Meet MPCDF: Diagonalization of Sparse Matrices

Eigenvalue problems play a central role in many scientific fields, including physics, chemistry, and data analysis. When the matrix is sparse and only a small subset of eigenpairs is needed, iterative eigensolvers are the method of choice. In this talk, I'll review sparse iterative eigensolver libraries and present examples with ARPACK and SLEPc.

Meet MPCDF: A seminar of this series is given on the first Thursday of the month, from 15:30 to 16:30, and features a technical talk (ca. 20-30 minutes) about an AI, HPC or data-related topic given by a staff member of the MPCDF. In addition, this meeting offers the opportunity for the users to informally interact with MPCDF staff, in order to discuss relevant kinds of technical topics. Optionally, questions or requests for specific topics to be covered in more depth can be raised in advance via email to training@mpcdf.mpg.de.

Target audience are intermediate to advanced users of MPCDF services as well as computational scientists and software developers of the MPG. Users seeking a basic introduction to MPCDF services are referred to our semi-annual online workshop "Introduction to MPCDF services" (see above) which offers a consistent introduction for new users of the MPCDF.

A registration is not necessary, just use the link on the left which directly connects you to the Zoom room of the event. The explicit connection details are

Meeting ID: 936 3550 3145

Passcode: 622791