BLP: Block-Level Pipelining for GPUs.
Proceedings of the 21st ACM International Conference on Computing Frontiers, 2024
IterML: Iterative Machine Learning for Intelligent Parameter Pruning and Tuning in Graphics Processing Units.
J. Signal Process. Syst., 2021
Directive-Based Data Partitioning and Pipelining and Auto-Tuning for High-Performance GPU Computing.
PhD thesis, 2020
Rapid design of a screw drive in-pipe robot based on parameterized simulation technology.
Simul., 2019
Iterative machine learning (IterML) for effective parameter pruning and tuning in accelerators.
Proceedings of the 16th ACM International Conference on Computing Frontiers, 2019
Directive-Based Partitioning and Pipelining for Graphics Processing Units.
Proceedings of the 2017 IEEE International Parallel and Distributed Processing Symposium, 2017
Directive-Based Pipelining Extension for OpenMP.
Proceedings of the 2016 IEEE International Conference on Cluster Computing, 2016
An Evaluation of Unified Memory Technology on NVIDIA GPUs.
Proceedings of the 15th IEEE/ACM International Symposium on Cluster, 2015