Gordon Euhyun Moon

According to our database, Gordon Euhyun Moon authored at least 16 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Exploring Attention Sparsity to Accelerate Transformer Training on GPUs.

Bokyeong Yoon, Ah-Hyun Lee, Jinsung Kim, Gordon Euhyun Moon

IEEE Access, 2024

Layer-Wise Sparse Training of Transformer via Convolutional Flood Filling.

Bokyeong Yoon, Yoonsang Han, Gordon Euhyun Moon

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2024

Exploiting Tensor Cores in Sparse Matrix-Multivector Multiplication via Block-Sparsity-Aware Clustering.

Eunji Lee, Yoonsang Han, Gordon Euhyun Moon

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2024

Accelerated Block-Sparsity-Aware Matrix Reordering for Leveraging Tensor Cores in Sparse Matrix-Multivector Multiplication.

Eunji Lee, Yoonsang Han, Gordon Euhyun Moon

Proceedings of the Euro-Par 2024: Parallel Processing, 2024

ML-Based Dynamic Operator-Level Query Mapping for Stream Processing Systems in Heterogeneous Computing Environments.

Sejeong Oh, Gordon Euhyun Moon, Sungyong Park

Proceedings of the IEEE International Conference on Cluster Computing, 2024

2023

SPION: Layer-Wise Sparse Training of Transformer via Convolutional Flood Filling.

Bokyeong Yoon, Yoonsang Han, Gordon Euhyun Moon

CoRR, 2023

Chronica: A Data-Imbalance-Aware Scheduler for Distributed Deep Learning.

Sanha Maeng, Gordon Euhyun Moon, Sungyong Park

Proceedings of the 23rd IEEE/ACM International Symposium on Cluster, 2023

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

Parallel Training of GRU Networks with a Multi-Grid Solver for Long Sequences.

Gordon Euhyun Moon, Eric C. Cyr

CoRR, 2022

2021

Extending Sparse Tensor Accelerators to Support Multiple Compression Formats.

Eric Qin, Geonhwa Jeong, William Won, Sheng-Chun Kao, Hyoukjun Kwon, Sudarshan Srinivasan, Dipankar Das, Gordon Euhyun Moon, Sivasankaran Rajamanickam, Tushar Krishna

Proceedings of the 35th IEEE International Parallel and Distributed Processing Symposium, 2021

2020

ALO-NMF: Accelerated Locality-Optimized Non-negative Matrix Factorization.

Gordon Euhyun Moon, J. Austin Ellis, Aravind Sukumaran-Rajam, Srinivasan Parthasarathy, P. Sadayappan

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

2019

PL-NMF: Parallel Locality-Optimized Non-negative Matrix Factorization.

Gordon Euhyun Moon, Aravind Sukumaran-Rajam, Srinivasan Parthasarathy, P. Sadayappan

CoRR, 2019

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

Proceedings of the 2019 IEEE/ACM Workshop on Machine Learning in High Performance Computing Environments, 2019

2018

Parallel Latent Dirichlet Allocation on GPUs.

Gordon Euhyun Moon, Israt Nisa, Aravind Sukumaran-Rajam, Bortik Bandyopadhyay, Srinivasan Parthasarathy, P. Sadayappan

Proceedings of the Computational Science - ICCS 2018, 2018

2017

Parallel LDA with Over-Decomposition.

Gordon Euhyun Moon, Aravind Sukumaran-Rajam, P. Sadayappan

Proceedings of the 24th IEEE International Conference on High Performance Computing Workshops, 2017

2016

A Large-Scale Study in Predictability of Daily Activities and Places.

Gordon Euhyun Moon, Jihun Hamm

Proceedings of the 8th EAI International Conference on Mobile Computing, 2016