TY - GEN

T1 - The Construction of the Parallel Algorithm Execution Schedule Taking into Account the Interprocessor Data Transfer

AU - Shichkina, Yulia

AU - Haidar Awadh, Al-Mardi Mohammed

AU - Storubluvchev, Nikita

AU - Degtyarev, Alexander

N1 - Shichkina Y., Awadh AM.M.H., Storublevtcev N., Degtyarev A. (2018) The Construction of the Parallel Algorithm Execution Schedule Taking into Account the Interprocessor Data Transfer. In: Gervasi O. et al. (eds) Computational Science and Its Applications – ICCSA 2018. ICCSA 2018. Lecture Notes in Computer Science, vol 10963. Springer, Cham. https://doi.org/10.1007/978-3-319-95171-3_6

PY - 2018

Y1 - 2018

N2 - The method of constructing a schedule for parallel algorithm execution is considered in the article. This algorithm takes into account the execution time of each operation of the algorithm and the relationship of operations on the data. The method is based on an information graph in which the nodes are the operations of the algorithm, and the edges are the directions of the data transfer. As a result of the interchange of operations between computing nodes, it is possible to achieve a reduction in the execution time of the algorithm by reducing the time spent on data transfer between computing nodes and reducing the downtime of computational nodes. The algorithm can be applied both in parallel programming and in adjacent areas, for example, when scheduling tasks in distributed systems.

AB - The method of constructing a schedule for parallel algorithm execution is considered in the article. This algorithm takes into account the execution time of each operation of the algorithm and the relationship of operations on the data. The method is based on an information graph in which the nodes are the operations of the algorithm, and the edges are the directions of the data transfer. As a result of the interchange of operations between computing nodes, it is possible to achieve a reduction in the execution time of the algorithm by reducing the time spent on data transfer between computing nodes and reducing the downtime of computational nodes. The algorithm can be applied both in parallel programming and in adjacent areas, for example, when scheduling tasks in distributed systems.

KW - Algorithm execution schedule

KW - Algorithm optimization

KW - Information graph

KW - Interprocessor data transmission

KW - Operation execution time

KW - Parallel algorithm

KW - Process

KW - Processor

UR - http://www.scopus.com/inward/record.url?scp=85049943027&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-95171-3_6

DO - 10.1007/978-3-319-95171-3_6

M3 - Conference contribution

SN - 978-3-319-95170-6

T3 - Lecture Notes in Computer Science

SP - 61

EP - 77

BT - Computational Science and Its Applications – ICCSA 2018

PB - Springer Nature

T2 - 18th International Conference on Computational Science and Its Applications, ICCSA 2018

Y2 - 2 July 2018 through 5 July 2018

ER -