7 papers
In-depth Analysis On Parallel Processing Patterns for High-Performance Dataframes
Niranda Perera, Arup Kumar Sarker, Mills Staylor +7
The Data Science domain has expanded monumentally in both research and industry communities during the past decade, predominantly owing to the Big Data revolution. Artificial Intel…
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…
HySec-Flow: Privacy-Preserving Genomic Computing with SGX-based Big-Data Analytics Framework
Chathura Widanage, Weijie Liu, Jiayu Li +4
Trusted execution environments (TEE) such as Intel's Software Guard Extension (SGX) have been widely studied to boost security and privacy protection for the computation of sensiti…
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…