Nowadays, the throughput improvement in large clusters of computers recommends the development of malleable applications. Thus, during the execution of these applications in a job, the resource management system (RMS) can modify its resource allocation, in order to increase the global throughput. There are different alternatives to complete the different steps in which the reallocation of resources is decomposed. To find the best alternatives, this paper introduces a configurable synthetic iterative MPI malleable application capable of modifying, in execution time, the number of MPI processes according to several parameters. The application includes a performance module to measure stages time within steps, from processes management to data redistribution. In this way, the analysis of different scenarios will allow to conclude how the reconfiguration of application has to be made in different circumstances. At the same time, this tool can be used to create workloads that will allow to analyse the impact of malleability on a system and the work in progress.

This work has been funded by the following projects: Project PID2020-113656RB-C21 supported by MCIN/AEI/10.13039/501100011033 and project UJI-B2021-58. Researcher S. Iserte was supported by the postdoctoral fellowship APOSTD/2020/026, and researcher I. Mart´ın was supported by the predoctoral fellowship ACIF/2021/260, both from Valencian Region Government and European Social Funds. The authors would like to thank the HPC Advisory Council for providing access to their high-performance computing clusters Jupiter and Thor which correspond, respectively, to System 2 and System 3 in the paper.

Peer Reviewed