Gordon Euhyun Moon

20 papers A* 1A 2B 1C 1Journal 8Unranked 7
YearRankTypeTitle / Venue / Authors
2025 A conf
D-HAT: Dynamic Hypergraph Representation Learning with Attention-Based Multi-Level Hypergraph Sampling.
CIKM
Ah-Hyun Lee, Gordon Euhyun Moon
2025 J jnl
Efficient GNN-based social recommender systems through social graph refinement.
J. Supercomput.
Sangmin Ga, Paul Hyunbin Cho, Gordon Euhyun Moon, Sungwon Jung
2024 — conf
Accelerated Block-Sparsity-Aware Matrix Reordering for Leveraging Tensor Cores in Sparse Matrix-Multivector Multiplication.
Euro-Par (3)
Eunji Lee, Yoonsang Han, Gordon Euhyun Moon
2024 — conf
Exploiting Tensor Cores in Sparse Matrix-Multivector Multiplication via Block-Sparsity-Aware Clustering.
IPDPS (Workshops)
Eunji Lee, Yoonsang Han, Gordon Euhyun Moon
2024 J jnl
Exploring Attention Sparsity to Accelerate Transformer Training on GPUs.
IEEE Access
Bokyeong Yoon, Ah-Hyun Lee, Jinsung Kim, Gordon Euhyun Moon
2024 — conf
Layer-Wise Sparse Training of Transformer via Convolutional Flood Filling.
PAKDD (2)
Bokyeong Yoon, Yoonsang Han, Gordon Euhyun Moon
2024 C conf
ML-Based Dynamic Operator-Level Query Mapping for Stream Processing Systems in Heterogeneous Computing Environments.
CLUSTER
Sejeong Oh, Gordon Euhyun Moon, Sungyong Park
2023 B conf
Chronica: A Data-Imbalance-Aware Scheduler for Distributed Deep Learning.
CCGrid
Sanha Maeng, Gordon Euhyun Moon, Sungyong Park
2023 J jnl
SPION: Layer-Wise Sparse Training of Transformer via Convolutional Flood Filling.
CoRR
Bokyeong Yoon, Yoonsang Han, Gordon Euhyun Moon
2022 J jnl
Evaluating Spatial Accelerator Architectures with Tiled Matrix-Matrix Multiplication.
IEEE Trans. Parallel Distributed Syst.
Gordon Euhyun Moon, Hyoukjun Kwon, Geonhwa Jeong, Prasanth Chatarasi, Sivasankaran Rajamanickam, Tushar Krishna
2022 J jnl
Parallel Training of GRU Networks with a Multi-Grid Solver for Long Sequences.
CoRR
Gordon Euhyun Moon, Eric C. Cyr
2021 J jnl
Evaluating Spatial Accelerator Architectures with Tiled Matrix-Matrix Multiplication.
CoRR
Gordon Euhyun Moon, Hyoukjun Kwon, Geonhwa Jeong, Prasanth Chatarasi, Sivasankaran Rajamanickam, Tushar Krishna
2021 A conf
Extending Sparse Tensor Accelerators to Support Multiple Compression Formats.
IPDPS
Eric Qin, Geonhwa Jeong, William Won, Sheng-Chun Kao, Hyoukjun Kwon, Sudarshan Srinivasan, Dipankar Das, Gordon Euhyun Moon, Sivasankaran Rajamanickam, Tushar Krishna
2021 J jnl
Extending Sparse Tensor Accelerators to Support Multiple Compression Formats.
CoRR
Eric Qin, Geonhwa Jeong, William Won, Sheng-Chun Kao, Hyoukjun Kwon, Sudarshan Srinivasan, Dipankar Das, Gordon Euhyun Moon, Sivasankaran Rajamanickam, Tushar Krishna
2020 A* conf
ALO-NMF: Accelerated Locality-Optimized Non-negative Matrix Factorization.
KDD
Gordon Euhyun Moon, J. Austin Ellis, Aravind Sukumaran-Rajam, Srinivasan Parthasarathy, P. Sadayappan
2019 J jnl
PL-NMF: Parallel Locality-Optimized Non-negative Matrix Factorization.
CoRR
Gordon Euhyun Moon, Aravind Sukumaran-Rajam, Srinivasan Parthasarathy, P. Sadayappan
2019 — conf
Parallel Data-Local Training for Optimizing Word2Vec Embeddings for Word and Graph Embeddings.
MLHPC@SC
Gordon Euhyun Moon, Denis Newman-Griffis, Jinsung Kim, Aravind Sukumaran-Rajam, Eric Fosler-Lussier, P. Sadayappan
2018 — conf
Parallel Latent Dirichlet Allocation on GPUs.
ICCS (2)
Gordon Euhyun Moon, Israt Nisa, Aravind Sukumaran-Rajam, Bortik Bandyopadhyay, Srinivasan Parthasarathy, P. Sadayappan
2017 — conf
Parallel LDA with Over-Decomposition.
HiPC Workshops
Gordon Euhyun Moon, Aravind Sukumaran-Rajam, P. Sadayappan
2016 — conf
A Large-Scale Study in Predictability of Daily Activities and Places.
MobiCASE
Gordon Euhyun Moon, Jihun Hamm