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Research Project 3.1
Workload modelling
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Objective:
The primary objective of RP3.1 is to fuse existing, disparate modelling approaches, mod elling and allocating computational heavy workloads in heterogeneous computing environments. This project aims to efficiently manage software development and runtime variability, focusing on known and unknown uncertainties.
The project focuses on developing a modelling environment that supports mixed core edge technologies and facilitates the dynamic reallocation of workloads. The project will address chal lenges in modelling allocation to mixed core and edge nodes, accommodating structural and functional aspects of parallel software
The approach involves enhancing modelling technologies by introducing concepts for para metric software allocation across mixed core and edge computing nodes. This enhancement will be independent of specific target languages or platforms, enabling broader applicability and flexibility. The project will also develop mechanisms for model transformations to support dynamic re-allocation of workloads, ensuring that extra-functional requirements and constraints, such as energy consumption and resource limitations, are met
Expected outcomes:
The project's expected outcomes include the development of a sophisticated modelling approach that will support the dynamic allocation of workloads in heterogeneous computing environments. This will enable more efficient and adaptable workload deployment, addressing key challenges in energy consumption and resource limitations. The work is anticipated to lead to innovative solutions in managing runtime variability and developing software for heterogeneous systems
Staffing:1 PhD-student, 1 Assoc. Sr. Lecturer, 1 Research Engineer (part of), 1 PhD-student funded by VR (part of)
Duration: 2024-2032
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