Vladimir Vlassov

Profiling Memory Vulnerability of Big-Data Applications

2016

Motivated by the increasing popularity of hosting in-memory big-data analytics in cloud, we present a profiling methodology that can understand how different memory subsystems, i.e., cache and memory bandwidth, are susceptible to the impact of …

Node Context Selection in Transformer-Based Graph Representation Learning Models

2022 · 2022 IEEE International Conference on Big Data (Big Data)

Transformer models have great potential in Graph Representation Learning (GRL) for efficiently scaling the learning process on large datasets and solving many challenges presented in Graph Neural Networks, e.g., oversmoothing and suspended animation. To represent …