TY - GEN
T1 - Scheduling divisible loads on heterogeneous linear networks using pipelined communications
AU - Chen, Chi Yeh
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/8/30
Y1 - 2017/8/30
N2 - This work considers the divisible load distribution problem on heterogeneous linear networks. A divisible load distribution determines optimal fractions of the load and assigns them to more than one processor for minimizing the parallel execution time. Two algorithms P (pipelined communication) and M (modified method) have been proposed. The algorithm P employs the pipelined communication technique in the design. The algorithm M uses a modified method to improve the algorithm P. Closed-form expressions for the parallel processing time and speed-up are derived. In homogeneous linear networks, this work demonstrates that the pipelined communication technique outperforms the send-and-receive strategy. In heterogeneous linear networks, experiments show that the proposed algorithms are better than the send-and-receive strategy. The algorithm M is better than algorithm P when the computation-to-communication ratio is large or the number of processors is small.
AB - This work considers the divisible load distribution problem on heterogeneous linear networks. A divisible load distribution determines optimal fractions of the load and assigns them to more than one processor for minimizing the parallel execution time. Two algorithms P (pipelined communication) and M (modified method) have been proposed. The algorithm P employs the pipelined communication technique in the design. The algorithm M uses a modified method to improve the algorithm P. Closed-form expressions for the parallel processing time and speed-up are derived. In homogeneous linear networks, this work demonstrates that the pipelined communication technique outperforms the send-and-receive strategy. In heterogeneous linear networks, experiments show that the proposed algorithms are better than the send-and-receive strategy. The algorithm M is better than algorithm P when the computation-to-communication ratio is large or the number of processors is small.
UR - https://www.scopus.com/pages/publications/85030833994
UR - https://www.scopus.com/pages/publications/85030833994#tab=citedBy
U2 - 10.1109/IFSA-SCIS.2017.8023321
DO - 10.1109/IFSA-SCIS.2017.8023321
M3 - Conference contribution
AN - SCOPUS:85030833994
T3 - IFSA-SCIS 2017 - Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems
BT - IFSA-SCIS 2017 - Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 17th Joint World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems, IFSA-SCIS 2017
Y2 - 27 June 2017 through 30 June 2017
ER -