7 citations · 7 across the 4 of their papers we have counts for
4 papers
Parallel Training of GRU Networks with a Multi-Grid Solver for Long Sequences
Gordon Euhyun Moon, Eric C. Cyr
Parallelizing Gated Recurrent Unit (GRU) networks is a challenging task, as the training procedure of GRU is inherently sequential. Prior efforts to parallelize GRU have largely fo…
Evaluating Spatial Accelerator Architectures with Tiled Matrix-Matrix Multiplication
Gordon E. Moon, Hyoukjun Kwon, Geonhwa Jeong +3
There is a growing interest in custom spatial accelerators for machine learning applications. These accelerators employ a spatial array of processing elements (PEs) interacting via…
Extending Sparse Tensor Accelerators to Support Multiple Compression Formats
Eric Qin, Geonhwa Jeong, William Won +7
Sparsity, which occurs in both scientific applications and Deep Learning (DL) models, has been a key target of optimization within recent ASIC accelerators due to the potential mem…
PL-NMF: Parallel Locality-Optimized Non-negative Matrix Factorization
Gordon E. Moon, Aravind Sukumaran-Rajam, Srinivasan Parthasarathy +1
Non-negative Matrix Factorization (NMF) is a key kernel for unsupervised dimension reduction used in a wide range of applications, including topic modeling, recommender systems and…