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# CDS Seminar (14th January 2021): Mixed Precision Algorithms in Numerical Linear Algebra : Techniques, Analysis, and Software

## 14 Jan @ 2:30 PM -- 3:30 PM

**Department of Computational and Data Sciences
Research Seminar (Online)**

**Speaker**: Dr. Srikara Pranesh, University of Manchester

**Title**: “Mixed Precision Algorithms in Numerical Linear Algebra : Techniques, Analysis, and Software”

**Venue**: Online

**Date & Time**: Jan 14 2021, 02:30 PM – 03:30 PM

__ABSTRACT:__

With constant increase in computational power, the role of numerical simulations is becoming more pronounced in science and engineering. Since numerical linear algebra (NLA) lies at the heart of many scientific computing applications, developing fast and robust algorithms with reliable software can facilitate in solving more challenging problems. In this talk I will discuss some recent advances in using low precision floating-point arithmetic in NLA algorithms. Specifically some of my recent work in the solution of dense linear system of equations.

I will begin by discussing GMRES(Generalized Minimal Residual)-based iterative refinement (GMRES-IR) method for the solution of linear system of equations, followed by a demonstration of four times speedup against state-of-the-art solver in LAPACK. Next I enumerate some mathematical issues that must be addressed to ensure robust implementation of GMRES-IR in software, and discuss possible remedies for these issues. Extension of these ideas to least squares problems will also be discussed. I will conclude the talk with a list of open problems in NLA where usage of low precision floating-point arithmetic can have speed and energy benefits

__BIOGRAPHY__

Dr. Srikara Pranesh is a research associate in numerical linear algebra group, department of mathematics, University of Manchester. Prior to this he obtained his PhD from Indian Institute of Science in 2018. His main research interests include numerical analysis, numerical linear algebra, and mathematical software.

**Host Faculty: Prof. Soumyendu Raha**