We look forward to seeing you in person on Tuesday, November 29, at 4:00pm. Join in person at 2405 Siebel Center for Computer Science, 201 N. Goodwin Ave.
Python has become a popular choice of language for various applications ranging from scientific computing to machine learning in recent years. Libraries such as numpy, scipy, etc. have made it possible to achieve high performance while maintaining productivity on a single node. Frameworks such as charm4py and mpi4py have helped achieve high performance on distributed systems but lack the interactivity that tools like Jupyter notebooks provide. CharmTyles aims at providing a set of abstractions working on a client-server model with a python frontend and a Charm++ program on the backend to maintain interactivity while still achieving good performance. This talk presents a dense linear algebra abstraction and a stencil computation abstraction based on this programming model.