Improved parallel optimal choropleth map classification

Jason Laura; Sergio J. Rey

doi:10.1007/978-1-4614-8745-6_15

Improved parallel optimal choropleth map classification

Jason Laura, Sergio J. Rey

Research output: Chapter in Book/Report/Conference proceeding › Chapter

3 Scopus citations

Abstract

In this chapter we introduce an improved parallel optimal choropleth map classification algorithm to support spatial analysis. This work contributes to the development of a Distributed Geospatial CyberInfrastructure and offers an implementation of the Fisher-Jenks optimal classification method suitable for multi-core desktop environments. We provide a description of both a single-core vectorized implementation and a parallelized implementation. Our results show that single core vectorization alone provides computational speedups compared to previous parallel implementations and that a combined, parallel and vectorized, implementation offers significant speed improvements.

Original language	English (US)
Title of host publication	Modern accelerator technologies for geographic information science
Publisher	Springer US
Pages	197-212
Number of pages	16
Volume	9781461487456
ISBN (Electronic)	9781461487456
ISBN (Print)	1461487447, 9781461487449
DOIs	https://doi.org/10.1007/978-1-4614-8745-6_15
State	Published - Aug 1 2013

Keywords

Parallelization •
PySAL
Spatial analysis •
Vectorization •

ASJC Scopus subject areas

General Computer Science

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10.1007/978-1-4614-8745-6_15

Cite this

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AU - Rey, Sergio J.

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AB - In this chapter we introduce an improved parallel optimal choropleth map classification algorithm to support spatial analysis. This work contributes to the development of a Distributed Geospatial CyberInfrastructure and offers an implementation of the Fisher-Jenks optimal classification method suitable for multi-core desktop environments. We provide a description of both a single-core vectorized implementation and a parallelized implementation. Our results show that single core vectorization alone provides computational speedups compared to previous parallel implementations and that a combined, parallel and vectorized, implementation offers significant speed improvements.

KW - Parallelization •

KW - PySAL

KW - Spatial analysis •

KW - Vectorization •

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M3 - Chapter

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SN - 1461487447

SN - 9781461487449

VL - 9781461487456

SP - 197

EP - 212

BT - Modern accelerator technologies for geographic information science

PB - Springer US

ER -

Improved parallel optimal choropleth map classification

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

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