z-logo
open-access-imgOpen Access
Scalable parallel performance measurement and analysis tools - state-of-the-art and future challenges
Author(s) -
Bernd Mohr
Publication year - 2014
Publication title -
supercomputing frontiers and innovations
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 16
eISSN - 2409-6008
pISSN - 2313-8734
DOI - 10.14529/jsfi140207
Subject(s) - computer science , scalability , porting , middleware (distributed applications) , distributed computing , software , state (computer science) , complex system , software system , computer architecture , embedded system , operating system , algorithm , artificial intelligence
Current large-scale HPC systems consist of complex configurations with a huge number of potentially heterogeneous components. As the systems get larger, their behavior becomes more and more dynamic and unpredictable because of hard and software re-configurations due to fault recovery and power usage optimizations. Deep software hierarchies of large, complex system software and middleware components are required to operate such systems. Therefore, porting, adapting and tuning applications to today's complex systems is a complicated and time-consuming task. Sophisticated integrated performance measurement, analysis, and optimization capabilities are required to efficiently utilize such systems. This article will summarize the state-of-the-art of scalable and portable parallel performance tools and the challenges these tools are facing on future extreme-scale and big data systems.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom