A Path Toward Ultra-Low-Energy Computing
Abstract
At roughly kT energy dissipation per operation, the thermodynamic energy efficiency “limits” of Moore’s Law were unimaginably far off in the 1960s. However, current computers operate at only 100-10,000 times this limit,... [ view full abstract ]
At roughly kT energy dissipation per operation, the thermodynamic energy efficiency “limits” of Moore’s Law were unimaginably far off in the 1960s. However, current computers operate at only 100-10,000 times this limit, forming an argument that historical rates of efficiency scaling must soon slow. This paper reviews the justification for the ~kT per operation limit in the context of processors for von Neumann-class computer architectures of the 1960s. We then reapply the fundamental arguments to contemporary applications and identify a new direction for future computing in which the ultimate efficiency limits would be much further out. New nanodevices with high-level functions that aggregate the functionality of several logic gates and some local memory may be the right building blocks for much more energy efficient execution of emerging applications—such as neural networks.
Authors
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Erik DeBenedictis
(Sandia National Laboratories)
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Michael Frank
(Sandia National Laboratories)
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Natesh Ganesh
(University of Massachusetts)
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Neal Anderson
(University of Massachusetts)
Topic Areas
Topics: Neuromorphic, or “brain inspired”, computing , Topics: Reversible and adiabatic computing , Topics: In-memory processing
Session
OS-02A » Adiabatic and reversible computation (13:15 - Monday, 17th October, Del Mar Ballroom C)
Paper
ID028_ICRC2016_final.pdf
Presentation Files
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