31 citations · 65 across the 3 of their papers we have counts for
3 papers
cs.IR2022★ 21 cited
A GPU-specialized Inference Parameter Server for Large-Scale Deep Recommendation Models
Yingcan Wei, Matthias Langer, Fan Yu +4
Recommendation systems are of crucial importance for a variety of modern apps and web services, such as news feeds, social networks, e-commerce, search, etc. To achieve peak predic…
cs.DC2022★ 31 cited
Merlin HugeCTR: GPU-accelerated Recommender System Training and Inference
Joey Wang, Yingcan Wei, Minseok Lee +9
In this talk, we introduce Merlin HugeCTR. Merlin HugeCTR is an open source, GPU-accelerated integration framework for click-through rate estimation. It optimizes both training and…
cs.DC2020★ 13 cited
Accelerating Sparse DNN Models without Hardware-Support via Tile-Wise Sparsity
Cong Guo, Bo Yang Hsueh, Jingwen Leng +7
Network pruning can reduce the high computation cost of deep neural network (DNN) models. However, to maintain their accuracies, sparse models often carry randomly-distributed weig…