TY - GEN
T1 - An enhanced DSM model for computation offloading
AU - Lee, Jaemin
AU - Jun, Yuhun
AU - Seo, Euiseong
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/5/2
Y1 - 2017/5/2
N2 - The distributed shared memory (DSM)-based computation offloading scheme allows collaborative multiple threads to dynamically migrate and execute across a mobile device and computing nodes. Despite this strong advantage, it misses a significant portion of the potential performance gain because the traditional DSM model is suboptimal for computation offloading. This paper proposes an enhanced DSM model that aims to enable multiple computing nodes to efficiently and reliably offload concurrent multiple threads from a mobile device. To achieve this design goal, we propose the following novel schemes: a) selective object tracking minimizes the set of objects to be monitored by the DSM layer; b) lock-thread repartitioning dynamically relocates threads and locks in order to reduce remote lock acquisitions and inter-node synchronizations; and c) thread-state checkpointing protects the data and context upon unexpected system failures. We implemented METEOR, which is a prototype based on the proposed schemes, and evaluated it with diverse applications. The evaluation showed that METEOR, with four computing nodes, improved the performance by up to 109% and reduced energy consumption by up to 52% in comparison with the previous DSM-based offloading scheme.
AB - The distributed shared memory (DSM)-based computation offloading scheme allows collaborative multiple threads to dynamically migrate and execute across a mobile device and computing nodes. Despite this strong advantage, it misses a significant portion of the potential performance gain because the traditional DSM model is suboptimal for computation offloading. This paper proposes an enhanced DSM model that aims to enable multiple computing nodes to efficiently and reliably offload concurrent multiple threads from a mobile device. To achieve this design goal, we propose the following novel schemes: a) selective object tracking minimizes the set of objects to be monitored by the DSM layer; b) lock-thread repartitioning dynamically relocates threads and locks in order to reduce remote lock acquisitions and inter-node synchronizations; and c) thread-state checkpointing protects the data and context upon unexpected system failures. We implemented METEOR, which is a prototype based on the proposed schemes, and evaluated it with diverse applications. The evaluation showed that METEOR, with four computing nodes, improved the performance by up to 109% and reduced energy consumption by up to 52% in comparison with the previous DSM-based offloading scheme.
UR - https://www.scopus.com/pages/publications/85020037037
U2 - 10.1109/PERCOM.2017.7917852
DO - 10.1109/PERCOM.2017.7917852
M3 - Conference contribution
AN - SCOPUS:85020037037
T3 - 2017 IEEE International Conference on Pervasive Computing and Communications, PerCom 2017
SP - 69
EP - 78
BT - 2017 IEEE International Conference on Pervasive Computing and Communications, PerCom 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE International Conference on Pervasive Computing and Communications, PerCom 2017
Y2 - 13 March 2017 through 17 March 2017
ER -