8 citations · 9 across the 4 of their papers we have counts for
4 papers
Employing Artificial Intelligence to Steer Exascale Workflows with Colmena
Logan Ward, J. Gregory Pauloski, Valerie Hayot-Sasson +6
Computational workflows are a common class of application on supercomputers, yet the loosely coupled and heterogeneous nature of workflows often fails to take full advantage of the…
TaPS: A Performance Evaluation Suite for Task-based Execution Frameworks
J. Gregory Pauloski, Valerie Hayot-Sasson, Maxime Gonthier +5
Task-based execution frameworks, such as parallel programming libraries, computational workflow systems, and function-as-a-service platforms, enable the composition of distinct tas…
Trillion Parameter AI Serving Infrastructure for Scientific Discovery: A Survey and Vision
Nathaniel Hudson, J. Gregory Pauloski, Matt Baughman +13
Deep learning methods are transforming research, enabling new techniques, and ultimately leading to new discoveries. As the demand for more capable AI models continues to grow, we…
DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies
Shuaiwen Leon Song, Bonnie Kruft, Minjia Zhang +89
In the upcoming decade, deep learning may revolutionize the natural sciences, enhancing our capacity to model and predict natural occurrences. This could herald a new era of scient…