A simple bridging model for high-performance computing. - Chong Li 003; Gaétan Hains (HPCS, 2011)

Implementation of Data-Parallel Skeletons: A Case Study Using a Coarse-Grained Hierarchical Model. - Chong Li 003; Frédéric Gava; Gaétan Hains (ISPDC, 2012)

SGL: towards a bridging model for heterogeneous hierarchical platforms. - Chong Li 003; Gaétan Hains (Int. J. High Perform. Comput. Netw., 2012)

Un modèle de transition logico-matérielle pour la simplification de la programmation parallèle. (A software-hardware bridging model for simplifying parallel programming). - Chong Li 003 (2013)

GPS: Towards Simplified Communication on SGL Model. - Chong Li 003; Gaétan Hains (IPDPS Workshops, 2014)

Derivation of parallel-efficient structural recursive functions from declarative graph queries. - Chong Li 003; Le-Duc Tung; Xiaodong Meng; Zhenjiang Hu (SAC, 2016)

Let High-level Graph Queries Be Parallel Efficient: An Approach Over Structural Recursion On Pregel. - Chong Li 003; Le-Duc Tung; Xiaodong Meng; Zhenjiang Hu (J. Inf. Process., 2016)

Automated Generation of BSP Automata. - Thibaut Tachon; Chong Li 003; Gaétan Hains; Frédéric Loulergue (Parallel Process. Lett., 2017)

Efficient and Systematic Partitioning of Large and Deep Neural Networks for Parallelization. - Haoran Wang; Chong Li 003; Thibaut Tachon; Hongxing Wang; Sheng Yang; Sébastien Limet; Sophie Robert 001 (Euro-Par, 2021)

Parallelizing Neural Network Models Effectively on GPU by Implementing Reductions Atomically. - Jie Zhao 002; Cédric Bastoul; Yanzhi Yi; Jiahui Hu; Wang Nie; Renwei Zhang; Zhen Geng; Chong Li 003; Thibaut Tachon; Zhiliang Gan (PACT, 2022)

Distributed and Parallel Sparse Computing for Very Large Graph Neural Networks. - Quentin R. Petit; Chong Li 003; Nahid Emad (IEEE Big Data, 2022)

Enhancing Graph Convolutional Networks by Topology Sampling. - Quentin R. Petit; Chong Li 003; Serge G. Petiton; Kelun Chai; Nahid Emad (IEEE Big Data, 2022)

SMSG: Profiling-Free Parallelism Modeling for Distributed Training of DNN. - Haoran Wang; Thibaut Tachon; Chong Li 003; Sophie Robert 001; Sébastien Limet (Int. J. Parallel Program., 2023)

RAPID: A Rapid Automatic Parallelizer for Immense Deep Neural Networks. - Thibaut Tachon; Haoran Wang; Chong Li 003 (CLUSTER Workshops, 2024)

An Efficient and Scalable Approach to Build Co-occurrence Matrix for DNN's Embedding Layer. - Quentin R. Petit; Chong Li 003; Nahid Emad (ICS, 2024)