SC13 Home > SC13 Schedule > SC13 Presentation - Scalable Performance Analysis of Exascale MPI Programs through Signature-Based Clustering Algorithms

SCHEDULE: NOV 16-22, 2013

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Scalable Performance Analysis of Exascale MPI Programs through Signature-Based Clustering Algorithms

SESSION: Research Poster Reception

EVENT TYPE: Posters, Electronic Posters, and Education Posters

TIME: 5:15PM - 7:00PM

AUTHOR(S):Amir Bahmani, Frank Mueller

ROOM:Mile High Pre-Function

ABSTRACT:
Exascale computing pose a number of challenges to application performance. Developers need to study application behavior by collecting detailed information with the help of tracing toolsets. But not only applications are scalability challenged, current tracing toolsets also fall short of exascale requirements for low background overheads since trace collection for each execution entity is becoming infeasible. One effective solution is to cluster processes with the same behavior into groups. Instead of collecting performance information from all individuals, this information can be collected from just a set of representatives. This work proposes a fast, scalable, signature-based clustering algorithm that clusters processes that exhibit the same execution behavior. Instead of prior work for statistical clustering metrics, it produces precise results without loss of events or accuracy. The proposed algorithm combines log(P) time complexity, low overhead at the clustering level, and it splits the merge process to make tracing suitable for exascale computing.

Chair/Author Details:

Amir Bahmani - North Carolina State University

Frank Mueller - North Carolina State University

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