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Orcun Yildiz
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2020 – today
- 2024
- [j7]Orcun Yildiz, Amal Gueroudji
, Julien Bigot, Bruno Raffin, Rosa M. Badia, Tom Peterka:
Extreme-scale workflows: A perspective from the JLESC international community. Future Gener. Comput. Syst. 161: 502-513 (2024) - [c14]Jie Ye
Viper: A High-Performance I/O Framework for Transparently Updating, Storing, and Transferring Deep Neural Network Models. ICPP 2024: 812-821 - [i1]Orcun Yildiz, Dmitriy Morozov, Arnur Nigmetov, Bogdan Nicolae, Tom Peterka:
Wilkins: HPC In Situ Workflows Made Easy. CoRR abs/2404.03591 (2024) - 2023
- [c13]Tom Peterka, Dmitriy Morozov, Arnur Nigmetov, Orcun Yildiz, Bogdan Nicolae, Philip E. Davis:
LowFive: In Situ Data Transport for High-Performance Workflows. IPDPS 2023: 985-995 - 2022
- [c12]Tu Mai Anh Do, Loïc Pottier, Orcun Yildiz, Karan Vahi, Patrycja Krawczuk, Tom Peterka, Ewa Deelman:
Accelerating Scientific Workflows on HPC Platforms with In Situ Processing. CCGRID 2022: 1-10 - [c11]Bogdan Nicolae
Towards Low-Overhead Resilience for Data Parallel Deep Learning. CCGRID 2022: 336-345 - [c10]Orcun Yildiz, Henry Chan, Krishnan Raghavan, William Judge, Mathew J. Cherukara, Prasanna Balaprakash, Subramanian Sankaranarayanan, Tom Peterka:
Automated Continual Learning of Defect Identification in Coherent Diffraction Imaging. AI4S 2022: 1-6 - 2021
- [c9]Tanner Hobson
Shared-Memory Communication for Containerized Workflows. CCGRID 2021: 123-132 - [c8]Orcun Yildiz, Dmitriy Morozov, Bogdan Nicolae, Tom Peterka:
Dynamic Heterogeneous Task Specification and Execution for In Situ Workflows. WORKS 2021: 25-32
2010 – 2019
- 2019
- [j6]Silvina Caíno-Lores
Toward High-Performance Computing and Big Data Analytics Convergence: The Case of Spark-DIY. IEEE Access 7: 156929-156955 (2019) - [j5]Orcun Yildiz
Heterogeneous Hierarchical Workflow Composition. Comput. Sci. Eng. 21(4): 76-86 (2019) - [c7]Matthieu Dorier
The challenges of elastic in situ analysis and visualization. ISAV@SC 2019: 23-28 - 2018
- [j4]Orcun Yildiz, Amelie Chi Zhou, Shadi Ibrahim:
Improving the Effectiveness of Burst Buffers for Big Data Processing in HPC Systems with Eley. Future Gener. Comput. Syst. 86: 308-318 (2018) - [c6]Silvina Caíno-Lores, Jesús Carretero
Spark-DIY: A Framework for Interoperable Spark Operations with High Performance Block-Based Data Models. BDCAT 2018: 1-10 - [c5]Orcun Yildiz, Shadi Ibrahim:
On the Performance of Spark on HPC Systems: Towards a Complete Picture. SCFA 2018: 70-89 - 2017
- [b1]Orcun Yildiz:
Efficient Big Data Processing on Large-Scale Shared Platforms: Managing I/Os and Failures. (Sur l'efficacité des traitements Big Data sur les plateformes partagées à grande échelle: gestion des entrées-sorties et des pannes). École normale supérieure de Rennes, France, 2017 - [j3]Orcun Yildiz, Shadi Ibrahim, Gabriel Antoniu:
Enabling fast failure recovery in shared Hadoop clusters: Towards failure-aware scheduling. Future Gener. Comput. Syst. 74: 208-219 (2017) - [c4]Orcun Yildiz, Amelie Chi Zhou, Shadi Ibrahim:
Eley: On the Effectiveness of Burst Buffers for Big Data Processing in HPC Systems. CLUSTER 2017: 87-91 - 2016
- [j2]Matthieu Dorier
On the energy footprint of I/O management in Exascale HPC systems. Future Gener. Comput. Syst. 62: 17-28 (2016) - [j1]Matthieu Dorier
Damaris: Addressing Performance Variability in Data Management for Post-Petascale Simulations. ACM Trans. Parallel Comput. 3(3): 15:1-15:43 (2016) - [c3]Orcun Yildiz, Matthieu Dorier
On the Root Causes of Cross-Application I/O Interference in HPC Storage Systems. IPDPS 2016: 750-759 - 2015
- [c2]Orcun Yildiz, Shadi Ibrahim, Tran Anh Phuong, Gabriel Antoniu:
Chronos: Failure-aware scheduling in shared Hadoop clusters. IEEE BigData 2015: 313-318 - 2014
- [c1]Orcun Yildiz, Matthieu Dorier
A performance and energy analysis of I/O management approaches for exascale systems. DICT@HPDC 2014: 35-40
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last updated on 2024-10-07 21:20 CEST by the dblp team
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