Modeling Data Flow Execution in a Parallel Environment-Reference-Cited by-同舟云学术

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Modeling Data Flow Execution in a Parallel Environment

Published:2017 Issue: Volume: Page:183-196
ISSN:0302-9743
Container-title:Big Data Analytics and Knowledge Discovery
language:
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Author:

Kougka Georgia,Gounaris Anastasios,Leser Ulf

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-64283-3_14

Reference21 articles.

1. Agrawal, K., Benoit, A., Dufossé, F., Robert, Y.: Mapping filtering streaming applications with communication costs. In: SPAA, pp. 19–28 (2009)

2. Agrawal, K., Benoit, A., Dufossé, F., Robert, Y.: Mapping filtering streaming applications. Algorithmica 62(1–2), 258–308 (2012)

3. Boehm, M., Tatikonda, S., Reinwald, B., Sen, P., Tian, Y., Burdick, D.R., Vaithyanathan, S.: Hybrid parallelization strategies for large-scale machine learning in systemML. Proc. VLDB Endow. 7(7), 553–564 (2014)

4. Chirkin, A.M., Belloum, A.S.Z., Kovalchuk, S.V., Makkes, M.X.: Execution time estimation for workflow scheduling. In: WORKS 2014, pp. 1–10 (2014)

5. Deshpande, A., Hellerstein, L.: Parallel pipelined filter ordering with precedence constraints. ACM Trans. Algorithms 8(4), 41:1–41:38 (2012)

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1. The Functional Scheme of Hardware Semafore for Parallel Computing;2022 International Russian Automation Conference (RusAutoCon);2022-09-04

2. Optimization of data flow execution in a parallel environment;Distributed and Parallel Databases;2018-08-22

3. The many faces of data-centric workflow optimization: a survey;International Journal of Data Science and Analytics;2018-03-06

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