DROM: Enabling Efficient and Effortless Malleability for Resource Managers

In the design of future HPC systems, research in resource management is showing an increasing interest in a more dynamic control of the available resources. It has been proven that enabling the jobs to change the number of computing resources at run time, i.e. their malleability, can significantly improve HPC system performance. However, job schedulers and applications typically do not support malleability due to the common belief that it introduces additional programming complexity and performance impact. This paper presents DROM, an interface that provides efficient malleability with no effort for program developers. The running application is enabled to adapt the number of threads to the number of assigned computing resources in a completely transparent way to the user through the integration of DROM with standard programming models, such as OpenMP/OmpSs, and MPI. We designed the APIs to be easily used by any programming model, application and job scheduler or resource manager. Our experimental results from two realistic use cases analysis, based on malleability by reducing the number of cores a job is using per node and jobs co-allocation, show the potential of DROM for improving the performance of HPC systems. In particular, the workload of two MPI+OpenMP neuro-simulators are tested, reporting improvement in system metrics, such as total run time and average response time, up to 8% and 48%, respectively.This work is partially supported by the Span- ish Government through Programa Severo Ochoa (SEV-2015-0493), by the Spanish Ministry of Science and Technology through TIN2015-65316-P project, by the Generalitat de Catalunya (contract 2017-SGR-1414) and from the European Union’s Horizon 2020 under grant agreement No 785907 (HBP SGA2)Peer ReviewedPostprint (author's final draft

Evaluating SLURM simulator with real-machine SLURM and vice versa

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Having a precise and a fast job scheduler model that resembles the real-machine job scheduling software behavior is extremely important in the field of job scheduling. The idea behind SLURM simulator is preserving the original code of the core SLURM functions while allowing for all the advantages of a simulator. Since 2011, SLURM simulator has passed through several iterations of improvements in different research centers. In this work, we present our latest improvements of SLURM simulator and perform the first-ever validation of the simulator on the real machine. In particular, we improved the simulator's performance for about 2.6 times, made the simulator deterministic across several same set-up runs, and improved the simulator's accuracy; its deviation from the real-machine is lowered from previous 12% to at most 1.7%. Finally, we illustrate with several use cases the value of the simulator for job scheduling researchers, SLURM-system administrators, and SLURM developers.Peer ReviewedPostprint (author's final draft