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Applying vectorization of diagonal sparse matrix to accelerate wind field calculation.

, , , and . J. Supercomput., 73 (1): 240-258 (2017)

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Coupled Dynamic Data-Driven Framework for Forest Fire Spread Prediction., , and . DyDESS, volume 8964 of Lecture Notes in Computer Science, page 54-67. Springer, (2014)Teaching Parallel Programming in Interdisciplinary Studies., , , , , , and . Euro-Par Workshops, volume 9523 of Lecture Notes in Computer Science, page 66-77. Springer, (2015)HeDPM: load balancing of linear pipeline applications on heterogeneous systems., , , , and . J. Supercomput., 73 (9): 3738-3760 (2017)GMATE: Dynamic Tuning of Parallel Applications in Grid Environment., , , and . J. Grid Comput., 12 (2): 371-398 (2014)Scalable dynamic Monitoring, Analysis and Tuning Environment for parallel applications., , , and . J. Parallel Distributed Comput., 70 (4): 330-337 (2010)Hybrid application to accelerate wind field calculation., , and . J. Comput. Sci., (2016)A methodology for transparent knowledge specification in a dynamic tuning environment., , , and . Softw. Pract. Exp., 42 (3): 281-302 (2012)Between classical and ideal: enhancing wildland fire prediction using cluster computing., , , , and . Clust. Comput., 9 (3): 329-343 (2006)Cloud-Based Urgent Computing for Forest Fire Spread Prediction under Data Uncertainties., , , and . HiPC, page 430-435. IEEE, (2021)Teaching parallel processing: development of curriculum and software tools., , , , , , , and . ITiCSE, page 159-161. ACM, (1996)