A Survey of Near-Data Processing Architectures for Neural Networks
Data-intensive workloads and applications, such as machine learning (ML), are fundamentally limited by traditional computing systems based on the von-Neumann architecture. As data movement operations and energy consumption become key bottlenecks in the design of computing systems, the interest in un...
Main Authors: | Mehdi Hassanpour, Marc Riera, Antonio González |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-01-01
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Series: | Machine Learning and Knowledge Extraction |
Subjects: | |
Online Access: | https://www.mdpi.com/2504-4990/4/1/4 |
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