APSIPA Transactions on Signal and Information Processing > Vol 6 > Issue 1

AI, native supercomputing and the revival of Moore's Law

Industrial Technology Advances

Chien-Ping Lu, Hardware Engineering, USA, cpl@novumind.com
 
Suggested Citation
Chien-Ping Lu (2017), "AI, native supercomputing and the revival of Moore's Law", APSIPA Transactions on Signal and Information Processing: Vol. 6: No. 1, e9. http://dx.doi.org/10.1017/ATSIP.2017.9

Publication Date: 29 Aug 2017
© 2017 Chien-Ping Lu
 
Subjects
 
Keywords
Moore's LawAIDeep LearningSupercomputingAlan Turing
 

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This is published under the terms of the Creative Commons Attribution licence.

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In this article:
I. AI AND THE UNIVERSAL COMPUTER 
II. THE PERFECT MARRIAGE BETWEEN THE UNIVERSAL COMPUTER AND MOORE'S LAW 
III. THE SLOWDOWN OF MOORE'S LAW 
IV. AI AND MOORE'S LAW 
V. DEEP LEARNING AND THE NEW AI MACHINE 
VI. SPATIAL DATAFLOW ARCHITECTURE 
VII. MATRIX MULTIPLICATION ACCORDING TO SUPERCOMPUTING 
VIII. NATIVE SUPERCOMPUTING 
IX. WHY COLLECTIVE STREAMING? 
X. CONCLUSION 

Abstract

Artificial Intelligence (AI) was the inspiration that shaped computing as we know it today. In this article, I explore why and how AI would continue to inspire computing and reinvent it when Moore's Law is running out of steam. At the dawn of computing, Alan Turing proposed that instead of comprising many different specific machines, the computing machinery for AI should be a Universal Digital Computer, modeled after human computers, which carry out calculations with pencil on paper. Based on the belief that a digital computer would be significantly faster, more diligent and patient than a human, he anticipated that AI would be advanced as software. In modern terminology, a universal computer would be designed to understand a language known as an Instruction Set Architecture (ISA), and software would be translated into the ISA. Since then, universal computers have become exponentially faster and more energy efficient through Moore's Law, while software has grown more sophisticated. Even though software has not yet made a machine think, it has been changing how we live fundamentally. The computing revolution started when the software was decoupled from the computing machinery. Since the slowdown of Moore's Law in 2005, the universal computer is no longer improving exponentially in terms of speed and energy efficiency. It has to carry ISA legacy, and cannot be aggressively modified to save energy. Turing's proposition of AI as software is challenged, and the temptation of making many domain-specific AI machines emerges. Thanks to Deep Learning, software can stay decoupled from the computing machinery in the language of linear algebra, which it has in common with supercomputing. A new universal computer for AI understands such language natively to then become a Native Supercomputer. AI has been and will still be the inspiration for computing. The quest to make machines think continues amid the slowdown of Moore's Law. AI might not only maximize the remaining benefits of Moore's Law, but also revive Moore's Law beyond current technology.

DOI:10.1017/ATSIP.2017.9