Learning Memory Access Patterns

Understand

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 bottleneck of memory performance.