Refactoring Software in the Automotive Domain for Execution on Heterogeneous Platforms
Hugo Andrade, Ivica Crnkovic, Jan Bosch

TL;DR
This paper presents a decision framework to assist automotive software engineers in systematically refactoring software for execution on heterogeneous computing platforms, addressing challenges in migration and optimization.
Contribution
It introduces a structured decision support framework based on architectural assessments for refactoring automotive software to heterogeneous platforms.
Findings
Framework developed through industry discussions
Supports risk minimization in migration process
Facilitates architectural decision-making
Abstract
The most important way to achieve higher performance in computer systems is through heterogeneous computing, i.e., by adopting hardware platforms containing more than one type of processor, such as CPUs, GPUs, and FPGAs. Several types of algorithms can be executed significantly faster on a heterogeneous platform. However, migrating CPU-executable software to other types of execution platforms poses a number of challenges to software engineering. Significant efforts are required in such type of migration, particularly for re-architecting and re-implementing the software. Further, optimizing it in terms of performance and other runtime properties can be very challenging, making the process complex, expensive, and error-prone. Therefore, a systematic approach based on explicit and justified architectural decisions is needed for a successful refactoring process from a homogeneous to a…
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