Modeling Task Mapping for Data-intensive Applications in Heterogeneous Systems

TL;DR

This paper presents a new model for task mapping in heterogeneous systems, focusing on communication, device differences, and aiding systematic algorithm design.

Contribution

The paper introduces a novel model for task mapping in heterogeneous systems and demonstrates its application through two mixed-integer linear programs.

Findings

Model effectively captures communication and device-specific factors.

Two MILPs demonstrate practical use of the model.

Model supports systematic design of task mapping algorithms.

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.