Identification

Title

Incorporating MAGMA into the 'fields' spatial statistics package

Abstract

In this report we describe how to incorporate the Cholesky decomposition from the Matrix Algebra on GPU and Multicore Architectures (MAGMA) library into some of the calculations of the 'fields' spatial statistics package in R. We provide MAGMA installation instructions as well as demonstrations of performance when applied to simulated datasets and the CO2 dataset available in fields. While there are other spatial statistics packages in R using parallelism, such as bigGP and parspatstat, none to our knowledge directly incorporates GPUs or other coprocessors. Our code is timed on Caldera computational nodes in the National Center for Atmospheric Research's Yellowstone supercomputing environment. We find that for 40,000 x 40,000 matrices the MAGMA-accelerated decomposition has a 30.7 and 46.2 times speedup for 1 and 2 GPU implementations respectively over chol, the standard Cholesky decomposition function in R (with settings allowing R programmers to use our accelerated function like they would chol). The speedups are greater when using in-place calculations where the original matrix is overwritten and not copied. In that case, the equivalent speedups are 41.8 and 54.4 times for in place decompositions on one and two GPUs respectively. We also time a simple spatial analysis workflow with maximum likelihood estimation with up to over 23,000 observations, where accelerated workflows achieved approximately 4.2 and 4.3 times speedup when using 1 and 2 GPUs respectively over a corresponding unaccelerated workflow. As problem size increases, speedups improve, and the 2 GPU decompositions perform increasingly well compared to their corresponding 1 GPU implementations. Performance for 2 GPU decompositions is slower than with 1 GPU in some cases due to additional communication overheads and data dependencies in the Cholesky decomposition algorithm, and will be explored further in Ramakrishnaiah et al. (2015).

Resource type

document

Resource locator

Unique resource identifier

code

http://n2t.net/ark:/85065/d72j6b88

codeSpace

Dataset language

eng

Spatial reference system

code identifying the spatial reference system

Classification of spatial data and services

Topic category

geoscientificInformation

Keywords

Keyword set

keyword value

Text

originating controlled vocabulary

title

reference date

date type

publication

effective date

2016-01-01T00:00:00Z

Keyword set

keyword value

EARTH SCIENCE SERVICES > DATA ANALYSIS AND VISUALIZATION > STATISTICAL APPLICATIONS

originating controlled vocabulary

title

reference date

date type

revision

effective date

2021-09-17

Geographic location

West bounding longitude

East bounding longitude

North bounding latitude

South bounding latitude

Temporal reference

Temporal extent

Begin position

End position

Dataset reference date

date type

publication

effective date

2015-08-01T00:00:00Z

Frequency of update

Quality and validity

Lineage

Conformity

Data format

name of format

version of format

Constraints related to access and use

Constraint set

Use constraints

Copyright Author(s). This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Limitations on public access

None

Responsible organisations

Responsible party

contact position

OpenSky Support

organisation name

UCAR/NCAR - Library

full postal address

PO Box 3000

Boulder

80307-3000

email address

opensky@ucar.edu

web address

http://opensky.ucar.edu/

name: homepage

responsible party role

pointOfContact

Metadata on metadata

Metadata point of contact

contact position

OpenSky Support

organisation name

UCAR/NCAR - Library

full postal address

PO Box 3000

Boulder

80307-3000

email address

opensky@ucar.edu

web address

http://opensky.ucar.edu/

name: homepage

responsible party role

pointOfContact

Metadata date

2023-08-18T18:06:35.038989

Metadata language