Optimizations for configuring and mapping software pipelines in many core systems
Janmartin Jahn, Santiago Pagani, Sebastian Kobbe, Jian-Jia Chen, Jörg Henkel · 2013
Efficiently utilizing the computational resources of many core systems is one of the most prominent challenges. The problem worsens when resource requirements vary unpredictably and applications may be started/stopped at any time. To address this challenge, we propose two schemes that calculate and adapt task mappings at runtime: a centralized, optimal mapping scheme and a distributed, hierarchical mapping scheme that trades optimality for a high degree of scalability. Experiments on Intel's 48-core Single-Chip Cloud Computer and in a many core simulator show that a significant improvement in system performance can be achieved over current state-of-the-art.