Shrinking Artificial Intelligence: Energy concerns push AI optimizations to the edge.
The article examines the energy consumption of artificial intelligence technology with a focus on the relationship between deep neural networks and Moore's Law. Energy consumption and latency of logic circuits are compared with that of memory transfers within an edge computing context along with oth...
| Publicado en: | Communications of the ACM Vol. 65; no. 1; pp. 12 - 15 |
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| Formato: | Artículo |
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Association for Computing Machinery
Jan2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| Sumario: | The article examines the energy consumption of artificial intelligence technology with a focus on the relationship between deep neural networks and Moore's Law. Energy consumption and latency of logic circuits are compared with that of memory transfers within an edge computing context along with other strategies to reduce the energy consumption of software execution such as data compression, precision reduction, and elimination of neural redundancy. |
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