Sie befinden Sich nicht im Netzwerk der Universität Paderborn. Der Zugriff auf elektronische Ressourcen ist gegebenenfalls nur via VPN oder Shibboleth (DFN-AAI) möglich. mehr Informationen...
Ergebnis 6 von 72
2016 28th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD), 2016, p.9-17
2016
Volltextzugriff (PDF)

Details

Autor(en) / Beteiligte
Titel
Using Balanced Data Placement to Address I/O Contention in Production Environments
Ist Teil von
  • 2016 28th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD), 2016, p.9-17
Ort / Verlag
IEEE
Erscheinungsjahr
2016
Quelle
IEEE Xplore Digital Library
Beschreibungen/Notizen
  • 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.
Sprache
Englisch
Identifikatoren
DOI: 10.1109/SBAC-PAD.2016.10
Titel-ID: cdi_ieee_primary_7789318

Weiterführende Literatur

Empfehlungen zum selben Thema automatisch vorgeschlagen von bX