Hongyuan Liu

• PhD (2022) College of William & Mary (Computer Science)
• MS (2016) The University of Hong Kong (Computer Science)
• BE (2013) Shandong University (Computer Science and Technology)

Conference Proceeding

1. Liu, H.; Nicolae, B.; Di, S.; Cappello, F.; Jog, A. (2021). Accelerating DNN Architecture Search at Scale Using Selective Weight Transfer. Proceedings of the IEEE International Conference on Cluster Computing (CLUSTER). IEEE.
   https://doi.org/10.1109/Cluster48925.2021.00051.
2. Liu, H.; Pai, S.; Jog, A. (2020). Why GPUs are Slow at Executing NFAs and How to Make them Faster. Proceedings of the Twenty-Fifth International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS).
   https://dl.acm.org/doi/10.1145/3373376.3378471.
3. Ibrahim, M. A.; Liu, H.; Kayiran, O.; Jog, A. (2019). Analyzing and Leveraging Remote-core Bandwidth for Enhanced Performance in GPUs. Proceedings of the 28th International Conference on Parallel Architectures and Compilation Techniques (PACT). IEEE.
   https://doi.org/10.1109/PACT.2019.00028.
4. Liu, H.; Ibrahim, M. A.; Kayiran, O.; Pai, S.; Jog, A. (2018). Architectural Support for Efficient Large-Scale Automata Processing. Proceedings of the 51st Annual IEEE/ACM International Symposium on Microarchitecture (MICRO).
   https://dl.acm.org/doi/10.1109/MICRO.2018.00078.
5. Liu, H.; Lam, K.; Lin, H.; Wang, C.; Ma, J. (2016). Lightweight Dependency Checking for Parallelizing Loops with Non-Deterministic Dependency on GPU. Proceedings of the IEEE 22nd International Conference on Parallel and Distributed Systems (ICPADS). IEEE.
   https://doi.org/10.1109/icpads.2016.0119.

Journal Article

1. Lin, H.; Wang, C.; Liu, H. (2018). On-GPU Thread-Data Remapping for Branch Divergence Reduction. ACM Transactions on Architecture and Code Optimization (TACO) (3 ed., vol. 15, pp. 1-24). ACM.
   https://dl.acm.org/doi/10.1145/3242089.