline of Computers as a General Purpose Technology

Contributed article, excerpt below in the March 2021 CACM.

My first reaction was No!  But some very good points made ... '

The Decline of Computers as a General Purpose Technology   By Neil C. Thompson, Svenja Spanuth

Communications of the ACM, March 2021, Vol. 64 No. 3, Pages 64-72  10.1145/3430936

Perhaps in no other technology has there been so many decades of large year-over-year improvements as in computing. It is estimated that a third of all productivity increases in the U.S. since 1974 have come from information technology,a,4 making it one of the largest contributors to national prosperity.

Key Insights  ...  

- Moore's Law was driven by technical achievements and a "general purpose technology" (GPT) economic cycle where market growth and investments in technical progress reinforced each other.  These created strong economic incentives for users to standardize to fast-improving CPUs, rather than designing their own specialized processors.

- Today, the GPT cycle is unwinding, resulting in less market growth and slower technical progress. 

- As CPU improvement slows, economic incentives will push users toward specialized processors, which threatens to fragment computing. In such a computing landscape, some users willbe in the 'fast lane,' benefit ing from customized hardware, and others will be left in the 'slow lane,' stuck on CPUs whose progress fades. ... 

The rise of computers is due to technical successes, but also to the economics forces that financed them. Bresnahan and Trajtenberg3 coined the term general purpose technology (GPT) for products, like computers, that have broad technical applicability and where product improvement and market growth could fuel each other for many decades. But, they also predicted that GPTs could run into challenges at the end of their life cycle: as progress slows, other technologies can displace the GPT in particular niches and undermine this economically reinforcing cycle. We are observing such a transition today as improvements in central processing units (CPUs) slow, and so applications move to specialized processors, for example, graphics processing units (GPUs), which can do fewer things than traditional universal processors, but perform those functions better. Many high profile applications are already following this trend, including deep learning (a form of machine learning) and Bitcoin mining. ... 

With this background, we can now be more precise about our thesis: "The Decline of Computers as a General Purpose Technology." We do not mean that computers, taken together, will lose technical abilities and thus 'forget' how to do some calculations. We do mean that the economic cycle that has led to the usage of a common computing platform, underpinned by rapidly improving universal processors, is giving way to a fragmentary cycle, where economics push users toward divergent computing platforms driven by special purpose processors.

This fragmentation means that parts of computing will progress at different rates. This will be fine for applications that move in the 'fast lane,' where improvements continue to be rapid, but bad for applications that no longer get to benefit from field-leaders pushing computing forward, and are thus consigned to a 'slow lane' of computing improvements. This transition may also slow the overall pace of computer improvement, jeopardizing this important source of economic prosperity.    ...."

A History and Future of Computer Hardware Capabilities

 Quite interesting talk I attended that presented how hardware, software methods and algorithms have influenced changes in architecture and speed.   Somewhat technical but instructive for anyone with an interest in the future forecasting of solving complex computational problems.

" ... Following his talk, "A New Golden Age for Computer Architecture," David Patterson was kind enough to answer some additional questions we were not able to get to during the live event. You'll find the questions and answers (including some interesting pointers) on our Discourse forum page.  

For those of you who were not able to attend live, this webcast can now be viewed on-demand.
Use the link below to enter the webcast at any time: A New Golden Age for Computer Architecture

View the most recent ACM TechTalk, "A New Golden Age for Computer Architecture," on demand. The talk was presented by David Patterson, Distinguished Engineer at Google, Professor Emeritus of Computer Science at UC Berkeley, and 2018 ACM A.M. Turing Award Laureate.  Cliff Young, Software Engineer at Google Brain, moderated the Q&A. Leave comments, questions, and check out further resources on ACM's Discourse page. ... '

Computing Beyond Moore's Law

Is hardware or software dominating?  Is brain inspiration and neurscience taking us beyond?   Will this form of bio-mimicry lead us beyond?  It should always be noted that the current neural algorithms are not accurate analogs to the way biological neurons work,  its a crude mimicry at best.  Will a more accurate biological work better?

Neural Algorithms and Computing Beyond Moore's Law
By James B. Aimone 
Communications of the ACM, April 2019, Vol. 62 No. 4, Page 110
10.1145/3231589

(Abstract, full text and references at the link)

The impending demise of Moore's Law has begun to broadly impact the computing research community.38 Moore's Law has driven the computing industry for many decades, with nearly every aspect of society benefiting from the advance of improved computing processors, sensors, and controllers. Behind these products has been a considerable research industry, with billions of dollars invested in fields ranging from computer science to electrical engineering. Fundamentally, however, the exponential growth in computing described by Moore's Law was driven by advances in materials science.30,37 From the start, the power of the computer has been limited by the density of transistors. Progressive advances in how to manipulate silicon through advancing lithography methods and new design tools have kept advancing computing in spite of perceived limitations of the dominant fabrication processes of the time.37   ... "

What will Make Future Computing more Powerful?

As Moore's law slows, what will drive new capabilities in computing?  Lots of things.  Quantum computing, new form of parallelism,  more accessible data, AI to use cognitive methods.  And more.   A decisive move from hardware to software driven value?  The Economist writes further.

Journal of Artificial Societies and Social Simulation

Was reminded of this resource recently.  Had used it to inspire some of our work with agent based models, good to see they are still going strong.  Articles vary in technical depth.   From their description:

" ... The Journal of Artificial Societies and Social Simulation is an interdisciplinary journal for the exploration and understanding of social processes by means of computer simulation. Since its first issue in 1998, it has been a world-wide leading reference for readers interested in social simulation and the application of computer simulation in  the social sciences.

Original research papers and critical reviews on all aspects of social simulation and agent societies that fall within the journal's objective to further the exploration and understanding of social processes by means of computer simulation are welcome. .... " 

 Just a few of their peer reviewed articles in the latest edition: 

An Agent-Based Model of Status Construction in Task Focused Groups
André Grow, Andreas Flache and Rafael Wittek

Self-Policing Through Norm Internalization: A Cognitive Solution to the Tragedy of the Digital Commons in Social Networks
Daniel Villatoro, Giulia Andrighetto, Rosaria Conte and Jordi Sabater-Mir

Modeling Education and Advertising with Opinion Dynamics
Thomas Moore, Patrick Finley, Nancy Brodsky, Theresa Brown, Benjamin Apelberg, Bridget Ambrose and Robert Glass

Mobilization, Flexibility of Identity, and Ethnic Cleavage
Kazuya Yamamoto

Exploring Creativity and Urban Development with Agent-Based Modeling
Ammar Malik, Andrew Crooks, Hilton Root and Melanie Swartz

How Evolutionary Dynamics Affects Network Reciprocity in Prisoner’s Dilemma
Giulio Cimini and Angel Sanchez

Innovation Suppression and Clique Evolution in Peer-Review-Based, Competitive Research Funding Systems: An Agent-Based Model
Pawel Sobkowicz

Does Longer Copyright Protection Help or Hurt Scientific Knowledge Creation?
Shahram Haydari and Rory Smead      ....  "

Moore's Law is 50

In Recode.  Been reading about Moore's law for many years.    Now over 50 years old, it maps how  " ...  the number-crunching capacity of our computers and the number of transistors on silicon chips double roughly every two years, that prediction has underpinned the unrelenting tide of technological progress. ... " .    Good background and prediction that the continuing change may soon end.

Systems to Prevent Deception Fail

A discussion of systems that are meant to prevent deception and unethical behavior.  In Knowledge@Wharton.  A topic in any system that is meant to gather human data when there are rewards and consequences.   Will cognitive science ultimately solve this?   Neuromarketing is an attempt to deal with this.  Now from a forthcoming book:

" ... Wharton professor Maurice E. Schweitzer found quite the opposite in a recent research study. He says that unethical behavior not only can leave no negative emotional reaction but also can, in fact, trigger positive feelings.

Schweitzer, along with co-authors Nicole E. Ruedy at the University of Washington Foster School of Business, Celia Moore at the London Business School and Francesca Gino at Harvard Business School, discuss this result in “The Cheater’s High: The Unexpected Affective Benefits of Unethical Behavior,” to be published in the Journal of Personality and Social Psychology. ... " 

An Age of Smart Machines

In the Economist:  Can we, will the knowledge worker be replaced and when?   Kurt Vonnegut is invoked from his novel Piano Player.   We certainly believed this in the 1980s.  .  " ... Two things are clear. The first is that smart machines are evolving at breakneck speed. Moore’s law—that the computing power available for a given price doubles about every 18 months—continues to apply. This power is leaping from desktops into people’s pockets. More than 1.1 billion people own smartphones and tablets. Manufacturers are putting smart sensors into all sorts of products. The second is that intelligent machines have reached a new social frontier: knowledge workers are now in the eye of the storm, much as stocking-weavers were in the days of Ned Ludd, the original Luddite. Bank clerks and travel agents have already been consigned to the dustbin by the thousand; teachers, researchers and writers are next. The question is whether the creation will be worth the destruction. ... " 

Singularity Rising

Moore's law and Artificial Intelligence.  What does it mean to be 'smart' for machines?  A new book:    Singularity Rising. describes the problem. What will the singularity, in whatever form it may take,  mean to human beings to human civilization?   And an interview with author James D Miller.

Moores Law Becoming Irrelevant

Has the ever increasing drumbeat to computing and data manipulation become irrelevant?  The folks behind ARM say that as processors proliferate, efficiency will become more important than raw processing power.    Its what you get done, not how fast you get it done.  More in Technology Review.

Moore's Law Survives

Have read about the imminent demise of Moore's law for some time.   Now development of new chip designs by Intel seem to say it will survive  longer yet.  " ... Moore pointed out that the number of transistors on a chip doubles every year. The current form of Moore's law has been set since 1975, when Moore altered the pace to a doubling every two years. Remarkably, the computer industry has maintained that pace ever since, training us to expect computers to become ever faster in the process .... " 

Is the Moore Party Over?

A short post in CACM on the slowdown of computing.  Or can we await quantum computing to save the day.   There are still good problems out there to address with more speed.

Toothpaste, Data and People at Procter & Gamble

An interesting and detailed article in Forbes on P&G's use of advanced data technology.  Note this work relates to another post I did about early attempts to deliver this kind of capability.  It was an idea we experimented with very early on and was supported from the executive suite down.  Large enterprises will increasingly have to make better decisions based on larger and complex data.    A surprisingly accurate view of what is going on there, quote below is just a taste.

" ... Procter & Gamble, the world’s biggest consumer products company, continues to be one of the leaders in the race to harness massive streams of data for managing a business better. The company has been profit-forecasting on a monthly basis for about 40 years, trying to predict components such as sales, commodity prices and exchange rates. But the amount of real-time data it has been able to process has increased vastly in the past three years, thanks to better software and Moore’s Law of increasing computing power. Now P&G borrows liberally from tools born on the Web: ubiquitous high-speed networking, data visualization and high-speed analysis on multiple streams of information. The tools allow P&G to make in minutes the decisions that used to take weeks or months, when data had to be collated and passed through committees on their way to the top.

With $79 billion in sales and 127,000 employees, P&G is on the verge of having everyone’s talents known and tracked, all information about sales decided at the executive level every week and production viewed in near real-time worldwide. The company talks in terms of increasing the amount of collected data sevenfold. The airy promises of networked technology are here, at a scale rarely, if ever, deployed before.

P&G has just started a “digital skills” inventory of its employees, establishing a baseline of skills, including how to get connected to the Internet, how to use basic collaboration and knowledge-exchanging tools for online meetings and mail, and how to tap into the company’s internal social network, P&G Pulse, for news and further training. There are higher expectations for more technical jobs, of course, or in grooming certain careers ... "

Transistor at 60

Its good to sit back and think about this anniversary. I remember wiring up some transistor based circuits in the 60s, but had no conception about where this would ultimately go. Packing them ever more densely and having faster switches is good, but the claim made in the excerpt below implies that this development alone will solve some remaining tough problems of our time. I don't think so. It will require some tough thinking about the methods that will use all these new chips, and making sure that future versions of Vista don't suck up all that new power.

"The Transistor at 60 (Via ACM Technews)
Sydney Morning Herald (Australia) (11/27/07) Head, Beverley

Since its debut six decades ago, transistor technology has advanced to the point where 820 million transistors can be housed on Intel's new Penryn processor. However, the shrinkage of transistors to accelerate processing speed and manage power efficiency has Intel co-founder Gordon Moore convinced that a physical barrier will be reached within the next 10 or 15 years. Not everyone agrees with Moore's assessment. "What's happened again and again when you come upon the physical limits is we've been able to advance around them, and I think that will continue for at least the next several generations," says director of IBM's Australia Development Laboratory Glenn Wightwick. Intel CTO Justin Rattner forecasts that within 10 years electronics will shift from reliance on an electron's electrostatic charge to its "spin," and perhaps usher in molecular devices. Wightwick says many research labs are investigating potential replacements for transistors, such as molecular cascades or carbon nanotubes. The trade-off with a switch to new electronic components is the cost and effort of facilitating such a transition, but users would benefit enormously because their interaction with technology would be easier thanks to single-system chips, Rattner says. He says these advances could lead to innovations such as practical machine translation, continuous speech recognition, and personal robots. "