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The future of main memory appears to lie in the direction of new non-volatilememory technologies that provide strong capacity-to-performance ratios, buthave write operations that are much more expensive than reads in terms ofenergy, bandwidth, and latency. This asymmetry can have a significant effect onalgorithm design, and in many cases it is possible to reduce writes at the costof reads. In this paper, we study which algorithmic techniques are useful indesigning practical write-efficient algorithms. We focus on several fundamentalalgorithmic building blocks including unordered set/map implemented using hashtables, ordered set/map implemented using various binary search trees,comparison sort, and graph traversal algorithms including breadth-first searchand Dijkstra's algorithm. We introduce new algorithms and implementations thatcan reduce writes, and analyze the performance experimentally using a softwaresimulator. Finally we summarize interesting lessons and directions in designingwrite-efficient algorithms.

Algorithmic Building Blocks for Asymmetric Memories