Gordon Euhyun Moon

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 15

Top Topics

Matrix Factorization

Alternating Least Squares

Latent Dirichlet Allocation

Top Venues

Publications

Eunji Lee, Yoonsang Han, Gordon Euhyun Moon
Exploiting Tensor Cores in Sparse Matrix-Multivector Multiplication via Block-Sparsity-Aware Clustering. IPDPS (Workshops) (2024)
Bokyeong Yoon, Yoonsang Han, Gordon Euhyun Moon
Layer-Wise Sparse Training of Transformer via Convolutional Flood Filling. PAKDD (2) (2024)
Sanha Maeng, Gordon Euhyun Moon, Sungyong Park
Chronica: A Data-Imbalance-Aware Scheduler for Distributed Deep Learning. CCGrid (2023)
Bokyeong Yoon, Yoonsang Han, Gordon Euhyun Moon
SPION: Layer-Wise Sparse Training of Transformer via Convolutional Flood Filling. CoRR (2023)
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) (2022)
Gordon Euhyun Moon, Eric C. Cyr
Parallel Training of GRU Networks with a Multi-Grid Solver for Long Sequences. CoRR (2022)
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 (2021)
Gordon Euhyun Moon, Hyoukjun Kwon, Geonhwa Jeong, Prasanth Chatarasi, Sivasankaran Rajamanickam, Tushar Krishna
Evaluating Spatial Accelerator Architectures with Tiled Matrix-Matrix Multiplication. CoRR (2021)
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)
Gordon Euhyun Moon, J. Austin Ellis, Aravind Sukumaran-Rajam, Srinivasan Parthasarathy, P. Sadayappan
ALO-NMF: Accelerated Locality-Optimized Non-negative Matrix Factorization. KDD (2020)
Gordon Euhyun Moon, Aravind Sukumaran-Rajam, Srinivasan Parthasarathy, P. Sadayappan
PL-NMF: Parallel Locality-Optimized Non-negative Matrix Factorization. CoRR (2019)
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)
Gordon Euhyun Moon, Israt Nisa, Aravind Sukumaran-Rajam, Bortik Bandyopadhyay, Srinivasan Parthasarathy, P. Sadayappan
Parallel Latent Dirichlet Allocation on GPUs. ICCS (2) (2018)
Gordon Euhyun Moon, Aravind Sukumaran-Rajam, P. Sadayappan
Parallel LDA with Over-Decomposition. HiPC Workshops (2017)
Gordon Euhyun Moon, Jihun Hamm
A Large-Scale Study in Predictability of Daily Activities and Places. MobiCASE (2016)