A Large-Scale Study in Predictability of Daily Activities and Places. - Gordon Euhyun Moon; Jihun Hamm (MobiCASE, 2016)

Parallel LDA with Over-Decomposition. - Gordon Euhyun Moon; Aravind Sukumaran-Rajam; P. Sadayappan (HiPC Workshops, 2017)

Parallel Latent Dirichlet Allocation on GPUs. - Gordon Euhyun Moon; Israt Nisa; Aravind Sukumaran-Rajam; Bortik Bandyopadhyay; Srinivasan Parthasarathy 001; P. Sadayappan (ICCS (2), 2018)

Parallel Data-Local Training for Optimizing Word2Vec Embeddings for Word and Graph Embeddings. - Gordon Euhyun Moon; Denis Newman-Griffis; Jinsung Kim; Aravind Sukumaran-Rajam; Eric Fosler-Lussier; P. Sadayappan (MLHPC@SC, 2019)

PL-NMF: Parallel Locality-Optimized Non-negative Matrix Factorization. - Gordon Euhyun Moon; Aravind Sukumaran-Rajam; Srinivasan Parthasarathy 001; P. Sadayappan (CoRR, 2019)

ALO-NMF: Accelerated Locality-Optimized Non-negative Matrix Factorization. - Gordon Euhyun Moon; J. Austin Ellis; Aravind Sukumaran-Rajam; Srinivasan Parthasarathy 001; P. Sadayappan (KDD, 2020)

Extending Sparse Tensor Accelerators to Support Multiple Compression Formats. - Eric Qin 001; Geonhwa Jeong; William Won; Sheng-Chun Kao; Hyoukjun Kwon; Sudarshan Srinivasan; Dipankar Das 002; Gordon Euhyun Moon; Sivasankaran Rajamanickam; Tushar Krishna (IPDPS, 2021)

Parallel Training of GRU Networks with a Multi-Grid Solver for Long Sequences. - Gordon Euhyun Moon; Eric C. Cyr (CoRR, 2022)

Evaluating Spatial Accelerator Architectures with Tiled Matrix-Matrix Multiplication. - Gordon Euhyun Moon; Hyoukjun Kwon; Geonhwa Jeong; Prasanth Chatarasi; Sivasankaran Rajamanickam; Tushar Krishna (IEEE Trans. Parallel Distributed Syst., 2022)

Chronica: A Data-Imbalance-Aware Scheduler for Distributed Deep Learning. - Sanha Maeng; Gordon Euhyun Moon; Sungyong Park (CCGrid, 2023)

SPION: Layer-Wise Sparse Training of Transformer via Convolutional Flood Filling. - Bokyeong Yoon; Yoonsang Han; Gordon Euhyun Moon (CoRR, 2023)

ML-Based Dynamic Operator-Level Query Mapping for Stream Processing Systems in Heterogeneous Computing Environments. - Sejeong Oh; Gordon Euhyun Moon; Sungyong Park (CLUSTER, 2024)

Accelerated Block-Sparsity-Aware Matrix Reordering for Leveraging Tensor Cores in Sparse Matrix-Multivector Multiplication. - Eunji Lee; Yoonsang Han; Gordon Euhyun Moon (Euro-Par (3), 2024)

Exploiting Tensor Cores in Sparse Matrix-Multivector Multiplication via Block-Sparsity-Aware Clustering. - Eunji Lee; Yoonsang Han; Gordon Euhyun Moon (IPDPS (Workshops), 2024)

Layer-Wise Sparse Training of Transformer via Convolutional Flood Filling. - Bokyeong Yoon; Yoonsang Han; Gordon Euhyun Moon (PAKDD (2), 2024)

Exploring Attention Sparsity to Accelerate Transformer Training on GPUs. - Bokyeong Yoon; Ah-Hyun Lee; Jinsung Kim; Gordon Euhyun Moon (IEEE Access, 2024)

Efficient GNN-based social recommender systems through social graph refinement. - Sangmin Ga; Paul Hyunbin Cho; Gordon Euhyun Moon; Sungwon Jung (J. Supercomput., 2025)