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Learning Memory Access Patterns
[article]
2018
arXiv
pre-print
The explosion in workload complexity and the recent slow-down in Moore's law scaling call for new approaches towards efficient computing. Researchers are now beginning to use recent advances in machine learning in software optimizations, augmenting or replacing traditional heuristics and data structures. However, the space of machine learning for computer hardware architecture is only lightly explored. In this paper, we demonstrate the potential of deep learning to address the von Neumann
arXiv:1803.02329v1
fatcat:35topihcwvgdtc2udajbkptbmi