7 citations · 8 across the 6 of their papers we have counts for
9 papers
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…
HPTMT Parallel Operators for High Performance Data Science & Data Engineering
Vibhatha Abeykoon, Supun Kamburugamuve, Chathura Widanage +5
Data-intensive applications are becoming commonplace in all science disciplines. They are comprised of a rich set of sub-domains such as data engineering, deep learning, and machin…
HPTMT: Operator-Based Architecture for Scalable High-Performance Data-Intensive Frameworks
Supun Kamburugamuve, Chathura Widanage, Niranda Perera +5
Data-intensive applications impact many domains, and their steadily increasing size and complexity demands high-performance, highly usable environments. We integrate a set of ideas…
Data Engineering for HPC with Python
Vibhatha Abeykoon, Niranda Perera, Chathura Widanage +6
Data engineering is becoming an increasingly important part of scientific discoveries with the adoption of deep learning and machine learning. Data engineering deals with a variety…
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…
High Performance Data Engineering Everywhere
Chathura Widanage, Niranda Perera, Vibhatha Abeykoon +7
The amazing advances being made in the fields of machine and deep learning are a highlight of the Big Data era for both enterprise and research communities. Modern applications req…
Families of Distributed Memory Parallel Graph Algorithms from Self-Stabilizing Kernels-An SSSP Case Study
Thejaka Kanewala, Marcin Zalewski, Martina Barnas +1
Self-stabilizing algorithms are an important because of their robustness and guaranteed convergence. Starting from any arbitrary state, a self-stabilizing algorithm is guaranteed t…
Abstract Graph Machine
Thejaka Amila Kanewala, Marcin Zalewski, Andrew Lumsdaine
An Abstract Graph Machine(AGM) is an abstract model for distributed memory parallel stabilizing graph algorithms. A stabilizing algorithm starts from a particular initial state and…
The Anatomy of Large-Scale Distributed Graph Algorithms
Jesun Sahariar Firoz, Thejaka Amila Kanewala, Marcin Zalewski +2
The increasing complexity of the software/hardware stack of modern supercomputers results in explosion of parameters. The performance analysis becomes a truly experimental science,…