2 citations · 5 across the 4 of their papers we have counts for
6 papers
Optimizing Graph Transformer Networks with Graph-based Techniques
Loc Hoang, Udit Agarwal, Gurbinder Gill +4
Graph transformer networks (GTN) are a variant of graph convolutional networks (GCN) that are targeted to heterogeneous graphs in which nodes and edges have associated type informa…
Sandslash: A Two-Level Framework for Efficient Graph Pattern Mining
Xuhao Chen, Roshan Dathathri, Gurbinder Gill +2
Graph pattern mining (GPM) is used in diverse application areas including social network analysis, bioinformatics, and chemical engineering. Existing GPM frameworks either provide…
An Adaptive Load Balancer For Graph Analytical Applications on GPUs
Vishwesh Jatala, Loc Hoang, Roshan Dathathri +3
Load-balancing among the threads of a GPU for graph analytics workloads is difficult because of the irregular nature of graph applications and the high variability in vertex degree…
Pangolin: An Efficient and Flexible Graph Pattern Mining System on CPU and GPU
Xuhao Chen, Roshan Dathathri, Gurbinder Gill +1
There is growing interest in graph pattern mining (GPM) problems such as motif counting. GPM systems have been developed to provide unified interfaces for programming algorithms fo…
Distributed Training of Embeddings using Graph Analytics
Gurbinder Gill, Roshan Dathathri, Saeed Maleki +3
Many applications today, such as NLP, network analysis, and code analysis, rely on semantically embedding objects into low-dimensional fixed-length vectors. Such embeddings natural…
Single Machine Graph Analytics on Massive Datasets Using Intel Optane DC Persistent Memory
Gurbinder Gill, Roshan Dathathri, Loc Hoang +2
Intel Optane DC Persistent Memory (Optane PMM) is a new kind of byte-addressable memory with higher density and lower cost than DRAM. This enables the design of affordable systems…