Using balanced data placement to address I/O contention in production environments

Designed for capacity and capability, HPC I/O systems are inherently complex and shared among multiple, concurrent jobs competing for resources. Lack of centralized coordination and control often render the end-to-end I/O paths vulnerable to load imbalance and contention. With the emergence of data-...

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Hauptverfasser: Neuwirth, Sarah (VerfasserIn) , Brüning, Ulrich (VerfasserIn)
Dokumenttyp: Kapitel/Artikel Konferenzschrift
Sprache:Englisch
Veröffentlicht: 2016
In: 2016 28th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD)
Year: 2016, Pages: 9-17
DOI:10.1109/SBAC-PAD.2016.10
Schlagworte:
Online-Zugang:Resolving-System, Volltext: http://dx.doi.org/10.1109/SBAC-PAD.2016.10
Verlag, Volltext: https://ieeexplore.ieee.org/document/7789318/
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Verfasserangaben:Sarah Neuwirth, Feiyi Wang, Sarp Oral, Sudharshan Vazhkudai, James H. Rogers and Ulrich Bruening

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520 |a Designed for capacity and capability, HPC I/O systems are inherently complex and shared among multiple, concurrent jobs competing for resources. Lack of centralized coordination and control often render the end-to-end I/O paths vulnerable to load imbalance and contention. With the emergence of data-intensive HPC applications, storage systems are further contended for performance and scalability. This paper proposes to unify two key approaches to tackle the imbalanced use of I/O resources and to achieve an end-to-end I/O performance improvement in the most transparent way. First, it utilizes a topology-aware, Balanced Placement I/O method (BPIO) for mitigating resource contention. Second, it takes advantage of the platform-neutral ADIOS middleware, which provides a flexible I/O mechanism for scientific applications. By integrating BPIO with ADIOS, referred to as Aequilibro, we obtain an end-to-end and per job I/O performance improvement for ADIOS-enabled HPC applications without requiring any code changes. Aequilibro can be applied to almost any HPC platform and is mostly suitable for systems that lack a centralized file system resource manager. We demonstrate the effectiveness of our integration on the Titan system at the Oak Ridge National Laboratory. Our experiments with a synthetic benchmark and real-world HPC workload show that, even in a noisy production environment, Aequilibro can improve large-scale application performance significantly. 
650 4 |a ADIOS-enabled HPC applications 
650 4 |a Aequilibro 
650 4 |a Aggregates 
650 4 |a balanced data placement 
650 4 |a balanced placement I/O method 
650 4 |a BPIO 
650 4 |a end-to-end I/O performance improvement 
650 4 |a flexible I/O mechanism 
650 4 |a High Performance Computing 
650 4 |a I/O contention 
650 4 |a I/O resources 
650 4 |a Load management 
650 4 |a noisy production environment 
650 4 |a Oak Ridge National Laboratory 
650 4 |a parallel processing 
650 4 |a Performance evaluation 
650 4 |a platform-neutral ADIOS middleware 
650 4 |a Resource management 
650 4 |a Scalability 
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