AI, Native Supercomputing and The Revival of Moore's Law

05/17/2017
by   Chien-Ping Lu, et al.
0

Based on Alan Turing's proposition on AI and computing machinery, which shaped Computing as we know it today, the new AI computing machinery should comprise a universal computer and a universal learning machine. The later should understand linear algebra natively to overcome the slowdown of Moore's law. In such a universal learnig machine, a computing unit does not need to keep the legacy of a universal computing core. The data can be distributed to the computing units, and the results can be collected from them through Collective Streaming, reminiscent of Collective Communication in Supercomputing. It is not necessary to use a GPU-like deep memory hierarchy, nor a TPU-like fine-grain mesh.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 14

10/16/2021

What can we learn from universal Turing machines?

In the present paper, we construct what we call a pedagogical universal ...
05/05/2014

Universal Memcomputing Machines

We introduce the notion of universal memcomputing machines (UMMs): a cla...
06/30/2020

Conscious Intelligence Requires Lifelong Autonomous Programming For General Purposes

Universal Turing Machines [29, 10, 18] are well known in computer scienc...
11/09/2021

Turing-Universal Learners with Optimal Scaling Laws

For a given distribution, learning algorithm, and performance metric, th...
10/02/2021

Induction, Popper, and machine learning

Francis Bacon popularized the idea that science is based on a process of...
04/27/2018

How does the AI understand what's going on

Most researchers regard AI as a static function without memory. This is ...
11/22/2021

Universal Swarm Computing by Nanorobots

Realization of universal computing units for nanorobots is highly promis...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.