Orcun Yildiz

Orcid: 0000-0001-9360-2489

According to our database1, Orcun Yildiz authored at least 21 papers between 2014 and 2024.

Collaborative distances:



In proceedings 
PhD thesis 


On csauthors.net:


Wilkins: HPC In Situ Workflows Made Easy.
CoRR, 2024

LowFive: In Situ Data Transport for High-Performance Workflows.
Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2023

Automated Continual Learning of Defect Identification in Coherent Diffraction Imaging.
Proceedings of the IEEE/ACM International Workshop on Artificial Intelligence and Machine Learning for Scientific Applications, 2022

Towards Low-Overhead Resilience for Data Parallel Deep Learning.
Proceedings of the 22nd IEEE International Symposium on Cluster, 2022

Accelerating Scientific Workflows on HPC Platforms with In Situ Processing.
Proceedings of the 22nd IEEE International Symposium on Cluster, 2022

Dynamic Heterogeneous Task Specification and Execution for In Situ Workflows.
Proceedings of the 2021 IEEE Workshop on Workflows in Support of Large-Scale Science (WORKS), 2021

Shared-Memory Communication for Containerized Workflows.
Proceedings of the 21st IEEE/ACM International Symposium on Cluster, 2021

Heterogeneous Hierarchical Workflow Composition.
Comput. Sci. Eng., 2019

Toward High-Performance Computing and Big Data Analytics Convergence: The Case of Spark-DIY.
IEEE Access, 2019

The challenges of elastic in situ analysis and visualization.
Proceedings of the Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization, 2019

Improving the Effectiveness of Burst Buffers for Big Data Processing in HPC Systems with Eley.
Future Gener. Comput. Syst., 2018

On the Performance of Spark on HPC Systems: Towards a Complete Picture.
Proceedings of the Supercomputing Frontiers - 4th Asian Conference, 2018

Spark-DIY: A Framework for Interoperable Spark Operations with High Performance Block-Based Data Models.
Proceedings of the 5th IEEE/ACM International Conference on Big Data Computing Applications and Technologies, 2018

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).
PhD thesis, 2017

Enabling fast failure recovery in shared Hadoop clusters: Towards failure-aware scheduling.
Future Gener. Comput. Syst., 2017

Eley: On the Effectiveness of Burst Buffers for Big Data Processing in HPC Systems.
Proceedings of the 2017 IEEE International Conference on Cluster Computing, 2017

Damaris: Addressing Performance Variability in Data Management for Post-Petascale Simulations.
ACM Trans. Parallel Comput., 2016

On the energy footprint of I/O management in Exascale HPC systems.
Future Gener. Comput. Syst., 2016

On the Root Causes of Cross-Application I/O Interference in HPC Storage Systems.
Proceedings of the 2016 IEEE International Parallel and Distributed Processing Symposium, 2016

Chronos: Failure-aware scheduling in shared Hadoop clusters.
Proceedings of the 2015 IEEE International Conference on Big Data (IEEE BigData 2015), Santa Clara, CA, USA, October 29, 2015

A performance and energy analysis of I/O management approaches for exascale systems.
Proceedings of the DIDC'14, 2014