Moore’s Law – Social Blog

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Professor Li mentioned that Moore’s Law is continuing and that there is no sign of stopping. However, this depends on which angle you are looking at things. Considering the generally accepted definition of Moore’s Law, it is stated that in 1965, Gordon Moore proposed that the number of transistors on a silicon chip would double every year. Because of this, we have experienced an exponential growth of computing power that has made much of the technology of today possible.

Change from the focus on hardware to software

For over the past 50 years, the focus has been on the physical side by reducing the size of transistors. Currently, the industry has accomplished making the transistors as small as 10 nanometer, which is so small that new complications have arisen. The research and development departments are dealing with electrical leakage, increased generated heat, and expanded cost of cooling. These problems are the main causes of contributing to the slowing rate of growth in processor power. It is estimated by several experts that Moore’s Law will end around 2025 because transistors will have reached their physical limits. Will this mean that technology advancement is all gloom and doom?

Not necessarily. Because it has been relatively easy to focus on increasing processor power by expanding the number of transistors on a single chip, there never really was any incentive to optimize performance out of a single chip. As the human species naturally seeks continued advancement, I believe that pushing more performance out of the same single chip will become much higher of a priority. This could translate to better algorithms, to optimize both efficiency and speed. We simply do not have a choice. How much and for how long this switch will lead to improved performance remains to be seen.

How do you think Moore’s Law will be continued? What are your predictions regarding the impact of switching to a software focus for Moore’s Law?

Let me know in the comments below!

References:

Rotman, D. (2020). We’re not prepared for the end of Moore’s Law. Retrieved on 10 September 2020 on https://www.technologyreview.com/2020/02/24/905789/were-not-prepared-for-the-end-of-moores-law/

Loeffler, J. (2018). No more transistors: The end of Moore’s Law. Retrieved on 10 September 2020 on https://interestingengineering.com/no-more-transistors-the-end-of-moores-law

Moore, S., K. (2019). Another step toward the end of Moore’s Law. Retrieved on 11 September 2020 on https://spectrum.ieee.org/semiconductors/devices/another-step-toward-the-end-of-moores-law

Bailey, B. (2018). The impact of Moore’s Law ending. Retrieved on 11 September 2020 on https://semiengineering.com/the-impact-of-moores-law-ending/

Tardi, C. (2020). Moore’s Law. Retrieved on 12 September 2020 on https://www.investopedia.com/terms/m/mooreslaw.asp

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google-quantum-computer

The producers of processors are facing a serious problem. In a few years, building faster processors with the technology as we know it will not be possible anymore. So far, building faster processors was essentially a matter of placing as many transistors as possible on one chip. The more transistors, the faster the chip. As Gordon Moore (co-founder of Intel) observed in 1965, the number of transistors per square inch on integrated circuits had doubled every year since the integrated circuit was invented. He stated that this trend would continue for the foreseeable future. This is known as the Moore’s Law. Regarding computer processors, it is possible to upgrade their performance by building smaller transistors and placing more and more on one chip. Nevertheless, this process is about to reach its limit. As soon as chip technology reaches the atomic level, the density of transistors reaches a physical limit. To give you an idea how dense the transistors are placed, in the year of 2000, 37.5 million transistors could be placed on one chip, in 2017 IBM projects to place 20 billion (yes billion) transistors on one chip. The most recent manufacturing techniques used are performed on a 7 nanometer scale. As a comparison, a human hair is approximately 80,000- 100,000 nanometers wide. The limit where it is still feasible financially to develop a chip would be 7 nanometers. A leading scientist in the field, Colwell, emphasized that by 2020 the limit of Moore’s Law, currently about 5 nanometers, will be reached.
What does that mean for the computer industry? Will we be stuck with the same processing power for years?

There are some promising alternatives that have yet to be fully translated from theory into practice. Next to alternatives like increasing the performance of storage drives,
overclocking processors while cooling them down to almost absolute zero,
one alternative seems most assuring.
Quantum computers are what organizations like Google, IBM or the NASA are looking into.

A prototype quantum annealer by the company D-Wave, recently acquired by Google, was able to perform a task a 100
million times faster than a convential processor. Or 10,000 years faster than a convential computer. This task is not performed easily though. The quantum computer needs to be cooled to a hundredth of a degree Celsius above absolute zero (−273.15°C), in order to create a somewhat stable environment. That is the reason the quantum computers as of today are called quantum annealer. The quantum annealer is also very sensitive to electromagnetic waves, like visible light, radio, infrared or x rays. It is therefore considered to be yet extremely unstable and very costly to use. This makes it very difficult to scale, since you cannot build a laboratory around a quantum annealer every time you want to upgrade your performance.
The technique behind it is fascinating however.

Imagine a switch that you can either switch on or off. homerswitch
That is how bits of today’s computers essentially work. They can either represent a 1 or a 0.

A quantum computer bit however, called qubit, can represent a 1, a 0 or both at once. This is confusing enough, however the possibilities do not stop here. With each qubit added to another, the total number of potential states doubles. Two qubits can represent a state of 00, 01, 10 and 11 at the same time.

This is an example of so called superposition.

This opens up seemingly endless possibilities in terms of performance. It means that the more data the computer has, the faster it is.

Now remember the problems that we are not yet able to solve, since we are missing the computer performance to analyze or calculate all the variables. Popular examples are simulating molecules in their entirety, compute any scientific experiment virtually, crack any so far known encryption technique, airline scheduling, financial analysis, cancer radiotherapy, gene research or simply improve web search.

Some scientists state that the creation of the first universal quantum computer will be similar to society as switching on the first self-sustaining nuclear reaction in Chicago in 1942. That definitely changed the world as we knew it. Luckily, The most recent quantum computer are not there yet and can only be used for very narrow, specific tasks. A so called universal quantum computer however can be applied to many processes, much like a PC of today – only a million times faster.

Do you have ideas for further applications of the process powers offered by quantum computers? What are in your opinion dangers or opportunities for quantum technology? As an example, Google is on the forefront of building a quantum computer, what are Google’s capabilities with their collected data?

References

Aaronson, S., & Technology, M. I. of (2013). Quantum computing since Democritus. Cambridge, United Kingdom: Cambridge University Press.

Adiabatic quantum computation (2016). . In Wikipedia. Retrieved from https://en.wikipedia.org/wiki/Adiabatic_quantum_computation

Aron, Jacob. (2016, August 31). Revealed: Google’s plan for quantum computer supremacy. Retrieved October 1, 2016, from https://www.newscientist.com/article/mg23130894-000-revealed-googles-plan-for-quantum-computer-supremacy/

Boixo, S., Isakov, S. V., Smelyanskiy, V. N., Babbush, R., Ding, N., Jiang, Z., … Neven, H. (2016, July 31). Title: Characterizing quantum supremacy in near-term devices. Retrieved October 4, 2016, from https://arxiv.org/abs/1608.00263

Crothers, B. (2013, August 28). End of Moore’s law: It’s not just about physics. Retrieved October 4, 2016, from https://www.cnet.com/news/end-of-moores-law-its-not-just-about-physics/

Finley, K. (2014, September 5). The Internet finally belongs to everyone. Retrieved October 4, 2016, from Business, https://www.wired.com/2014/09/martinis/

Freiberger, M. (2015, October 1). What can quantum computers do? Retrieved October 4, 2016, from https://plus.maths.org/content/what-can-quantum-computers-do

Gaudin, S. (2015, December 15). Quantum computing may be moving out of science fiction. . Retrieved from http://www.computerworld.com/article/3015538/emerging-technology/quantum-computing-may-be-moving-out-of-science-fiction.html

HuChenming— (2016). Moore’s law. In Wikipedia. Retrieved from https://en.wikipedia.org/wiki/Moore%27s_law#Near-term_limits

Simonite, T. (2016, February 4). Inside Google’s quantum computing lab, Questing for the perfect computer. Retrieved October 4, 2016, from https://www.technologyreview.com/s/544421/googles-quantum-dream-machine/

Launching the quantum artificial intelligence lab. (2013, May 16). Retrieved from https://research.googleblog.com/2013/05/launching-quantum-artificial.html

Staff, datascience@berkeley. (2014, March 5). Moore’s law and computer processing power – Blog. Retrieved October 4, 2016, from https://datascience.berkeley.edu/moores-law-processing-power/

Moore’s Law from a different perspective

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Quantum computing – The next frontier after Moore’s Law?

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