Jiannan Tian
Orcid: 0000-0003-1101-9148
According to our database1,
Jiannan Tian
authored at least 36 papers
between 2019 and 2024.
Collaborative distances:
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Bibliography
2024
IEEE Trans. Parallel Distributed Syst., March, 2024
Proc. VLDB Endow., February, 2024
2023
SZ3: A Modular Framework for Composing Prediction-Based Error-Bounded Lossy Compressors.
IEEE Trans. Big Data, April, 2023
CoRR, 2023
CoRR, 2023
AMRIC: A Novel In Situ Lossy Compression Framework for Efficient I/O in Adaptive Mesh Refinement Applications.
Proceedings of the International Conference for High Performance Computing, 2023
Analyzing Impact of Data Reduction Techniques on Visualization for AMR Applications Using AMReX Framework.
Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, 2023
Proceedings of the 37th International Conference on Supercomputing, 2023
HEAT: A Highly Efficient and Affordable Training System for Collaborative Filtering Based Recommendation on CPUs.
Proceedings of the 37th International Conference on Supercomputing, 2023
FZ-GPU: A Fast and High-Ratio Lossy Compressor for Scientific Computing Applications on GPUs.
Proceedings of the 32nd International Symposium on High-Performance Parallel and Distributed Computing, 2023
2022
Proc. VLDB Endow., 2022
SOLAR: A Highly Optimized Data Loading Framework for Distributed Training of CNN-based Scientific Surrogates.
CoRR, 2022
Optimizing Error-Bounded Lossy Compression for Three-Dimensional Adaptive Mesh Refinement Simulations.
CoRR, 2022
CoRR, 2022
Proceedings of the 30th International Symposium on Modeling, 2022
Proceedings of the 2022 IEEE International Parallel and Distributed Processing Symposium, 2022
CEAZ: accelerating parallel I/O via hardware-algorithm co-designed adaptive lossy compression.
Proceedings of the ICS '22: 2022 International Conference on Supercomputing, Virtual Event, June 28, 2022
Improving Prediction-Based Lossy Compression Dramatically via Ratio-Quality Modeling.
Proceedings of the 38th IEEE International Conference on Data Engineering, 2022
Proceedings of the HPDC '22: The 31st International Symposium on High-Performance Parallel and Distributed Computing, Minneapolis, MN, USA, 27 June 2022, 2022
TAC: Optimizing Error-Bounded Lossy Compression for Three-Dimensional Adaptive Mesh Refinement Simulations.
Proceedings of the HPDC '22: The 31st International Symposium on High-Performance Parallel and Distributed Computing, Minneapolis, MN, USA, 27 June 2022, 2022
Proceedings of the 32nd International Conference on Field-Programmable Logic and Applications, 2022
HBMax: Optimizing Memory Efficiency for Parallel Influence Maximization on Multicore Architectures.
Proceedings of the International Conference on Parallel Architectures and Compilation Techniques, 2022
2021
CEAZ: Accelerating Parallel I/O via Hardware-Algorithm Co-Design of Efficient and Adaptive Lossy Compression.
CoRR, 2021
CoRR, 2021
Proceedings of the 35th IEEE International Parallel and Distributed Processing Symposium, 2021
ClickTrain: efficient and accurate end-to-end deep learning training via fine-grained architecture-preserving pruning.
Proceedings of the ICS '21: 2021 International Conference on Supercomputing, 2021
Adaptive Configuration of In Situ Lossy Compression for Cosmology Simulations via Fine-Grained Rate-Quality Modeling.
Proceedings of the HPDC '21: The 30th International Symposium on High-Performance Parallel and Distributed Computing, 2021
Proceedings of the IEEE International Conference on Cluster Computing, 2021
2020
An Efficient End-to-End Deep Learning Training Framework via Fine-Grained Pattern-Based Pruning.
CoRR, 2020
waveSZ: a hardware-algorithm co-design of efficient lossy compression for scientific data.
Proceedings of the PPoPP '20: 25th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2020
Understanding GPU-Based Lossy Compression for Extreme-Scale Cosmological Simulations.
Proceedings of the 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2020
LCFI: A Fault Injection Tool for Studying Lossy Compression Error Propagation in HPC Programs.
Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020
cuSZ: An Efficient GPU-Based Error-Bounded Lossy Compression Framework for Scientific Data.
Proceedings of the PACT '20: International Conference on Parallel Architectures and Compilation Techniques, 2020
2019
DeepSZ: A Novel Framework to Compress Deep Neural Networks by Using Error-Bounded Lossy Compression.
Proceedings of the 28th International Symposium on High-Performance Parallel and Distributed Computing, 2019
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019