Hybrid reinforcement learning with expert state sequences
Xiaoxiao Guo, Shiyu Chang, et al.
AAAI 2019
We present a single-program-multiple-data computational model which we have implemented in the EPEX system to run in parallel mode FORTRAN scientific application programs. The computational model assumes a shared memory organization and is based on the scheme that all processes executing a program in parallel remain in existence for the entire execution; however, the tasks to be executed by each process are determined dynamically during execution by the use of appropriate synchronizing constructs that are imbedded in the program. We have demonstrated the applicability of the model in the parallelization of several applications. We discuss parallelization features of these applications and performance issues such as overhead, speedup, efficiency. © 1988.
Xiaoxiao Guo, Shiyu Chang, et al.
AAAI 2019
Rie Kubota Ando
CoNLL 2006
Fearghal O'Donncha, Albert Akhriev, et al.
Big Data 2021
Hannah Kim, Celia Cintas, et al.
IJCAI 2023