Open AccessDesign and Implementation of a Dynamic Task Mapping Algorithm Based on Hotspot Statistics
Author(s) -
Jie Wang,
Duoli Zhang,
Hu Ge,
Wei Ni,
Yukun Song
Publication year - 2022
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2245/1/012001
Subject(s) - computer science , preprocessor , verilog , hotspot (geology) , task (project management) , dynamic programming , data mapping , real time computing , algorithm , distributed computing , data mining , embedded system , programming language , field programmable gate array , management , geophysics , economics , geology
In a coarse-grained heterogeneous multi-core system, the task map is responsible for allocating the cores for task execution. The existing user static mapping method has low programming friendliness. As the scale and density of system tasks increase, so does the complexity of manual programming by users, resulting in programming inefficiencies. Aiming at this problem, based on the existing heterogeneous multi-core platform, this paper studies a dynamic task mapping method with hotspot statistics, and uses the preprocessing of the mapping to reduce the time spent on the actual mapping. The hardware mapper is designed and implemented in Verilog, and the verification platform is built in the HDL environment. The experimental results show that the new mapping algorithm significantly improves the performance of the system, with an average of 32.50% and a maximum of 47.16%.