Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

IF value: 5.240
IF5.240
IF 5-year value: 5.768
IF 5-year
5.768
CiteScore value: 8.9
CiteScore
8.9
SNIP value: 1.713
SNIP1.713
IPP value: 5.53
IPP5.53
SJR value: 3.18
SJR3.18
Scimago H <br class='widget-line-break'>index value: 71
Scimago H
index
71
h5-index value: 51
h5-index51
Preprints
https://doi.org/10.5194/gmd-2016-204
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-2016-204
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Submitted as: development and technical paper 21 Sep 2016

Submitted as: development and technical paper | 21 Sep 2016

Review status
This preprint was under review for the journal GMD. A revision for further review has not been submitted.

Technical Note: Improving the computational efficiency of sparse matrix multiplication in linear atmospheric inverse problems

Vineet Yadav1 and Anna M. Michalak2 Vineet Yadav and Anna M. Michalak
  • 1Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, 91011, USA
  • 2Department of Global Ecology, Carnegie Institution for Science, Stanford, California, 94305, USA

Abstract. Matrix multiplication of two sparse matrices is a fundamental operation in linear Bayesian inverse problems for computing covariance matrices of observations and a posteriori uncertainties. Applications of sparse-sparse matrix multiplication algorithms for specific use-cases in such inverse problems remain unexplored. Here we present a hybrid-parallel sparse-sparse matrix multiplication approach that is more efficient by a third in terms of execution time and operation count relative to standard sparse matrix multiplication algorithms available in most libraries. Two modifications of this hybrid-parallel algorithm are also proposed for the types of operations typical of atmospheric inverse problems, which further reduce the cost of sparse matrix multiplication by yielding only upper triangular and/or dense matrices.

Vineet Yadav and Anna M. Michalak

Interactive discussion

Status: closed (peer review stopped)
Status: closed (peer review stopped)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Interactive discussion

Status: closed (peer review stopped)
Status: closed (peer review stopped)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Vineet Yadav and Anna M. Michalak

Vineet Yadav and Anna M. Michalak

Viewed

Total article views: 1,065 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
707 292 66 1,065 78 61 81
  • HTML: 707
  • PDF: 292
  • XML: 66
  • Total: 1,065
  • Supplement: 78
  • BibTeX: 61
  • EndNote: 81
Views and downloads (calculated since 21 Sep 2016)
Cumulative views and downloads (calculated since 21 Sep 2016)

Viewed (geographical distribution)

Total article views: 972 (including HTML, PDF, and XML) Thereof 969 with geography defined and 3 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved

No saved metrics found.

Discussed

No discussed metrics found.
Latest update: 28 Nov 2020
Publications Copernicus
Download
Short summary
Multiplication of two matrices that consists of few non-zero entries is a fundamental operation in problems that involve estimation of greenhouse gas fluxes from atmospheric measurements. To increase computational efficiency of estimating these quantities, modification of the standard matrix multiplication algorithm for multiplying these matrices is proposed in this research.
Multiplication of two matrices that consists of few non-zero entries is a fundamental operation...
Citation