Skip to main content
Top
Published in: Wireless Personal Communications 3/2022

06-09-2021

Analysis of Overall Assignment and Sorting of Tasks in Heterogeneous Computing Systems Based on Mathematical Programming Algorithms

Authors: Hengyu Tian, Jiawei Chen

Published in: Wireless Personal Communications | Issue 3/2022

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

The problem of assignment and sequencing of tasks is a very complex problem, which is related to whether the computer system can effectively exert the overall efficiency. Solving this problem can make the lowest cost and obtain the greatest benefit. However, the current algorithms for coordinating job assignment and sorting are not completely suitable for heterogeneous computing systems. In order to rationally arrange the problem of computer assignment and sorting, this paper proposes a mathematical programming algorithm to effectively solve the inadaptability of assignment and sorting to heterogeneous computing systems. This paper adopts the control variable method and the comparative analysis method, selects the mathematical programming algorithm and the genetic algorithm, the simulated annealing algorithm these two algorithms, selects the relevant performance indicators, designs the experiments to perform calculations and collects the data. Through the comparison of different algorithms in heterogeneous computing systems, it can be seen that in terms of performance, the average response time and node utilization of the three algorithms are not much different, but the availability of the mathematical programming algorithm is significantly higher than that of the other two. When the rate is 1.0, it still has an availability of 0.59. With the increase in the number of tasks and CPU utilization, the advantages of the mathematical programming algorithm are gradually becoming obvious. Although the receiving capabilities of the three algorithms are decreasing with the increase of these two indicators, when the number of tasks reaches 140, the mathematical programming algorithm can receive tasks remains at 78%, indicating that the algorithm is stable. By applying heterogeneous computing systems on different platforms, GPU and FPGA each have their own advantages. The purpose of coordinating assignments and sequencing is to better allocate resources in the future and maximize benefits. Through the study of mathematical programming algorithms, the time required to execute programs in heterogeneous computing systems can be better reduced, thereby improving the overall system effectiveness.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literature
1.
go back to reference Slupphaug, O., Imsland, L., & Foss, B. A. (2015). Uncertainty modeling and robust output feedback control of nonlinear discrete systems: A mathematical programming approach. International Journal of Robust & Nonlinear Control, 10(13), 1129–1152.MATHCrossRef Slupphaug, O., Imsland, L., & Foss, B. A. (2015). Uncertainty modeling and robust output feedback control of nonlinear discrete systems: A mathematical programming approach. International Journal of Robust & Nonlinear Control, 10(13), 1129–1152.MATHCrossRef
2.
go back to reference Kianpisheh, S., Charkari, N. M., & Kargahi, M. (2016). Ant colony based constrained workflow scheduling for heterogeneous computing systems. Cluster Computing, 19(3), 1–18.CrossRef Kianpisheh, S., Charkari, N. M., & Kargahi, M. (2016). Ant colony based constrained workflow scheduling for heterogeneous computing systems. Cluster Computing, 19(3), 1–18.CrossRef
3.
go back to reference Sadeghi, A., & Smith, S. L. (2017). Heterogeneous task allocation and sequencing via decentralized large neighborhood search. Unmanned Systems, 05(02), 1–17.CrossRef Sadeghi, A., & Smith, S. L. (2017). Heterogeneous task allocation and sequencing via decentralized large neighborhood search. Unmanned Systems, 05(02), 1–17.CrossRef
4.
go back to reference Kabiru, S., Saidu, B. M., Abdul, A. Z., et al. (2017). An optimal assignment schedule of staff-subject allocation. Journal of Mathematical Finance, 7(4), 805–820.CrossRef Kabiru, S., Saidu, B. M., Abdul, A. Z., et al. (2017). An optimal assignment schedule of staff-subject allocation. Journal of Mathematical Finance, 7(4), 805–820.CrossRef
5.
go back to reference Seng, D. W., Li, J. W., Fang, X. J., et al. (2018). Low-carbon flexible job-shop scheduling based on improved nondominated sorting genetic algorithm-II. International Journal of Simulation Modelling, 17(4), 712–723.CrossRef Seng, D. W., Li, J. W., Fang, X. J., et al. (2018). Low-carbon flexible job-shop scheduling based on improved nondominated sorting genetic algorithm-II. International Journal of Simulation Modelling, 17(4), 712–723.CrossRef
6.
go back to reference Ali, G., Akram, M., & Alcantud, J. C. R. (2020). Attributes reductions of bipolar fuzzy relation decision systems. Neural Computing and Applications, 32, 10051–10071.CrossRef Ali, G., Akram, M., & Alcantud, J. C. R. (2020). Attributes reductions of bipolar fuzzy relation decision systems. Neural Computing and Applications, 32, 10051–10071.CrossRef
7.
go back to reference Taktak, R., & D’Ambrosio, C. (2016). An overview on mathematical programming approaches for the deterministic unit commitment problem in hydro valleys. Energy Systems, 8(1), 57–79.CrossRef Taktak, R., & D’Ambrosio, C. (2016). An overview on mathematical programming approaches for the deterministic unit commitment problem in hydro valleys. Energy Systems, 8(1), 57–79.CrossRef
8.
go back to reference Hadji, M., & Zeghlache, D. (2017). Mathematical programming approach for revenue maximization in cloud federations. IEEE Transactions on Cloud Computing, 5(1), 99–111.CrossRef Hadji, M., & Zeghlache, D. (2017). Mathematical programming approach for revenue maximization in cloud federations. IEEE Transactions on Cloud Computing, 5(1), 99–111.CrossRef
9.
go back to reference Guu, S. M., Mishra, S. K., & Pandey, Y. (2016). Duality for nonsmooth mathematical programming problems with equilibrium constraints. Journal of Inequalities & Applications, 2016(1), 1–15.MathSciNetMATHCrossRef Guu, S. M., Mishra, S. K., & Pandey, Y. (2016). Duality for nonsmooth mathematical programming problems with equilibrium constraints. Journal of Inequalities & Applications, 2016(1), 1–15.MathSciNetMATHCrossRef
10.
go back to reference Passchyn, W., Briskorn, D., & Spieksma, F. C. R. (2016). Mathematical programming models for lock scheduling with an emission objective. European Journal of Operational Research, 248(3), 802–814.MathSciNetMATHCrossRef Passchyn, W., Briskorn, D., & Spieksma, F. C. R. (2016). Mathematical programming models for lock scheduling with an emission objective. European Journal of Operational Research, 248(3), 802–814.MathSciNetMATHCrossRef
11.
go back to reference Ahmadi, A., & Jokar, M. (2016). An efficient multiple-stage mathematical programming method for advanced single and multi-floor facility layout problems. Applied Mathematical Modelling, 40(9–10), 5605–5620.MathSciNetMATHCrossRef Ahmadi, A., & Jokar, M. (2016). An efficient multiple-stage mathematical programming method for advanced single and multi-floor facility layout problems. Applied Mathematical Modelling, 40(9–10), 5605–5620.MathSciNetMATHCrossRef
12.
go back to reference Scholz, A., Henn, S., Stuhlmann, M., et al. (2016). A new mathematical programming formulation for the single-picker routing problem. European Journal of Operational Research, 253(1), 68–84.MathSciNetMATHCrossRef Scholz, A., Henn, S., Stuhlmann, M., et al. (2016). A new mathematical programming formulation for the single-picker routing problem. European Journal of Operational Research, 253(1), 68–84.MathSciNetMATHCrossRef
13.
go back to reference Wang, S., Li, K., Jing, M., et al. (2016). A reliability-aware task scheduling algorithm based on replication on heterogeneous computing systems. Journal of Grid Computing, 15(1), 1–17.CrossRef Wang, S., Li, K., Jing, M., et al. (2016). A reliability-aware task scheduling algorithm based on replication on heterogeneous computing systems. Journal of Grid Computing, 15(1), 1–17.CrossRef
14.
go back to reference Yuan, S., Deng, G., Feng, Q., et al. (2017). Multi-objective evolutionary algorithm based on decomposition for energy-aware scheduling in heterogeneous computing systems. Journal of Universal Computer ence, 23(7), 636–651. Yuan, S., Deng, G., Feng, Q., et al. (2017). Multi-objective evolutionary algorithm based on decomposition for energy-aware scheduling in heterogeneous computing systems. Journal of Universal Computer ence, 23(7), 636–651.
15.
go back to reference Hazarika, A., Poddar, S., et al. (2020). Survey on memory management techniques in heterogeneous computing systems. IET Computers & Digital Techniques, 14(2), 47–60.CrossRef Hazarika, A., Poddar, S., et al. (2020). Survey on memory management techniques in heterogeneous computing systems. IET Computers & Digital Techniques, 14(2), 47–60.CrossRef
16.
go back to reference Quan, Z., Wang, Z. J., Ye, T., et al. (2020). Task scheduling for energy consumption constrained parallel applications on heterogeneous computing systems. IEEE Transactions on Parallel and Distributed Systems, 31(5), 1165–1182.CrossRef Quan, Z., Wang, Z. J., Ye, T., et al. (2020). Task scheduling for energy consumption constrained parallel applications on heterogeneous computing systems. IEEE Transactions on Parallel and Distributed Systems, 31(5), 1165–1182.CrossRef
17.
go back to reference Vucha, M., Babu, D., Rajawat, A., et al. (2017). Resources optimization methodology for heterogeneous computing system. Journal of Theoretical and Applied Information Technology, 95(22), 6068–6078. Vucha, M., Babu, D., Rajawat, A., et al. (2017). Resources optimization methodology for heterogeneous computing system. Journal of Theoretical and Applied Information Technology, 95(22), 6068–6078.
18.
go back to reference Malashenko, Y. E., & Nazarova, I. A. (2016). Control model of the phased upgrade of a heterogeneous computing system. Journal of Computer & Systems Sciences International, 55(6), 924–937.MathSciNetMATHCrossRef Malashenko, Y. E., & Nazarova, I. A. (2016). Control model of the phased upgrade of a heterogeneous computing system. Journal of Computer & Systems Sciences International, 55(6), 924–937.MathSciNetMATHCrossRef
19.
go back to reference Zamani-Gargari, M., Kalavani, F., & Zare, K. (2019). Review of impacts of static var compensator allocation on radial distribution networks. IETE Journal of Research, 65(1), 120–127.CrossRef Zamani-Gargari, M., Kalavani, F., & Zare, K. (2019). Review of impacts of static var compensator allocation on radial distribution networks. IETE Journal of Research, 65(1), 120–127.CrossRef
20.
go back to reference Dong, Y., Jing, H., Li, Y., et al. (2020). Ultrasound-elastic-image-assisted diagnosis of pulmonary nodules based on genetic algorithm. Neural Computing and Applications, 32, 18305–18314.CrossRef Dong, Y., Jing, H., Li, Y., et al. (2020). Ultrasound-elastic-image-assisted diagnosis of pulmonary nodules based on genetic algorithm. Neural Computing and Applications, 32, 18305–18314.CrossRef
21.
go back to reference Fan, B., Leng, S., et al. (2016). A dynamic bandwidth allocation algorithm in mobile networks with big data of users and networks. IEEE Network, 30(1), 6–10.CrossRef Fan, B., Leng, S., et al. (2016). A dynamic bandwidth allocation algorithm in mobile networks with big data of users and networks. IEEE Network, 30(1), 6–10.CrossRef
22.
go back to reference Chaudhary, N. I., Aslam, M. S., Baleanu, D., et al. (2020). Design of sign fractional optimization paradigms for parameter estimation of nonlinear Hammerstein systems. Neural Computing and Applications, 32, 8381–8399.CrossRef Chaudhary, N. I., Aslam, M. S., Baleanu, D., et al. (2020). Design of sign fractional optimization paradigms for parameter estimation of nonlinear Hammerstein systems. Neural Computing and Applications, 32, 8381–8399.CrossRef
23.
go back to reference Jin, O., Yamada, C., Miyagi, K., et al. (2016). Accelerating techniques for sequence alignment based on an extended NW algorithm. IEEJ Transactions on Industry Applications, 136(10), 686–691.CrossRef Jin, O., Yamada, C., Miyagi, K., et al. (2016). Accelerating techniques for sequence alignment based on an extended NW algorithm. IEEJ Transactions on Industry Applications, 136(10), 686–691.CrossRef
24.
go back to reference Wu, Y., & Liu, J. (2021). Research on college gymnastics teaching model based on multimedia image and image texture feature analysis. Discover Internet of Things, 1, 15.CrossRef Wu, Y., & Liu, J. (2021). Research on college gymnastics teaching model based on multimedia image and image texture feature analysis. Discover Internet of Things, 1, 15.CrossRef
25.
go back to reference Kharlampovich, O., Mohajeri, A., Taam, A., et al. (2017). Quadratic equations in hyperbolic groups are NP-complete. Transactions of the American Mathematical Society, 369(9), 6207–6238.MathSciNetMATHCrossRef Kharlampovich, O., Mohajeri, A., Taam, A., et al. (2017). Quadratic equations in hyperbolic groups are NP-complete. Transactions of the American Mathematical Society, 369(9), 6207–6238.MathSciNetMATHCrossRef
26.
go back to reference Kim, T., & Dong, M. (2016). An iterative Hungarian method to joint relay selection and resource allocation for D2D communications. Wireless Communications Letters IEEE, 3(6), 625–628. Kim, T., & Dong, M. (2016). An iterative Hungarian method to joint relay selection and resource allocation for D2D communications. Wireless Communications Letters IEEE, 3(6), 625–628.
27.
go back to reference Meng, Z., Hu, Q., & Dang, C. (2017). A penalty function algorithm with objective parameters for nonlinear mathematical programming. Journal of Industrial & Management Optimization, 5(3), 585–601.MathSciNetMATHCrossRef Meng, Z., Hu, Q., & Dang, C. (2017). A penalty function algorithm with objective parameters for nonlinear mathematical programming. Journal of Industrial & Management Optimization, 5(3), 585–601.MathSciNetMATHCrossRef
28.
go back to reference Dolgui, A., Kovalev, S., Kovalyov, M. Y., et al. (2018). Optimal workforce assignment to operations of a paced assembly line. European Journal of Operational Research, 264(1), 200–211.MathSciNetMATHCrossRef Dolgui, A., Kovalev, S., Kovalyov, M. Y., et al. (2018). Optimal workforce assignment to operations of a paced assembly line. European Journal of Operational Research, 264(1), 200–211.MathSciNetMATHCrossRef
29.
go back to reference Mohaqeqi, M., Nasri, M., Xu, Y., et al. (2018). Optimal harmonic period assignment: Complexity results and approximation algorithms. Real-Time Systems, 54(4), 830–860.MATHCrossRef Mohaqeqi, M., Nasri, M., Xu, Y., et al. (2018). Optimal harmonic period assignment: Complexity results and approximation algorithms. Real-Time Systems, 54(4), 830–860.MATHCrossRef
30.
go back to reference Maysami, A. M., & Salmanzadeh, H. (2017). Assigning construction tasks among a group of workers with respect to minimizing total work risk on the base of DOISIS-MODEL. Iran Occupational Health, 13(6), 98–104. Maysami, A. M., & Salmanzadeh, H. (2017). Assigning construction tasks among a group of workers with respect to minimizing total work risk on the base of DOISIS-MODEL. Iran Occupational Health, 13(6), 98–104.
Metadata
Title
Analysis of Overall Assignment and Sorting of Tasks in Heterogeneous Computing Systems Based on Mathematical Programming Algorithms
Authors
Hengyu Tian
Jiawei Chen
Publication date
06-09-2021
Publisher
Springer US
Published in
Wireless Personal Communications / Issue 3/2022
Print ISSN: 0929-6212
Electronic ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-021-09053-3

Other articles of this Issue 3/2022

Wireless Personal Communications 3/2022 Go to the issue