In-situ workflows are a particular class of scientific workflows where different components
(such as simulation, visualization, machine learning, and data analysis) run concurrently. In …

With the increasing amount of digital data available for analysis and simulation, the class of
I/O-intensive HPC workflows is fated to quickly expand, further exacerbating the …

Testing is one of the most important steps in software development–it ensures the quality of
software. Continuous Integration (CI) is a widely used testing standard that can report …

Scientific workflows on High-Performance Computing (HPC) consist of multiple data
processing and computing tasks with dependencies. Efficiently scheduling computing …

In-situ workflow is a type of workflow where multiple components execute concurrently with
data flowing continuously. The adoption of in-situ workflows not only accelerates mission …

In this thesis we introduce a new scheduling algorithm MARS based on a cost-aware multi-
scalable reinforcement learning approach, which serves as an intermediate layer between …

Testing is one of the most important steps in software development–it ensures the quality of
software. Continuous Integration (CI) is a widely used testing standard that can report …

Scientific computation increasingly consists of a workflow of interrelated tasks.
Containerization can make workflow systems more manageable, reproducible, and portable …

In this paper, we propose a workflow orchestration system that is able to run workflows on
both HPC systems and in the cloud using HPC containers. Most existing workflow …

Scientific discovery increasingly depends on middleware that enables the execution of
heterogeneous workflows on heterogeneous platforms. One of the main challenges is to …