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2020 – today
- 2024
[j2]Bokyeong Yoon
, Ah-Hyun Lee, Jinsung Kim, Gordon Euhyun Moon:
Exploring Attention Sparsity to Accelerate Transformer Training on GPUs. IEEE Access 12: 131373-131384 (2024)- [c10]Eunji Lee, Yoonsang Han, Gordon Euhyun Moon:
Accelerated Block-Sparsity-Aware Matrix Reordering for Leveraging Tensor Cores in Sparse Matrix-Multivector Multiplication. Euro-Par (3) 2024: 3-16 - [c9]Eunji Lee, Yoonsang Han, Gordon Euhyun Moon:
Exploiting Tensor Cores in Sparse Matrix-Multivector Multiplication via Block-Sparsity-Aware Clustering. IPDPS (Workshops) 2024: 1181-1183 - [c8]Bokyeong Yoon, Yoonsang Han, Gordon Euhyun Moon:
Layer-Wise Sparse Training of Transformer via Convolutional Flood Filling. PAKDD (2) 2024: 158-170 - 2023
- [c7]Sanha Maeng, Gordon Euhyun Moon, Sungyong Park:
Chronica: A Data-Imbalance-Aware Scheduler for Distributed Deep Learning. CCGrid 2023: 262-272 - [i5]Bokyeong Yoon, Yoonsang Han, Gordon Euhyun Moon:
SPION: Layer-Wise Sparse Training of Transformer via Convolutional Flood Filling. CoRR abs/2309.12578 (2023) - 2022
- [j1]Gordon Euhyun Moon, Hyoukjun Kwon, Geonhwa Jeong, Prasanth Chatarasi, Sivasankaran Rajamanickam, Tushar Krishna:
Evaluating Spatial Accelerator Architectures with Tiled Matrix-Matrix Multiplication. IEEE Trans. Parallel Distributed Syst. 33(4): 1002-1014 (2022) - [i4]Gordon Euhyun Moon, Eric C. Cyr:
Parallel Training of GRU Networks with a Multi-Grid Solver for Long Sequences. CoRR abs/2203.04738 (2022) - 2021
- [c6]Eric Qin, Geonhwa Jeong, William Won, Sheng-Chun Kao, Hyoukjun Kwon, Sudarshan Srinivasan, Dipankar Das, Gordon Euhyun Moon, Sivasankaran Rajamanickam, Tushar Krishna:
Extending Sparse Tensor Accelerators to Support Multiple Compression Formats. IPDPS 2021: 1014-1024 - [i3]Eric Qin, Geonhwa Jeong, William Won, Sheng-Chun Kao, Hyoukjun Kwon, Sudarshan Srinivasan, Dipankar Das, Gordon Euhyun Moon, Sivasankaran Rajamanickam, Tushar Krishna:
Extending Sparse Tensor Accelerators to Support Multiple Compression Formats. CoRR abs/2103.10452 (2021) - [i2]Gordon Euhyun Moon, Hyoukjun Kwon, Geonhwa Jeong, Prasanth Chatarasi, Sivasankaran Rajamanickam, Tushar Krishna:
Evaluating Spatial Accelerator Architectures with Tiled Matrix-Matrix Multiplication. CoRR abs/2106.10499 (2021) - 2020
- [c5]Gordon Euhyun Moon, J. Austin Ellis, Aravind Sukumaran-Rajam, Srinivasan Parthasarathy, P. Sadayappan:
ALO-NMF: Accelerated Locality-Optimized Non-negative Matrix Factorization. KDD 2020: 1758-1767
2010 – 2019
- 2019
- [c4]Gordon Euhyun Moon, Denis Newman-Griffis, Jinsung Kim, Aravind Sukumaran-Rajam, Eric Fosler-Lussier, P. Sadayappan:
Parallel Data-Local Training for Optimizing Word2Vec Embeddings for Word and Graph Embeddings. MLHPC@SC 2019: 44-55 - [i1]Gordon Euhyun Moon, Aravind Sukumaran-Rajam, Srinivasan Parthasarathy, P. Sadayappan:
PL-NMF: Parallel Locality-Optimized Non-negative Matrix Factorization. CoRR abs/1904.07935 (2019) - 2018
- [c3]Gordon Euhyun Moon, Israt Nisa, Aravind Sukumaran-Rajam, Bortik Bandyopadhyay, Srinivasan Parthasarathy, P. Sadayappan:
Parallel Latent Dirichlet Allocation on GPUs. ICCS (2) 2018: 259-272 - 2017
- [c2]Gordon Euhyun Moon, Aravind Sukumaran-Rajam, P. Sadayappan:
Parallel LDA with Over-Decomposition. HiPC Workshops 2017: 25-31 - 2016
- [c1]Gordon Euhyun Moon, Jihun Hamm:
A Large-Scale Study in Predictability of Daily Activities and Places. MobiCASE 2016: 86-97
Coauthor Index
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