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Algorithmic Building Blocks for Asymmetric Memories

Authors Yan Gu, Yihan Sun, Guy E. Blelloch

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Yan Gu
  • Carnegie Mellon University, Pittsburgh, PA, USA
Yihan Sun
  • Carnegie Mellon University, Pittsburgh, PA, USA
Guy E. Blelloch
  • Carnegie Mellon University, Pittsburgh, PA, USA

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Yan Gu, Yihan Sun, and Guy E. Blelloch. Algorithmic Building Blocks for Asymmetric Memories. In 26th Annual European Symposium on Algorithms (ESA 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 112, pp. 44:1-44:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018) https://doi.org/10.4230/LIPIcs.ESA.2018.44

Abstract

The future of main memory appears to lie in the direction of new non-volatile memory technologies that provide strong capacity-to-performance ratios, but have write operations that are much more expensive than reads in terms of energy, bandwidth, and latency. This asymmetry can have a significant effect on algorithm design, and in many cases it is possible to reduce writes at the cost of more reads. This paper studies which algorithmic techniques are useful in designing practical write-efficient algorithms. We focus on several fundamental algorithmic building blocks including unordered set/map implemented using hash tables, comparison sort, and graph traversal algorithms including breadth-first search and Dijkstra's algorithm. We introduce new algorithms and implementations that can reduce writes, and analyze the performance experimentally using a software simulator. Finally, we summarize interesting lessons and directions in designing write-efficient algorithms that can be valuable to share.

Subject Classification

ACM Subject Classification
  • Theory of computation → Models of computation
  • Theory of computation → Design and analysis of algorithms
Keywords
  • Asymmetric Memory
  • I/O Cost
  • Write-Efficient Algorithms
  • Hash Tables
  • Graph-Traversal Algorithms

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