most citedPyTorch-Direct: Enabling GPU Centric Data Access for Very Large Graph Neural Network Training with Irregular Accesses

3 citations · 3 across the 2 of their papers we have counts for

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cs.DC2020

At-Scale Sparse Deep Neural Network Inference with Efficient GPU Implementation

Mert Hidayetoglu, Carl Pearson, Vikram Sharma Mailthody +4

This paper presents GPU performance optimization and scaling results for inference models of the Sparse Deep Neural Network Challenge 2020. Demands for network quality have increas…

cs.DC2020

EMOGI: Efficient Memory-access for Out-of-memory Graph-traversal In GPUs

Seung Won Min, Vikram Sharma Mailthody, Zaid Qureshi +3

Modern analytics and recommendation systems are increasingly based on graph data that capture the relations between entities being analyzed. Practical graphs come in huge sizes, of…