EQUILIBRIA: Co-Optimizing Energy and Latency in Online ML-based Stream Processing Systems [paper]
Sejeong Oh, Soyang Baek, Gordon E. Moon, Sungyong Park
The 25th IEEE International Symposium on Cluster, Cloud and Internet Computing (CCGrid), Tromsø, Norway, 2025 [BK21+ Computer Science IF 1]
Efficient GNN-based Social Recommender Systems through Social Graph Refinement [paper]
Sangmin Ga, Paul Hyunbin Cho, Gordon E. Moon, Sungwon Jung
The Journal of Supercomputing, 2025 [SCI]
Tensor Core-Adapted Sparse Matrix Multiplication for Accelerating Sparse Deep Neural Networks [paper]
Yoonsang Han, Inseo Kim, Jinsung Kim, Gordon E. Moon
Electronics, 2024 [SCI]
ML-based Dynamic Operator-Level Query Mapping for Stream Processing Systems in Heterogeneous Computing Environments [paper]
Sejeong Oh, Gordon E. Moon, Sungyong Park
IEEE International Conference on Cluster Computing (CLUSTER), Kobe, Japan, 2024 [BK21+ Computer Science IF 1]
Exploring Attention Sparsity to Accelerate Transformer Training on GPUs [paper]
Bokyeong Yoon, Ah-hyun Lee, Jinsung Kim, Gordon E. Moon
IEEE Access, 2024 [SCI]
Accelerated Block-Sparsity-Aware Matrix Reordering for Leveraging Tensor Cores in Sparse Matrix-Multivector Multiplication [paper]
Eunji Lee*, Yoonsang Han*, Gordon E. Moon (* equal contribution)
The 30th International European Conference on Parallel and Distributed Computing (Euro-Par), Madrid, Spain, 2024 [BK21+ Computer Science IF 1]
Layer-Wise Sparse Training of Transformer via Convolutional Flood Filling [paper]
Bokyeong Yoon, Yoonsang Han, Gordon E. Moon
The 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Taipei, Taiwan, 2024 [BK21+ Computer Science IF 1]
Chronica: A Data-Imbalance-Aware Scheduler for Distributed Deep Learning [paper]
Sanha Maeng, Gordon E. Moon, Sungyong Park
The 23rd IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGrid), Bangalore, India, 2023 [BK21+ Computer Science IF 1]
Parallel Training of GRU Networks with a Multi-Grid Solver for Long Sequences [paper]
Gordon E. Moon, Eric C. Cyr
International Conference on Learning Representations (ICLR), 2022 [KIISE Outstanding S]
Evaluating Spatial Accelerator Architectures with Tiled Matrix-Matrix Multiplication [paper]
Gordon E. Moon, Hyoukjun Kwon, Geonhwa Jeong, Prasanth Chatarasi, Sivasankaran Rajamanickam, Tushar Krishna
IEEE Transactions on Parallel and Distributed Systems (TPDS), 2022 [SCI]
Extending Sparse Tensor Accelerators to Support Multiple Compression Formats [paper]
Eric Qin, Geonhwa Jeong, William Won, Sheng-Chun Kao, Hyoukjun Kwon, Sudarshan Srinivasan, Dipankar Das, Gordon E. Moon, Sivasankaran Rajamanickam, Tushar Krishna
IEEE International Parallel & Distributed Processing Symposium (IPDPS), 2021 [BK21+ Computer Science IF 2]
ALO-NMF: Accelerated Locality-Optimized Non-negative Matrix Factorization [paper]
Gordon E. Moon, J. Austin Ellis, Aravind Sukumaran-Rajam, Srinivasan Parthasarathy, P. Sadayappan
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2020 [BK21+ Computer Science IF 4]
Parallel Data-Local Training for Optimizing Word2Vec Embeddings for Word and Graph Embeddings [paper]
Gordon E. Moon, Denis Newman-Griffis, Jinsung Kim, Aravind Sukumaran-Rajam, Eric Fosler-Lussier, P. Sadayappan
International Workshop on Machine Learning in High-Performance Computing Environments (MLHPC), Denver, CO, USA, 2019
Multi-Level Sparse Matrix Reordering for Accelerating Sparse Matrix-Matrix Multiplication
Sohyeon Kim, Sangwon Bae, Euhyun Moon
Korea Computer Congress (KCC), 2025
Transformer-based Recommender Systems with Social Information
Cheolhee Kim, Bokyeong Yoon, Paul Hyunbin Cho, Euhyun Moon
Korea Software Congress (KSC), 2023
Heterogeneity-Aware Calibration for Federated Learning with Non-IID Data
Sooyeon Kim, Haeeun Lee, Eunji Lee, Euhyun Moon
Korea Software Congress (KSC), 2023
Leveraging Convolution Filter for Sparsifying Attention in Transformer
Bokyeong Yoon, Euhyun Moon
Korea Computer Congress (KCC), 2023
A Data Imbalance Minimization Strategy for Scalable Deep Learning Training
Sanha Maeng, Euhyun Moon, Sungyong Park
Journal of KIISE, 2023