Parallelization and load balancing of a comprehensive atmospheric chemistry transport model

Chemistry transport models are generally claimed to be well suited for massively parallel processing on distributed memory architectures since the arithmetic-to-communication ratio is usually high. However, this observation proves insufficient to account for an efficient parallel performance with in...

Full description

Saved in:
Bibliographic Details
Published in:Atmospheric environment (1994) Vol. 31; no. 21; pp. 3561 - 3574
Main Author: Elbern, Hendrik
Format: Journal Article
Language:English
Published: Oxford Elsevier Ltd 01.11.1997
Elsevier Science
Subjects:
Applied sciences
Atmospheric pollution
Exact sciences and technology
Pollutants physicochemistry study: properties, effects, reactions, transport and distribution
Pollution
Mesoscale air quality modeling
message passing
grid partitioning
parallel efficiency
parallel computing
dynamic load balancing
Mesoscale
Pollutant behavior
Air pollution
Air quality
Numerical simulation
Parallel computation
Load balancing
Dynamic load
ISSN:1352-2310, 1873-2844
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Chemistry transport models are generally claimed to be well suited for massively parallel processing on distributed memory architectures since the arithmetic-to-communication ratio is usually high. However, this observation proves insufficient to account for an efficient parallel performance with increasing complexity of the model. The modeling of the local state of the atmosphere ensues very different branches of the modules' code and greater differences in the computational work load and, consequently, runtime of individual processors occur to a much larger extent during a time step than reported for meteorological models. Variable emissions, changes in actinic fluxes, and all processes associated with cloud modeling are highly variable in time and space and are identified to induce large load imbalances which severely affect the parallel efficiency. This is more so, when the model domain encompasses more heterogeneous meteorological or regional regimes, which impinge dissimilarly on simulations of atmospheric chemistry processes. These conditions hold for the EURAD model applied in this study, which covers the European continental scale as integration domain. Based on a master-worker configuration with a horizontal grid partitioning approach, a method is proposed where the integration domain of the individual processors is locally adjusted to accommodate for load imbalances. This ensures a minimal communication volume and data exchange only with the next neighbors. The interior boundary adjustments of the processors are combined with routine boundary exchange which is required each time step anyway. Two dynamic load balancing schemes were implemented and compared against a conventional equal area partition and a static load balancing scheme. The methods are devised for massively parallel distributed memory computers of both, Single and Multiple Instruction stream Multiple Data stream (SIMD, MIMD) types. A midsummer episode of highly elevated ozone concentrations over parts of Europe was taken as test case. The dynamic load balancing approaches were found to perform significantly better and reduce idle times of the processors considerably. The efficiency was raised from to 62% for a 128 processor configuration.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:1352-2310
1873-2844
DOI:10.1016/S1352-2310(97)00157-X