Malleable Molecular Dynamics Simulations with GROMACS and DMR
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arXiv
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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2026
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| _version_ | 1866909043203768320 |
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| author | Sandås, Petter Iserte, Sergio Aréjula-Aísa, Íñigo Hess, Berk Peña, Antonio J. |
| author_facet | Sandås, Petter Iserte, Sergio Aréjula-Aísa, Íñigo Hess, Berk Peña, Antonio J. |
| contents | Static resource allocations in high-performance computing (HPC) lead to inefficiencies for time-varying workloads, causing idle resources, queue delays, and higher node-hour costs. The Dynamic Management of Resources (DMR) middleware enables MPI process malleability in Slurm via a simple API decoupled from scheduler internals. In this work, we integrate DMR into the GROMACS molecular dynamics engine to obtain a malleable variant that can dynamically adapt its MPI process count by combining communication-efficiency-aware reconfiguration with GROMACS' native checkpoint/restart mechanism. We evaluate this design on the MareNostrum~5 supercomputer, comparing dynamic runs against static executions and quantifying reconfiguration overheads, time-to-solution, and node-hour savings for bursty GROMACS workloads. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_14655 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Malleable Molecular Dynamics Simulations with GROMACS and DMR Sandås, Petter Iserte, Sergio Aréjula-Aísa, Íñigo Hess, Berk Peña, Antonio J. Distributed, Parallel, and Cluster Computing Static resource allocations in high-performance computing (HPC) lead to inefficiencies for time-varying workloads, causing idle resources, queue delays, and higher node-hour costs. The Dynamic Management of Resources (DMR) middleware enables MPI process malleability in Slurm via a simple API decoupled from scheduler internals. In this work, we integrate DMR into the GROMACS molecular dynamics engine to obtain a malleable variant that can dynamically adapt its MPI process count by combining communication-efficiency-aware reconfiguration with GROMACS' native checkpoint/restart mechanism. We evaluate this design on the MareNostrum~5 supercomputer, comparing dynamic runs against static executions and quantifying reconfiguration overheads, time-to-solution, and node-hour savings for bursty GROMACS workloads. |
| title | Malleable Molecular Dynamics Simulations with GROMACS and DMR |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2605.14655 |