Baodi Shan

I’m a Ph.D. candidate in Computer Science at Stony Brook University, advised by Dr. Barbara Chapman in Exascallab. I received my B.Eng. from Shandong University in 2021 and expect to graduate in September 2026.

My research focuses on networking and system architecture for large-scale AI and HPC systems.

You can reach me by email or download my CV.

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selected publications

HPDC
GICC: A High-Performance Runtime for GPU-Initiated Communication and Coordination in Modern HPC Systems

Baodi Shan, Mauricio Araya-Polo, and Barbara Chapman

In Proceedings of the 35th International Symposium on High-Performance Parallel and Distributed Computing (HPDC), Jul 2026

Abs Bib

GICC is a GPU-initiated communication and coordination runtime that spans libfabric-based Slingshot and libibverbs-based InfiniBand backends, enabling GPU-triggered progress, active messages, and barrier operations across heterogeneous GPU clusters. GICC achieves up to 1.95x lower put latency than NVSHMEM on InfiniBand and up to 25% higher weak-scaling efficiency on Slingshot, and reduces communication time on a 64-GPU stencil workload by over 52% versus GPU-aware MPI.
@inproceedings{shan2026gicc, author = {Shan, Baodi and Araya-Polo, Mauricio and Chapman, Barbara}, title = {GICC: A High-Performance Runtime for GPU-Initiated Communication and Coordination in Modern HPC Systems}, booktitle = {Proceedings of the 35th International Symposium on High-Performance Parallel and Distributed Computing (HPDC)}, year = {2026}, month = jul, }

LLVM/OpenMP

DiOMP-Offloading: Toward Portable Distributed Heterogeneous OpenMP

Baodi Shan, Mauricio Araya-Polo, and Barbara Chapman

In Proceedings of the SC ’25 Workshops of the International Conference on High Performance Computing, Network, Storage, and Analysis (SC-W), Nov 2025

Bib

@inproceedings{shan2025diomp,
  author = {Shan, Baodi and Araya-Polo, Mauricio and Chapman, Barbara},
  title = {DiOMP-Offloading: Toward Portable Distributed Heterogeneous OpenMP},
  booktitle = {Proceedings of the SC '25 Workshops of the International Conference on High Performance Computing, Network, Storage, and Analysis (SC-W)},
  year = {2025},
  month = nov,
}

LLVM/OpenMP

Discussion of Device-Device Collective Communication in OpenMP Target Offloading

Baodi Shan, Mauricio Araya-Polo, Johannes Doerfert, and 1 more author

In International Workshop on OpenMP (IWOMP), Sep 2025

Bib

@inproceedings{shan2025iwomp,
  author = {Shan, Baodi and Araya-Polo, Mauricio and Doerfert, Johannes and Chapman, Barbara},
  title = {Discussion of Device-Device Collective Communication in OpenMP Target Offloading},
  booktitle = {International Workshop on OpenMP (IWOMP)},
  year = {2025},
  month = sep,
}

LLVM/OpenMP
Towards a Scalable and Efficient PGAS-Based Distributed OpenMP

Baodi Shan, Mauricio Araya-Polo, and Barbara Chapman

In Advancing OpenMP for Future Accelerators, Sep 2024

Abs Bib

MPI+X has been the de facto standard for distributed memory parallel programming. It is widely used primarily as an explicit two-sided communication model, which often leads to complex and error-prone code. Alternatively, PGAS model utilizes efficient one-sided communication and more intuitive communication primitives. In this paper, we present a novel approach that integrates PGAS concepts into the OpenMP programming model, leveraging the LLVM compiler infrastructure and the GASNet-EX communication library. Our model addresses the complexity associated with traditional MPI+OpenMP programming models while ensuring excellent performance and scalability. We evaluate our approach using a set of micro-benchmarks and application kernels on two distinct platforms: Ookami from Stony Brook University and NERSC Perlmutter. The results demonstrate that DiOMP achieves superior bandwidth and lower latency compared to MPI+OpenMP, up to }}25\backslash%}}25%higher bandwidth and down to }}45\backslash%}}45%on latency. DiOMP offers a promising alternative to the traditional MPI+OpenMP hybrid programming model, towards providing a more productive and efficient way to develop high-performance parallel applications for distributed memory systems.
@inproceedings{10.1007/978-3-031-72567-8_5, author = {Shan, Baodi and Araya-Polo, Mauricio and Chapman, Barbara}, editor = {Espinosa, Alexis and Klemm, Michael and de Supinski, Bronis R. and Cytowski, Maciej and Klinkenberg, Jannis}, title = {Towards a Scalable and Efficient PGAS-Based Distributed OpenMP}, booktitle = {Advancing OpenMP for Future Accelerators}, year = {2024}, month = sep, publisher = {Springer Nature Switzerland}, address = {Cham}, pages = {64--78}, isbn = {978-3-031-72567-8}, }

LLVM/OpenMP

Evaluation of Programming Models and Performance for Stencil Computation on GPGPUs

Baodi Shan, and Mauricio Araya-Polo

In 2024 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), May 2024

DOI Bib

@inproceedings{10596372,
  author = {Shan, Baodi and Araya-Polo, Mauricio},
  booktitle = {2024 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)},
  title = {Evaluation of Programming Models and Performance for Stencil Computation on GPGPUs},
  year = {2024},
  month = may,
  volume = {},
  number = {},
  pages = {1178-1180},
  keywords = {Solid modeling;Distributed processing;Three-dimensional displays;Computational modeling;High performance computing;Conferences;Graphics processing units;stencil computation;GPGPU;CUDA;OpenMP},
  doi = {10.1109/IPDPSW63119.2024.00198},
}

LLVM/OpenMP

MPI-Based Remote OpenMP Offloading: A More Efficient and Easy-to-Use Implementation

Baodi Shan, Mauricio Araya-Polo, Abid M. Malik, and 1 more author

In Proceedings of the 14th International Workshop on Programming Models and Applications for Multicores and Manycores, Montreal, QC, Canada, Feb 2023

DOI Bib PDF

@inproceedings{10.1145/3582514.3582519,
  author = {Shan, Baodi and Araya-Polo, Mauricio and Malik, Abid M. and Chapman, Barbara},
  title = {MPI-Based Remote OpenMP Offloading: A More Efficient and Easy-to-Use Implementation},
  year = {2023},
  month = feb,
  isbn = {9798400701153},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  url = {https://doi.org/10.1145/3582514.3582519},
  doi = {10.1145/3582514.3582519},
  booktitle = {Proceedings of the 14th International Workshop on Programming Models and Applications for Multicores and Manycores},
  pages = {50--59},
  numpages = {10},
  keywords = {OpenMP, distributed computing, GPGPU},
  location = {Montreal, QC, Canada},
  series = {PMAM'23},
}

LLVM/OpenMP
Towards Efficient Remote OpenMP Offloading

Wenbin Lu, Baodi Shan, Eric Raut, and 5 more authors

In OpenMP in a Modern World: From Multi-device Support to Meta Programming, Sep 2022

Abs Bib PDF

On modern heterogeneous HPC systems, the most popular way to realize distributed computation is the hybrid programming model of MPI+X (X being OpenMP/CUDA/etc.), as it has been proven to perform well with various scientific applications. However, application developers prefer to use a single coherent programming model over a hybrid model, as maintainability and portability decrease per additional model. Recent work [14] has shown that the OpenMP device offloading model could be used to program distributed accelerator-based HPC systems with minimal changes to the application.
@inproceedings{10.1007/978-3-031-15922-0_2, author = {Lu, Wenbin and Shan, Baodi and Raut, Eric and Meng, Jie and Araya-Polo, Mauricio and Doerfert, Johannes and Malik, Abid M. and Chapman, Barbara}, editor = {Klemm, Michael and de Supinski, Bronis R. and Klinkenberg, Jannis and Neth, Brandon}, title = {Towards Efficient Remote OpenMP Offloading}, booktitle = {OpenMP in a Modern World: From Multi-device Support to Meta Programming}, year = {2022}, month = sep, publisher = {Springer International Publishing}, address = {Cham}, pages = {17--31}, isbn = {978-3-031-15922-0}, }

LLVM

LCFI: A Fault Injection Tool for Studying Lossy Compression Error Propagation in HPC Programs

Baodi Shan, Aabid Shamji, Jiannan Tian, and 2 more authors

In 2020 IEEE International Conference on Big Data (Big Data), Dec 2020

Bib PDF

@inproceedings{shan2020lcfi,
  title = {LCFI: A Fault Injection Tool for Studying Lossy Compression Error Propagation in HPC Programs},
  author = {Shan, Baodi and Shamji, Aabid and Tian, Jiannan and Li, Guanpeng and Tao, Dingwen},
  booktitle = {2020 IEEE International Conference on Big Data (Big Data)},
  pages = {2708--2715},
  year = {2020},
  month = dec,
  organization = {IEEE},
}