Search Results for author:
Found 7 papers, 2 papers with code
Performance Evaluation of Dynamic Scaling on MPI
Our dynamic scaling implementation allows the new MPI processes from new hosts to communicate with the original ones immediately.
Distributed, Parallel, and Cluster Computing
Global Data Science Project for COVID-19
At international level, due to the travel restrictions, the number of international flights has plunged overall at around 88 percent during March.
Time-Efficient and High-Quality Graph Partitioning for Graph Dynamic Scaling
In the case of distributed graph processing, changing the number of the graph partitions while maintaining high partitioning quality imposes serious computational overheads as typically a time-consuming graph partitioning algorithm needs to execute each time repartitioning is required.
graph partitioning
Distributed, Parallel, and Cluster Computing
Databases
Discrete Mathematics
Data Structures and Algorithms
Social and Information Networks
mdx: A Cloud Platform for Supporting Data Science and Cross-Disciplinary Research Collaborations
The growing amount of data and advances in data science have created a need for a new kind of cloud platform that provides users with flexibility, strong security, and the ability to couple with supercomputers and edge devices through high-performance networks.
Is Self-Supervised Pretraining Good for Extrapolation in Molecular Property Prediction?
In material science, the prediction of unobserved values, commonly referred to as extrapolation, is particularly critical for property prediction as it enables researchers to gain insight into materials beyond the limits of available data.
On Data Imbalance in Molecular Property Prediction with Pre-training
In this study, we propose an effective pre-training method that addresses the imbalance in input data.
Revisiting Mobility Modeling with Graph: A Graph Transformer Model for Next Point-of-Interest Recommendation
Extracting distinct fine-grained features unique to each piece of information is difficult since temporal information often includes spatial information, as users tend to visit nearby POIs.
