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PIGEON: Optimizing CUDA Code Generator for End-to-End Training and Inference of Relational Graph Neural Networks.

, , , , , , и . CoRR, (2023)

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Israt Rayhan

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GraphStorm an Easy-to-use and Scalable Graph Neural Network Framework: From Beginners to Heroes., , , , , и . KDD, стр. 5790-5791. ACM, (2023)PIGEON: Optimizing CUDA Code Generator for End-to-End Training and Inference of Relational Graph Neural Networks., , , , , , и . CoRR, (2023)Distributed-memory parallel algorithms for sparse times tall-skinny-dense matrix multiplication., , , , , и . ICS, стр. 431-442. ACM, (2021)Adaptive sparse tiling for sparse matrix multiplication., , , , и . PPoPP, стр. 300-314. ACM, (2019)Sampled Dense Matrix Multiplication for High-Performance Machine Learning., , , , и . HiPC, стр. 32-41. IEEE, (2018)Parallel Algorithms for Masked Sparse Matrix-Matrix Products., , , , и . ICPP, стр. 10:1-10:11. ACM, (2022)Load-Balanced Sparse MTTKRP on GPUs., , , , и . IPDPS, стр. 123-133. IEEE, (2019)Hector: An Efficient Programming and Compilation Framework for Implementing Relational Graph Neural Networks in GPU Architectures., , , , , , и . ASPLOS (3), стр. 528-544. ACM, (2024)Optimizing Irregular Dense Operators of Heterogeneous GNN Models on GPU., , , , , и . IPDPS Workshops, стр. 199-206. IEEE, (2023)An efficient mixed-mode representation of sparse tensors., , , , , и . SC, стр. 49:1-49:25. ACM, (2019)