Generalizable Reinforcement Learning-Based Coarsening Model for Resource Allocation over Large and Diverse Stream Processing Graphs (Englisch)
- Neue Suche nach: Nie, Lanshun
- Neue Suche nach: Qiu, Yuqi
- Neue Suche nach: Meng, Fei
- Neue Suche nach: Yu, Mo
- Neue Suche nach: Li, Jing
- Neue Suche nach: Nie, Lanshun
- Neue Suche nach: Qiu, Yuqi
- Neue Suche nach: Meng, Fei
- Neue Suche nach: Yu, Mo
- Neue Suche nach: Li, Jing
In:
2023 IEEE International Parallel and Distributed Processing Symposium (IPDPS)
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435-445
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2023
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ISBN:
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ISSN:
- Aufsatz (Konferenz) / Elektronische Ressource
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Titel:Generalizable Reinforcement Learning-Based Coarsening Model for Resource Allocation over Large and Diverse Stream Processing Graphs
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Beteiligte:Nie, Lanshun ( Autor:in ) / Qiu, Yuqi ( Autor:in ) / Meng, Fei ( Autor:in ) / Yu, Mo ( Autor:in ) / Li, Jing ( Autor:in )
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Erschienen in:
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Verlag:
- Neue Suche nach: IEEE
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Erscheinungsdatum:01.05.2023
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Format / Umfang:3229078 byte
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ISBN:
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ISSN:
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DOI:
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Medientyp:Aufsatz (Konferenz)
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Format:Elektronische Ressource
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Sprache:Englisch
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Datenquelle:
Inhaltsverzeichnis Konferenzband
Die Inhaltsverzeichnisse werden automatisch erzeugt und basieren auf den im Index des TIB-Portals verfügbaren Einzelnachweisen der enthaltenen Beiträge. Die Anzeige der Inhaltsverzeichnisse kann daher unvollständig oder lückenhaft sein.
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Keynote: Fifty Years of Parallel Programming: Ieri, Oggi, Domani or Yesterday, Today, Tomorrow| 2023
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Title Page i| 2023
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Title Page iii| 2023
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Copyright Page| 2023
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Table of Contents| 2023
- 13
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Message from the IPDPS 2023 General Co-chairs| 2023
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Message from the IPDPS 2023 Program Chairs| 2023
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IPDPS 2023 Technical Program| 2023
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IPDPS 2023 Organization| 2023
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Traversing Large Compressed Graphs on GPUsGera, Prasun / Kim, Hyesoon et al. | 2023
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IPDPS 2023 Technical Program Committee| 2023
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Generalizable Reinforcement Learning-Based Coarsening Model for Resource Allocation over Large and Diverse Stream Processing GraphsNie, Lanshun / Qiu, Yuqi / Meng, Fei / Yu, Mo / Li, Jing et al. | 2023
- 446
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- 798
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- 809
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- 820
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- 831
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- 842
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- 853
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- 864
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FIRST: Exploiting the Multi-Dimensional Attributes of Functions for Power-Aware Serverless ComputingZhang, Lu / Li, Chao / Wang, Xinkai / Feng, Weiqi / Yu, Zheng / Chen, Quan / Leng, Jingwen / Guo, Minyi / Yang, Pu / Yue, Shang et al. | 2023
- 875
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Duo: Improving Data Sharing of Stateful Serverless Applications by Efficiently Caching Multi-Read DataHuang, Zhuo / Fan, Hao / Cheng, Chaoyi / Wu, Song / Jin, Hai et al. | 2023
- 886
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- 897
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rFaaS: Enabling High Performance Serverless with RDMA and LeasesCopik, Marcin / Taranov, Konstantin / Calotoiu, Alexandru / Hoefler, Torsten et al. | 2023
- 908
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- 918
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- 929
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- 940
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- 951
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- 963
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RT-DBSCAN: Accelerating DBSCAN using Ray Tracing HardwareNagarajan, Vani / Kulkarni, Milind et al. | 2023
- 974
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- 985
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LowFive: In Situ Data Transport for High-Performance WorkflowsPeterka, Tom / Morozov, Dmitriy / Nigmetov, Arnur / Yildiz, Orcun / Nicolae, Bogdan / Davis, Philip E. et al. | 2023
- 996
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MCR-DL: Mix-and-Match Communication Runtime for Deep LearningAnthony, Quentin / Awan, Ammar Ahmad / Rasley, Jeff / He, Yuxiong / Shafi, Aamir / Abduljabbar, Mustafa / Subramoni, Hari / Panda, Dhabaleswar et al. | 2023
- 1007
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Lossy Scientific Data Compression With SPERRLi, Shaomeng / Lindstrom, Peter / Clyne, John et al. | 2023
- 1018
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Fast And Automatic Floating Point Error Analysis With CHEF-FPSingh, Garima / Kundu, Baidyanath / Menon, Harshitha / Penev, Alexander / Lange, David J. / Vassilev, Vassil et al. | 2023
- 1029
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- 1041
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ZFP-X: Efficient Embedded Coding for Accelerating Lossy Floating Point CompressionLu, Bing / Li, Yida / Wang, Junqi / Luo, Huizhang / Li, Kenli et al. | 2023
- 1051
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Author Index| 2023