Evaluation of Grid Middleware Frameworks for Execution of MPI Applications

2011 ◽  
pp. 56-61
Author(s):  
Abhishek Jain ◽  
Sathish S. Vadhiyar
Keyword(s):  
Grid Middleware ◽  
Mpi Applications

The analysis of the tools of grid middleware

2008 ◽  
Author(s):  
Rimantas Plestys ◽  
Gytis Vilutis ◽  
Rimantas Kavaliunas ◽  
Kestutis Paulikas
Keyword(s):  
Grid Middleware

Optimizations to enhance sustainability of MPI applications

2014 ◽  
Author(s):  
Jesus Carretero ◽  
Javier Garcia-Blas ◽  
David E. Singh ◽  
Florin Isaila ◽  
Thomas Fahringer ◽  
...  
Keyword(s):  
Mpi Applications

scholarly journals Special Issue: Adaptive Grid Middleware

2006 ◽  
Vol 18 (13) ◽  
pp. 1657-1658
Author(s):  
Thilo Kielmann ◽  
Wilson Rivera
Keyword(s):  
Adaptive Grid ◽  
Special Issue ◽  
Grid Middleware

scholarly journals Toward More Scalable Off-Line Simulations of MPI Applications

2015 ◽  
Vol 25 (03) ◽  
pp. 1541002 ◽  
Author(s):  
Henri Casanova ◽  
Anshul Gupta ◽  
Frédéric Suter
Keyword(s):  
Message Passing ◽  
Post Mortem ◽  
Application Performance ◽  
Popular Approach ◽  
Mpi Applications ◽  
Line Analysis ◽  
Application Execution

The off-line (or post-mortem) analysis of execution event traces is a popular approach to understand the performance of HPC applications that use the message passing paradigm. Combining this analysis with simulation makes it possible to “replay” the application execution to explore “what if?” scenarios, e.g., assessing application performance in a range of (hypothetical) execution environments. However, such off-line analysis faces scalability issues for acquiring, storing, or replaying large event traces. We first present two previously proposed and complementary frameworks for off-line replaying of MPI application event traces, each with its own objectives and limitations. We then describe how these frameworks can be combined so as to capitalize on their respective strengths while alleviating several of their limitations. We claim that the combined framework affords levels of scalability that are beyond that achievable by either one of the two individual frameworks. We evaluate this framework to illustrate the benefits of the proposed combination for a more scalable off-line analysis of MPI applications.

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