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

May 17, 2017 Β· Declared Dead Β· πŸ› APSIPA Transactions on Signal and Information Processing

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Authors Chien-Ping Lu arXiv ID 1705.05983 Category cs.AI: Artificial Intelligence Citations 11 Venue APSIPA Transactions on Signal and Information Processing Last Checked 4 months ago
Abstract
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.
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