Mapping and scheduling HPC applications for optimizing I/O

Author:

Carretero Jesus1,Jeannot Emmanuel2,Pallez Guillaume2,Singh David E.1,Vidal Nicolas2

Affiliation:

1. University Carlos III, Leganés, Spain

2. Inria Bordeaux, Talence, France

Funder

Agence Nationale de la Recherche

Conseil Régional Aquitaine

Publisher

ACM

Reference31 articles.

1. A multivariate and quantitative model for predicting cross-application interference in virtual environments;Alves Maicon Melo;Journal of Systems and Software,2017

2. What Size Should Your Buffers to Disks be?

3. Sizing and Partitioning Strategies for Burst-Buffers to Reduce IO Contention

4. Co-scheduling algorithms for high-throughput workload execution

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1. StarShip: Mitigating I/O Bottlenecks in Serverless Computing for Scientific Workflows;Proceedings of the ACM on Measurement and Analysis of Computing Systems;2024-02-16

2. Detecting interference between applications and improving the scheduling using malleable application clones;The International Journal of High Performance Computing Applications;2023-12-13

3. IO-aware Job-Scheduling: Exploiting the Impacts of Workload Characterizations to select the Mapping Strategy;The International Journal of High Performance Computing Applications;2023-05-15

4. Taming Metadata-intensive HPC Jobs Through Dynamic, Application-agnostic QoS Control;2023 IEEE/ACM 23rd International Symposium on Cluster, Cloud and Internet Computing (CCGrid);2023-05

5. Illuminating the I/O Optimization Path of Scientific Applications;Lecture Notes in Computer Science;2023

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