| Title: |
Communication and Shared Memory Efficient Mapping Techniques of Real-Time DAGs upon Clustered Multicore Platforms |
| Authors: |
Schuh, Matheus; Maiza, Claire; Raymond, Pascal; Ferres, Bruno; Goossens, Joël; Dinechin, Benoît Dupont De |
| Contributors: |
Kalray; VERIMAG (VERIMAG - IMAG); Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP); Université Grenoble Alpes (UGA); Institut des sciences informatiques et de leurs interactions - CNRS Sciences informatiques (INS2I-CNRS); Université Grenoble Alpes - UFR Informatique, mathématiques et mathématiques appliquées (UGA UFR IM2AG); Université libre de Bruxelles = Free University of Brussels (ULB) |
| Source: |
33rd International Conference on Real-Time Networks and Systems; https://hal.science/hal-05289989; 33rd International Conference on Real-Time Networks and Systems, Nov 2025, Pise, Italy |
| Publisher Information: |
CCSD |
| Publication Year: |
2025 |
| Collection: |
Université Grenoble Alpes: HAL |
| Subject Terms: |
Mapping; Ordering; Periodic DAG; Multicores; Manycores; Clustered Architectures; Banked Memory; List Scheduling; Partitioned Memory; [INFO.INFO-ES]Computer Science [cs]/Embedded Systems |
| Subject Geographic: |
Pise; Italy |
| Description: |
International audience ; When it comes to mapping and scheduling Real-Time applications on parallel platforms, the Directed Acyclic Graphs (DAGs) processing model is commonly used. In this paper, we leverage the structural properties of DAG-based applications to optimize their deployment in clustered multicore processors. We assume a constant communication time between clusters and partitioned banked memory inside clusters. Our main contribution is a novel mapping (and ordering) heuristic that accounts for both communication size and DAG topology, while respecting memory constraints. Compared to the classic list scheduling-based mapping algorithm HLFET, when our approach succeeds in finding a mapping, it achieves a reduction of up to 75% in the global DAG response time and leads to better scheduling in 80% of the cases. |
| Document Type: |
conference object |
| Language: |
English |
| Availability: |
https://hal.science/hal-05289989; https://hal.science/hal-05289989v1/document; https://hal.science/hal-05289989v1/file/map-sched-preprint.pdf |
| Rights: |
https://creativecommons.org/licenses/by-nc-nd/4.0/ |
| Accession Number: |
edsbas.4CDC3816 |
| Database: |
BASE |