Authors
Fabio Montagna, Giuseppe Tagliavini, Davide Rossi, Angelo Garofalo, Luca Benini
Publication date
2021
Conference
Architecture of Computing Systems: 34th International Conference, ARCS 2021, Virtual Event, June 7–8, 2021, Proceedings 34
Pages
167-182
Publisher
Springer International Publishing
Description
High-level programming models aim at exploiting hardware parallelism and reducing software development costs. However, their adoption on ultra-low-power multi-core microcontroller (MCU) platforms requires minimizing the overheads of work-sharing constructs on fine-grained parallel regions. This work tackles this challenge by proposing OMP-SPMD, a streamlined approach for parallel computing enabling the OpenMP syntax for the Single-Program Multiple-Data (SPMD) paradigm. To assess the performance improvement, we compare our solution with two alternatives: a baseline implementation of the OpenMP runtime based on the fork-join paradigm (OMP-base) and a version leveraging hardware-specific optimizations (OPM-opt). We benchmarked these libraries on a Parallel Ultra-Low Power (PULP) MCU, highlighting that hardware-specific optimizations improve OMP-base performance up to 69 …
Total citations
202220232024221
Scholar articles
F Montagna, G Tagliavini, D Rossi, A Garofalo, L Benini - Architecture of Computing Systems: 34th International …, 2021