NHR PerfLab Seminar on September 12 (online): The Linear Algebra Mapping Problem and how programming languages solve it

You are cordially invited to the next NHR PerfLab Seminar talk.
The event will take place online via Zoom.

Title:    The Linear Algebra Mapping Problem
           and how programming languages solve it

Speaker:  Paolo Bientinesi,
           University of Umeå,
           Director, HPC2N

Date:   Tuesday, September 12, 2023
Time:   2:00 p.m. - 3:00 p.m. CEST

Zoom link: https://fau.zoom.us/j/68603607738

Abstract:

The computational workflows of countless applications across science and engineering involve operations on matrices. To support such a broad
demand, the numerical linear algebra community has delivered over the course of the years an assortment of high-performance libraries,
offering application-independent kernels that serve as universal building blocks. However, despite their quality, such libraries are not
utilized as often as one would imagine. Indeed, often times their usability is limited by an interface and a level of abstraction that are
inconvenient for many users. Furthermore, typically users face operations that are more complex than those offered by the library
kernels, and the decomposition of a target operation in terms of a set of available kernels is far from being a trivial task. We refer to this
task as the "Linear Algebra Mapping Problem" (LAMP). This problem is solved internally by all those programming languages that offer
high-level matrix syntax, such as Matlab, Python, R, and C++ in combination with libraries such as Armadillo or Eigen. These languages
tremendously help users' productivity. However, we show that in terms of performance, they are still immature as their solutions to LAMPs are
severely suboptimal.

Short bio:

Paolo Bientinesi is Professor in High-Performance Computing at Umeå University, and director of the High-Performance Computing Center North
(HPC2N, Sweden). He completed his Laurea degree in computer science at the University of Pisa (Italy, 1998), and received his Ph.D. from The
University of Texas at Austin (USA, 2006). Before moving to Sweden, he was professor at RWTH Aachen University (Germany, 2008). His research
interests include matrix and tensor operations, automatic algorithm & code generation, performance modeling, and computer music. Paolo
Bientinesi leads the research group High-Performance and Automatic Computing (HPAC, hpac.cs.umu.se, https://github.com/HPAC

Web version of this announcement: https://hpc.fau.de/2023/09/05/nhr-perflab-seminar-the-linear-algebra-mapping-problem-and-how-programming-languages-solve-it-september-12-nline/

See https://hpc.fau.de/research/nhr-perflab-seminar-series/ for past and upcoming NHR PerfLab seminar talks.