Message from the Workshop Chairs

This workshop’s program includes a keynote, two invited talks, six papers and four lightning talks. Paper topics include enabling shared memory access to Python processes in task-based programming models; workarounds for Python workflows in HPC environments; experiences in developing a distributed Agent-Based modelling (ABM) distributed toolkit in Python; new contributions to a distributed, asynchronous many-task (AMT) computing framework that encompasses the entire computing process, from a Jupyter front-end for managing code and results to the collection and visualization of performance data; a new high-performance Python API with a C++ core to represent data as a table and provide distributed data operations; and a computation environment for HPC that aims to accelerate microstructural analytics scaling Numpy workflows to enable multidimensional image analysis of diverse specimens.