Chong Li

Orcid: 0000-0002-4160-7170

Affiliations:
  • Huawei Technologies France S.A.S.U, Boulogne-Billancourt, France
  • Université Paris-Est, LACL, Paris, France (PhD 2013)


According to our database1, Chong Li authored at least 20 papers between 2011 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
SymTensor: Symbolic and Adaptive Tensor Partitioning by Unified Parallelism for Deep Learning.
Int. J. Parallel Program., September, 2026

PRISM: Profiling-Free Symbolic Memory-Driven Strategy Planner for Large DNN Model Training.
Proceedings of the Supercomputing Asia and International Conference on High Performance Computing in Asia Pacific Region, 2026

2025
Efficient Embedding Initialization via Dominant Eigenvector Projections.
Proceedings of the SC '25 Workshops of the International Conference for High Performance Computing, 2025

ManuMatic: Strategy Injection for Robust Automatic Hybrid Parallelism in Distributed DNN Training.
Proceedings of the Network and Parallel Computing, 2025

BMPipe: Bubble-Memory Co-Optimization Strategy Planner for Very-Large DNN Training.
Proceedings of the IEEE International Conference on Cluster Computing, 2025

2024
An Efficient and Scalable Approach to Build Co-occurrence Matrix for DNN's Embedding Layer.
Proceedings of the 38th ACM International Conference on Supercomputing, 2024

RAPID: A Rapid Automatic Parallelizer for Immense Deep Neural Networks.
Proceedings of the IEEE International Conference on Cluster Computing, 2024

2023
SMSG: Profiling-Free Parallelism Modeling for Distributed Training of DNN.
Int. J. Parallel Program., 2023

2022
Enhancing Graph Convolutional Networks by Topology Sampling.
Proceedings of the IEEE International Conference on Big Data, 2022

Distributed and Parallel Sparse Computing for Very Large Graph Neural Networks.
Proceedings of the IEEE International Conference on Big Data, 2022

Parallelizing Neural Network Models Effectively on GPU by Implementing Reductions Atomically.
Proceedings of the International Conference on Parallel Architectures and Compilation Techniques, 2022

2021
Efficient and Systematic Partitioning of Large and Deep Neural Networks for Parallelization.
Proceedings of the Euro-Par 2021: Parallel Processing, 2021

2017
Automated Generation of BSP Automata.
Parallel Process. Lett., 2017

2016
Let High-level Graph Queries Be Parallel Efficient: An Approach Over Structural Recursion On Pregel.
J. Inf. Process., 2016

Derivation of parallel-efficient structural recursive functions from declarative graph queries.
Proceedings of the 31st Annual ACM Symposium on Applied Computing, 2016

2014
GPS: Towards Simplified Communication on SGL Model.
Proceedings of the 2014 IEEE International Parallel & Distributed Processing Symposium Workshops, 2014

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

2012
SGL: towards a bridging model for heterogeneous hierarchical platforms.
Int. J. High Perform. Comput. Netw., 2012

Implementation of Data-Parallel Skeletons: A Case Study Using a Coarse-Grained Hierarchical Model.
Proceedings of the 11th International Symposium on Parallel and Distributed Computing, 2012

2011
A simple bridging model for high-performance computing.
Proceedings of the 2011 International Conference on High Performance Computing & Simulation, 2011


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