7 citations · 10 across the 5 of their papers we have counts for
6 papers
COGNATE: Acceleration of Sparse Tensor Programs on Emerging Hardware using Transfer Learning
Chamika Sudusinghe, Gerasimos Gerogiannis, Damitha Lenadora +3
Sparse tensor programs are essential in deep learning and graph analytics, driving the need for optimized processing. To meet this demand, specialized hardware accelerators are bei…
SENSEi: Input-Sensitive Compilation for Accelerating GNNs
Damitha Lenadora, Vimarsh Sathia, Gerasimos Gerogiannis +3
Over the years, many frameworks and optimization techniques have been proposed to accelerate graph neural networks (GNNs). Compared to the optimizations explored in these systems,…
Hybrid Cloud and HPC Approach to High-Performance Dataframes
Kaiying Shan, Niranda Perera, Damitha Lenadora +6
Data pre-processing is a fundamental component in any data-driven application. With the increasing complexity of data processing operations and volume of data, Cylon, a distributed…
High Performance Dataframes from Parallel Processing Patterns
Niranda Perera, Supun Kamburugamuve, Chathura Widanage +7
The data science community today has embraced the concept of Dataframes as the de facto standard for data representation and manipulation. Ease of use, massive operator coverage, a…
A Fast, Scalable, Universal Approach For Distributed Data Aggregations
Niranda Perera, Vibhatha Abeykoon, Chathura Widanage +7
In the current era of Big Data, data engineering has transformed into an essential field of study across many branches of science. Advancements in Artificial Intelligence (AI) have…
Exploratory Analysis of a Social Media Network in Sri Lanka during the COVID-19 Virus Outbreak
Damitha Lenadora, Gihan Gamage, Dilantha Haputhanthri +2
During the COVID-19 pandemic, multiple aspects of human life were subjected to unprecedented changes, globally. In Sri Lanka, a developing country located in South Asia, it was pos…