Parallel Scientific Computing on Loosely Coupled Networks of Computers

Collignon, T.P.; Gijzen, Martin B. van

doi:10.1007/978-3-642-03344-5_4

Cited by 4 publications

(1 citation statement)

References 51 publications

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“…The energy saving elements can be segregated such as energy usage time, demand management, and cost efficiency. The proposed algorithm can be used to optimize the energy supply and contracted supplies based on the load profile of the consumers (Collignon and van Gijzen, 2010). This work provides a dynamic approach to quantify the economics that are helpful for evaluating the commercial feasibility of the proposed methodology.…”

Section: Literature Reviewmentioning

confidence: 99%

Predicting energy consumption through the LEAP model based on LMDI technique along with economic analysis: A case study

Abbas,

Waqas,

Lun

et al. 2023

Energy Exploration & Exploitation

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This research reports the implementation of logarithmic mean Divisia index (LMDI) and categorizes the growth of total energy usage in three different industrial sectors for the years of 2010 to 2021. Furthermore, it classifies and evaluates the factors influencing on energy consumption in Punjab province thru a sustainable way. The growth consumption is classified into scale influence, structure influence, and efficiency influence. Likewise, the long-term energy alternatives planning-Punjab model is executed with the energy consumption, scale impact, structure impact, and efficiency impact. Besides, comprehensive adjustment scenarios are also introduced to examine the impact of three different factors on overall energy usage. The results from the qualitative decomposition of LMDI indicate that the high scale can lead to high-energy consumption in Punjab Province. However, it can be reduced by high-efficiency reinforcement. The total energy consumption in 2024, 2036, and 2044 under reference scenario is 304.12, 460.01, and 590.04 million tons compared to structure influence analysis for slow terminology (SIAS) and comprehensive scenario. For that reason, it can predict and provide earlier energy management planning for the province. Conversely, the structure factor does not display obvious effect on the energy use. Equally, the quantitative results of the long-term energy alternative planning (LEAP) model are relatively consistent with those of LMDI model, whose advantageous impact on the structure influence is reasonably extrapolated. This phenomenon indicates that the structure influence and efficiency influence will maintain the disruptive impact on increasing overall energy use for the future perspectives. Consequently, the LEAP model predicts the energy consumption of Punjab Province among the years of 2020 to 2040 under medium-term development framework.

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Section: Literature Reviewmentioning

confidence: 99%

Predicting energy consumption through the LEAP model based on LMDI technique along with economic analysis: A case study

Abbas,

Waqas,

Lun

et al. 2023

Energy Exploration & Exploitation

View full text Add to dashboard Cite

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Influencing factors of carbon emissions in transportation industry based on CD function and LMDI decomposition model: China as an example

Liu

Zhang

et al. 2021

Environmental Impact Assessment Review

123

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Two implementations of the preconditioned conjugate gradient method on heterogeneous computing grids

Collignon¹,

Gijzen²

2010

International Journal of Applied Mathematics and Computer Science

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Efficient iterative solution of large linear systems on grid computers is a complex problem. The induced heterogeneity and volatile nature of the aggregated computational resources present numerous algorithmic challenges. This paper describes a case study regarding iterative solution of large sparse linear systems on grid computers within the software constraints of the grid middleware GridSolve and within the algorithmic constraints of preconditioned Conjugate Gradient (CG) type methods. We identify the various bottlenecks induced by the middleware and the iterative algorithm. We consider the standard CG algorithm of Hestenes and Stiefel, and as an alternative the Chronopoulos/Gear variant, a formulation that is potentially better suited for grid computing since it requires only one synchronisation point per iteration, instead of two for standard CG. In addition, we improve the computation-to-communication ratio by maximising the work in the preconditioner. In addition to these algorithmic improvements, we also try to minimise the communication overhead within the communication model currently used by the GridSolve middleware. We present numerical experiments on 3D bubbly flow problems using heterogeneous computing hardware that show lower computing times and better speed-up for the Chronopoulos/Gear variant of conjugate gradients. Finally, we suggest extensions to both the iterative algorithm and the middleware for improving granularity.

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Parallel Scientific Computing on Loosely Coupled Networks of Computers

Cited by 4 publications

References 51 publications

Predicting energy consumption through the LEAP model based on LMDI technique along with economic analysis: A case study

Predicting energy consumption through the LEAP model based on LMDI technique along with economic analysis: A case study

Influencing factors of carbon emissions in transportation industry based on CD function and LMDI decomposition model: China as an example

Two implementations of the preconditioned conjugate gradient method on heterogeneous computing grids

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