TAUoverSupermon; Low-overhead Online parallel performance monitoring

被引：0

作者：

Nataraj, Aroon ^{[1
]}

Sottile, Matthew ^{[2
]}

Morris, Alan ^{[1
]}

Malony, Allen D. ^{[1
]}

Shende, Sameer ^{[1
]}

机构：

[1] Univ Oregon, Dept Comp & Informat Sci, Eugene, OR 97403 USA

[2] Los Alamos Natl Lab, Los Alamos, NM USA

来源：

EURO-PAR 2007 PARALLEL PROCESSING, PROCEEDINGS | 2007年 / 4641卷

关键词：

online performance measurement; cluster monitoring;

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Online application performance monitoring allows tracking performance characteristics during execution as opposed to doing so post-mortem. This opens up several possibilities otherwise unavailable such as real-time visualization and application performance steering that can be useful in the context of long-running applications. As HPC systems grow in size and complexity, the key challenge is to keep the online performance monitor scalable and low overhead while still providing a useful performance reporting capability. Two fundamental components that constitute such a performance monitor are the measurement and transport systems. We adapt and combine two existing, mature systems - TAU and Supermon - to address this problem. TAU performs the measurement while Supermon is used to collect the distributed measurement state. Our experiments show that this novel approach leads to very low-overhead application monitoring as well as other benefits unavailable from using a transport such as NFS.

引用

页码：85 / +

页数：3