English

Modeling Task Mapping for Data-intensive Applications in Heterogeneous Systems

Distributed, Parallel, and Cluster Computing 2026-04-15 v1 Optimization and Control

Abstract

We introduce a new model for the task mapping problem to aid in the systematic design of algorithms for heterogeneous systems including, but not limited to, CPUs, GPUs and FPGAs. A special focus is set on the communication between the devices, its influence on parallel execution, as well as on device-specific differences regarding parallelizability and streamability. We show how this model can be utilized in different system design phases and present two novel mixed-integer linear programs to demonstrate the usage of the model.

Keywords

Cite

@article{arxiv.2208.06321,
  title  = {Modeling Task Mapping for Data-intensive Applications in Heterogeneous Systems},
  author = {Martin Wilhelm and Hanna Geppert and Anna Drewes and Thilo Pionteck},
  journal= {arXiv preprint arXiv:2208.06321},
  year   = {2026}
}
R2 v1 2026-06-25T01:40:07.796Z