Code generation for energy‐efficient execution of dynamic streaming task graphs on parallel and heterogeneous platforms-Reference-Cited by-同舟云学术

Code generation for energy‐efficient execution of dynamic streaming task graphs on parallel and heterogeneous platforms

Published:2020-11-06 Issue:2 Volume:34 Page:
ISSN:1532-0626
Container-title:Concurrency and Computation: Practice and Experience
language:en
Short-container-title:Concurrency and Computation

Author:

Litzinger Sebastian¹^ORCID,Keller Jörg¹^ORCID

Affiliation:

1. Faculty of Mathematics and Computer Science FernUniversität in Hagen Hagen Germany

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cpe.6072

Reference22 articles.

1. Exploiting coarse-grained task, data, and pipeline parallelism in stream programs

2. Handbook of Scheduling

3. Fast crown scheduling heuristics for energy‐efficient mapping and scaling of moldable streaming tasks on manycore systems;Melot N;ACM Trans Archit Code Optim,2015

4. MelotN. Algorithms and Framework for Energy Efficient Parallel Stream Computing on Many‐Core Architectures [Ph.D thesis]. Linköping UniversityLinköping Sweden;2017.

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2. Integrating Energy-Optimizing Scheduling of Moldable Streaming Tasks with Design Space Exploration for Multiple Core Types on Configurable Platforms;Journal of Signal Processing Systems;2022-06-30

3. Energy-Efficient Execution of Streaming Task Graphs with Parallelizable Tasks on Multicore Platforms with Core Failures;Euro-Par 2021: Parallel Processing Workshops;2022

4. Combining Design Space Exploration with Task Scheduling of Moldable Streaming Tasks on Reconfigurable Platforms;Applied Reconfigurable Computing. Architectures, Tools, and Applications;2021