Diving for Treasure in a Sea of Scientific Literature: Extracting Scientific Information from Free Text Articles

Aarthi Koripelly, University of Chicago
25 January 2021
It has become impossible for researchers to keep up with the more than 2.5 million publications published every year. We explore scalable approaches for automatically extracting relations from scientific papers (e.g., melting point of a polymer). We implement a dependency parser-based relation extraction model to understand relationships without the need for a Named Entity tagger, integrate several word embeddings models and custom tokenization to boost learning performance for scientific text. The exponential growth of scientific...

SciFlow project using Parsl to execute Scientific Workflows on HPC resources

Amanda Wijewickrama and Rajini Wijayawardana, University of Colombo School of Computing, Sri Lanka
19 January 2021
The majority of tasks that we, as researchers and analysts, perform, are conveniently expressible as scientific workflows. These workflows provide abstraction, integration and reusability, thereby easing the scientific knowledge discovery process. However, as the complexity of the scientific problem increases, the complexity of the workflow too increases proportionately. To facilitate such interactions, workflows utilize complex connectors. The SciFlow framework provides a set of compositional channel connectors in a control thread, which can be used to...

A Look at Parsl and Funcx: Two Excellent Parallel Scripting Tools for Clouds and Supercomputers

Dennis Gannon, School of Informatics, Computing and Engineering, Indiana University
11 January 2021
In 2019, Yadu N Babuji, Anna Woodard, Zhuozhao Li, Daniel S. Katz, Ben Clifford, Rohan Kumar, Lukasz Lacinski, Ryan Chard, Justin Michael Joseph Wozniak, Michael Wilde and Kyle Chard published a paper in HPDC ’19 entitled Parsl: Pervasive Parallel Programming in Python. I have been looking forward to finding the time to dig into it and give it a try. The time did arrive and, as I started to dig, I discovered some of this...