Gordon Euhyun Moon

According to our database, Gordon Euhyun Moon authored at least 11 papers between 2016 and 2023.

Collaborative distances:

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

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