DBScholar

Back to papers

BladeDISC: Optimizing Dynamic Shape Machine Learning Workloads via Compiler Approach

Summary: BladeDISC is a compiler-driven optimizer for dynamic-shape ML workloads, tackling fusion and codegen with unknown shapes. Key ideas: symbolic shape representation and shape-information propagation to enable shape-agnostic fusion and generic codegen. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6772
Venue
SIGMOD
Year
2023
Pagerank
5.2634238e-05
Overall Rank
9,475 | 35.00%
DOI
10.1145/3617327

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{zheng_sigmod23,
        title = {{BladeDISC: Optimizing Dynamic Shape Machine Learning Workloads via Compiler Approach}},
        author = {Zheng, Zhen and Pan, Zaifeng and Wang, Dalin and Zhu, Kai and Zhao, Wenyi and Guo, Tianyou and Qiu, Xiafei and Sun, Minmin and Bai, Junjie and Zhang, Feng and Du, Xiaoyong and Zhai, Jidong and Lin, Wei},
        series = {{SIGMOD} '23},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3617327},
        url = {https://dl.acm.org/doi/10.1145/3617327},
        year = {2023}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 30 of 30 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
23 Efficiently Compiling Efficient Query Plans for Modern Hardware 2011 VLDB 0.00054886415
53 Eddies: Continuously Adaptive Query Processing 2000 SIGMOD 0.00041071971
492 Robust Query Processing through Progressive Optimization 2004 SIGMOD 0.0001756877
521 PyTorch Distributed: Experiences on Accelerating Data Parallel Training 2020 VLDB 0.0001713368
1,079 Hybrid Parallelization Strategies for Large-Scale Machine Learning in SystemML 2014 VLDB 0.00012258469
1,241 Balsa: Learning a Query Optimizer Without Expert Demonstrations 2022 SIGMOD 0.00011521639
1,442 An Architecture for Compiling UDF-centric Workflows 2015 VLDB 0.00010778486
1,574 Pipelined Query Processing in Coprocessor Environments 2018 SIGMOD 0.00010321274
1,666 HippogriffDB: Balancing I/O and GPU Bandwidth in Big Data Analytics 2016 VLDB 0.00010068964
1,768 Tuplex: Data Science in Python at Native Code Speed 2021 SIGMOD 9.8041636e-05
2,316 Evaluating End-to-End Optimization for Data Analytics Applications in Weld 2018 VLDB 8.7596739e-05
2,688 Accelerating Recommendation System Training by Leveraging Popular Choices 2022 VLDB 8.2564305e-05
2,695 NeutronStar: Distributed GNN Training with Hybrid Dependency Management 2022 SIGMOD 8.2468134e-05
3,205 On Optimizing Operator Fusion Plans for Large-Scale Machine Learning in SystemML 2018 VLDB 7.6386536e-05
4,049 Resource Elasticity for Large-Scale Machine Learning 2015 SIGMOD 6.9369379e-05
4,089 TCUDB: Accelerating Database with Tensor Processors 2022 SIGMOD 6.9096857e-05
4,215 Designing an Open Framework for Query Optimization and Compilation 2022 VLDB 6.8275676e-05
4,912 HET-GMP: A Graph-based System Approach to Scaling Large Embedding Model Training 2022 SIGMOD 6.4481656e-05
4,956 Heterogeneity-Aware Distributed Machine Learning Training via Partial Reduce 2021 SIGMOD 6.4290135e-05
5,003 Galvatron: Efficient Transformer Training over Multiple GPUs Using Automatic Parallelism 2023 VLDB 6.4065691e-05
5,807 Improving Execution Efficiency of Just-in-time Compilation based Query Processing on GPUs 2021 VLDB 6.0805143e-05
6,022 NuPS: A Parameter Server for Machine Learning with Non-Uniform Parameter Access 2022 SIGMOD 6.0046123e-05
6,349 Grizzly: Efficient Stream Processing Through Adaptive Query Compilation 2020 SIGMOD 5.9049304e-05
7,662 Measuring and Optimizing Distributed Array Programs 2016 VLDB 5.5732476e-05
8,350 FuseME: Distributed Matrix Computation Engine based on Cuboid-based Fused Operator and Plan Generation 2022 SIGMOD 5.4460082e-05
8,368 Excalibur: A Virtual Machine for Adaptive Fine-grained JIT-Compiled Query Execution based on VOILA 2023 VLDB 5.4419148e-05
8,637 Harmony: Overcoming the Hurdles of GPU Memory Capacity to Train Massive DNN Models on Commodity Servers 2022 VLDB 5.3954887e-05
9,000 Optimizing Inference Serving on Serverless Platforms 2022 VLDB 5.3350531e-05
9,292 COMET: A Novel Memory-Efficient Deep Learning Training Framework by Using Error-Bounded Lossy Compression 2022 VLDB 5.2908632e-05
9,826 ETO: Accelerating Optimization of DNN Operators by High-Performance Tensor Program Reuse 2022 VLDB 5.2141422e-05
Previous Page 1 / 1 Next

Semantically Similar Papers