26 citations · 135 across the 21 of their papers we have counts for
42 papers
Submission-Aware Reviewer Profiling for Reviewer Recommender System
Omer Anjum, Alok Kamatar, Toby Liang +2
Assigning qualified, unbiased and interested reviewers to paper submissions is vital for maintaining the integrity and quality of the academic publishing system and providing valua…
A Compiler Framework for Optimizing Dynamic Parallelism on GPUs
Mhd Ghaith Olabi, Juan Gómez Luna, Onur Mutlu +2
Dynamic parallelism on GPUs allows GPU threads to dynamically launch other GPU threads. It is useful in applications with nested parallelism, particularly where the amount of neste…
Measuring Fine-Grained Domain Relevance of Terms: A Hierarchical Core-Fringe Approach
Jie Huang, Kevin Chen-Chuan Chang, Jinjun Xiong +1
We propose to measure fine-grained domain relevance - the degree that a term is relevant to a broad (e.g., computer science) or narrow (e.g., deep learning) domain. Such measuremen…
Pseudo-IoU: Improving Label Assignment in Anchor-Free Object Detection
Jiachen Li, Bowen Cheng, Rogerio Feris +4
Current anchor-free object detectors are quite simple and effective yet lack accurate label assignment methods, which limits their potential in competing with classic anchor-based…
Large Graph Convolutional Network Training with GPU-Oriented Data Communication Architecture
Seung Won Min, Kun Wu, Sitao Huang +5
Graph Convolutional Networks (GCNs) are increasingly adopted in large-scale graph-based recommender systems. Training GCN requires the minibatch generator traversing graphs and sam…
PyTorch-Direct: Enabling GPU Centric Data Access for Very Large Graph Neural Network Training with Irregular Accesses
Seung Won Min, Kun Wu, Sitao Huang +5
With the increasing adoption of graph neural networks (GNNs) in the machine learning community, GPUs have become an essential tool to accelerate GNN training. However, training GNN…