|Title||P3S: A Methodology to Analyze and Predict Application Scalability|
|Publication Type||Journal Article|
|Year of Publication||2018|
|Authors||Panadero, J, Wong, A, Rexachs, D, Luque, E|
|Journal||IEEE Transactions on Parallel and Distributed Systems|
|Keywords||Computational modeling, Hardware, HPC Systems, Mathematical model, MPI application, Multicore processing, prediction of an application scalability, Predictive models, Scalability, scalability prediction, Tools|
Executing message-passing parallel applications on a large number of resources in an efficient way is not a trivial task. Due to the complex interaction between the parallel applications and the HPC system, many applications may suffer performance inefficiencies when they scale. To achieve an efficient use of these large-scale systems using thousands of cores, a point to consider before executing an application is to know its behavior in the system. In this work, we propose a novel methodology called P3S (Prediction of Parallel Program Scalability), which allows us to analyze and predict the scalability of message-passing applications on a given system. The methodology strives to use a bounded analysis time, and a reduced set of resources to predict the application behavior for large-scale. The experimental validation proves that the P3S is able to predict the application scalability with an average accuracy greater than 95 percent using a reduced set of resources.