SHAMan is an out-of-the-box framework to perform black-box auto-tuning of custom computer components running on a distributed system (for example a High Performance Computing system), for a given application launched through the Slurm workload manager. It relies on state-of-the-art black-box algorithms to find the components' parametrization that are the most efficient in terms of execution time. It also integrates noise reduction strategies to deal with the possible interference of shared resources for large scale HPC systems, and pruning strategies to limit the time spent by the optimization process.

Compared to already existing softwares, it provides these main advantages:

🚀 Accessibility: the optimization engine is accessible either through a Web Interface or a Commande Line Interface (CLI)

🚀 Easy to extend: the optimization engine uses a plug-in architecture and the development of the heuristic is thus the only development cost

🚀 Integrated within the HPC ecosystem: the framework relies on the Slurmworkload manager to run HPC applications. The microservice architecture enables it to have no concurrent interactions with the cluster and the application itself.

🚀 Flexible for a wide range of use-cases: new components can be registered through a generalist configuration file.

🚀 Integrates noise reduction strategies: because of their highly dynamic nature and the complexity of applications and software stacks, distributed systems are subject to many interference when running in production, which results in a different performance measure for each run even with the same system’s parametrization. Noise reduction strategies are included in the framework to perform well even in the case of strong interference.

🚀 Integrates pruning strategies: runs with unsuited parametrization are stopped prematurely to speed-up the convergence process