OASIcs.PARMA-DITAM.2024.5.pdf
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Embedded Multi-Core Code Generation with Cross-Layer Parallelization
Authors
Oliver Oey 
,
Michael Huebner ,
Timo Stripf ,
Juergen Becker
-
Part of:
Volume:
15th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 13th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2024)
Series: Open Access Series in Informatics (OASIcs)
Conference: Workshop on Parallel Programming and Run-Time Management Techniques for Many-core Architectures (PARMA)
Conference: Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (DITAM) - License:
Creative Commons Attribution 4.0 International license
- Publication Date: 2024-03-01
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Oliver Oey, Michael Huebner, Timo Stripf, and Juergen Becker. Embedded Multi-Core Code Generation with Cross-Layer Parallelization. In 15th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 13th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2024). Open Access Series in Informatics (OASIcs), Volume 116, pp. 5:1-5:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)
https://doi.org/10.4230/OASIcs.PARMA-DITAM.2024.5
https://doi.org/10.4230/OASIcs.PARMA-DITAM.2024.5
Abstract
In this paper, we present a method for optimizing C code for embedded multi-core systems using cross-layer parallelization. The method has two phases. The first is to develop the algorithm without any optimization for the target platform. Then, the second step is to optimize and parallelize the code across four defined layers which are the algorithm, code, task, and data layers, for efficient execution on the target hardware. Each layer is focused on selected hardware characteristics. By using an iterative approach, individual kernels and composite algorithms can be very well adapted to execution on the hardware without further adaptation of the algorithm itself. The realization of this cross-layer parallelization consists of algorithm recognition, code transformations, task distribution, and insertion of synchronization and communication statements. The method is evaluated first on a common kernel and then on a sample image processing algorithm to showcase the benefits of the approach. Compared to other methods that only rely on two or three of these layers, 20 to 30 % of additional performance gain can be achieved.
Subject Classification
ACM Subject Classification
- Software and its engineering → Source code generation
- Software and its engineering → Imperative languages
- Software and its engineering → Very high level languages
- Computer systems organization → Embedded software
Keywords
- Parallelization
- multi-core Processors
- model-based Development
- Code Generation
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References
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