POET is composed of static and dynamic application optimisation, during design (statis) and runtime (runtime). The static optimisation is using MODAK, based on the performance model and the AoE selected optimisations. HPC places utmost importance on application performance, and the optimisation generally involves manual profiling and tuning of application to suit target hardware. Additionally, the optimisation process is not portable and needs to be repeated when moving to other HPC systems. The wide variety of cloud targets with hundreds of different server configuration provides flexibility but lacks the control and performance of HPC systems. In a software defined infrastructure, automating the optimisation of application deployments for heterogeneous targets remains an unsolved problem. Container virtualization has fastened the convergence of HPC and cloud due to its ease of use, portability, scalability, and the advancement of user-friendly runtimes. MODAK addresses the problem of enabling application experts with limited hardware or optimisation knowledge to use diverse targets in an optimal way. When there are many deployment options for the individual components of an application, how to select the best or appropriate set of deployment options for a given context (workload range). At the node level, it is hard to manage heterogeneous resources in order to fulfil QoS requirements at runtime.
Read more at the Horizon Results Platform: https://ec.europa.eu/info/funding-tenders/opportunities/portal/screen/opportunities/horizon-results-platform/35895
Modelling, profilers, monitoring tools, containers, HPC, infrastructure selection, infrastructure tuning, infrastructure changing, software system configurations, runtime discovery, composition of multi-cloud and HPC resources