In this paper, we design parallel write-efficient geometric algorithms
that perform asymptotically fewer writes than standard
algorithms for the same problem. This is motivated by emerging
non-volatile memory technologies with read performance being
close to that of random access memory but writes being significantly
more expensive in terms of energy and latency. We design
algorithms for planar Delaunay triangulation, k-d trees, and static
and dynamic augmented trees. Our algorithms are designed in
the recently introduced Asymmetric Nested-Parallel Model, which
captures the parallel setting in which there is a small symmetric
memory where reads and writes are unit cost as well as a large
asymmetric memory where writes are ω times more expensive
than reads. In designing these algorithms, we introduce several
techniques for obtaining write-efficiency, including DAG tracing,
prefix doubling, and α-labeling, which we believe will be useful for
designing other parallel write-efficient algorithms.
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Algorithmic Building Blocks for Asymmetric Memories
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.
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- Award ID(s):
- 1533858
- NSF-PAR ID:
- 10080525
- Date Published:
- Journal Name:
- 26th Annual European Symposium on Algorithms (ESA 2018)
- Page Range / eLocation ID:
- 44:1--44:15
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.4230/LIPIcs.ESA.2018.44
