Affiliation:
1. Institute of Informatics, Federal University of Rio Grande do Sul
2. Department of Informatics and Statistics, Federal University of Santa Catarina
3. INRIA, University of Grenoble Alpes
Abstract
We present a comprehensive survey on parallel I/O in the high-performance computing (HPC) context. This is an important field for HPC because of the historic gap between processing power and storage latency, which causes application performance to be impaired when accessing or generating large amounts of data. As the available processing power and amount of data increase, I/O remains a central issue for the scientific community. In this survey article, we focus on a traditional I/O stack, with a POSIX parallel file system. We present background concepts everyone could benefit from. Moreover, through the comprehensive study of publications from the most important conferences and journals in a 5-year time window, we discuss the state of the art in I/O optimization approaches, access pattern extraction techniques, and performance modeling, in addition to general aspects of parallel I/O research. With this approach, we aim at identifying the general characteristics of the field and the main current and future research topics.
Funder
EU H2020 Programme
MCTI/RNP-Brazil under the HPC4E Project
Publisher
Association for Computing Machinery (ACM)
Subject
General Computer Science,Theoretical Computer Science
Cited by
24 articles.
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1. Lazy Read: Asynchronous Execution of Synchronous File I/O;2023 IEEE International Conference on Big Data (BigData);2023-12-15
2. Clustering based Probabilistic I/O Scheduling for Burst-Buffers Equipped HPC;2023 IEEE 14th International Symposium on Parallel Architectures, Algorithms and Programming (PAAP);2023-11-24
3. Achieving Enhanced Performance Combining Checkpointing and Dynamic State Partitioning;2023 IEEE 35th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD);2023-10-17
4. Landscape of High-Performance Python to Develop Data Science and Machine Learning Applications;ACM Computing Surveys;2023-10-05
5. I/O Access Patterns in HPC Applications: A 360-Degree Survey;ACM Computing Surveys;2023-09-15