259 citations · 527 across the 9 of their papers we have counts for
10 papers
WRATH: Workload Resilience Across Task Hierarchies in Task-based Parallel Programming Frameworks
Sicheng Zhou, Zhuozhao Li, Valérie Hayot-Sasson +6
Failures in Task-based Parallel Programming (TBPP) can severely degrade performance and result in incomplete or incorrect outcomes. Existing failure-handling approaches, including…
UniFaaS: Programming across Distributed Cyberinfrastructure with Federated Function Serving
Yifei Li, Ryan Chard, Yadu Babuji +3
Modern scientific applications are increasingly decomposable into individual functions that may be deployed across distributed and diverse cyberinfrastructure such as supercomputer…
funcX: Federated Function as a Service for Science
Zhuozhao Li, Ryan Chard, Yadu Babuji +9
funcX is a distributed function as a service (FaaS) platform that enables flexible, scalable, and high performance remote function execution. Unlike centralized FaaS systems, funcX…
Extended Abstract: Productive Parallel Programming with Parsl
Kyle Chard, Yadu Babuji, Anna Woodard +6
Parsl is a parallel programming library for Python that aims to make it easy to specify parallelism in programs and to realize that parallelism on arbitrary parallel and distribute…
IMPECCABLE: Integrated Modeling PipelinE for COVID Cure by Assessing Better LEads
Aymen Al Saadi, Dario Alfe, Yadu Babuji +33
The drug discovery process currently employed in the pharmaceutical industry typically requires about 10 years and $2-3 billion to deliver one new drug. This is both too expensive…
Targeting SARS-CoV-2 with AI- and HPC-enabled Lead Generation: A First Data Release
Yadu Babuji, Ben Blaiszik, Tom Brettin +15
Researchers across the globe are seeking to rapidly repurpose existing drugs or discover new drugs to counter the the novel coronavirus disease (COVID-19) caused by severe acute re…
funcX: A Federated Function Serving Fabric for Science
Ryan Chard, Yadu Babuji, Zhuozhao Li +5
Exploding data volumes and velocities, new computational methods and platforms, and ubiquitous connectivity demand new approaches to computation in the sciences. These new approach…
Serverless Supercomputing: High Performance Function as a Service for Science
Ryan Chard, Tyler J. Skluzacek, Zhuozhao Li +6
Growing data volumes and velocities are driving exciting new methods across the sciences in which data analytics and machine learning are increasingly intertwined with research. Th…
Parsl: Pervasive Parallel Programming in Python
Yadu Babuji, Anna Woodard, Zhuozhao Li +9
High-level programming languages such as Python are increasingly used to provide intuitive interfaces to libraries written in lower-level languages and for assembling applications…
DLHub: Model and Data Serving for Science
Ryan Chard, Zhuozhao Li, Kyle Chard +7
While the Machine Learning (ML) landscape is evolving rapidly, there has been a relative lag in the development of the "learning systems" needed to enable broad adoption. Furthermo…