7 papers
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…
Scientific Image Restoration Anywhere
Vibhatha Abeykoon, Zhengchun Liu, Rajkumar Kettimuthu +2
The use of deep learning models within scientific experimental facilities frequently requires low-latency inference, so that, for example, quality control operations can be perform…