Annual General Meeting & Naylor Lecture

Location: 
Zoom, with support from ICMS
Start Date: 
Friday 20th November, 2020
Meeting Time: 
15:00
Speakers: 
Naylor Lecture: Nicholas J. Higham (Manchester)

LMS Annual General Meeting & Naylor Lecture

The lecture is aimed at a general mathematical audience. All interested, whether LMS members or not, are most welcome to attend this event.


Programme

3.00 pm Opening of the meeting and LMS Business (open to all but with voting for members only)

Agenda and Papers

Election of the LMS Council and Nominating Committee in 2020

3.55 pm Election Results Announced.

4.00 pm  Naylor Lecture 2020: Nicholas J. Higham (Manchester)  The Mathematics of Today's Floating-Point Arithmetic.

Abstract: The 1985 IEEE standard for floating-point arithmetic brought much needed order to computer arithmetic, and for the next 30 years virtually every computer adhered to it. In the last five years or so, new hardware designed for machine learning has been introduced that offers fast mixed precision “matrix multiply-accumulate” operations, thereby complicating the picture. We discuss the mathematical aspects of the current floating-point landscape. In particular, we explain how recent probabilistic error analysis is providing new understanding of accuracy, why stochastic rounding can be beneficial, and how low precision arithmetic can be exploited to deliver accurate results more quickly. 

5.00 pm Close of Meeting.


 

Registration: Registration will be required this year and the registration form is available here. Please note registration closes at 7.00pm (GMT) on Thursday 19 November.

LMS Annual Dinner: Regretablly, the Annual Dinner will not be held after the AGM this year due to the Covid-19 pandemic and the social distancing measures in place to keep our members and guests safe. 


Graduate Student Meeting held on 16 November 2020.

This meeting was intended as an introduction to the Society Meeting on 20 November 2020.  

2.00 Opening of Meeting and Welcome

Theo Mary (Sorbonne)

Title: Mixed precision arithmetic: hardware, algorithms, and analysis 

Abstract: This lecture is concerned with floating-point arithmetic and its effect on numerical algorithms. After briefly reviewing its basic properties, we will discuss recent evolutions of floating-point arithmetic, notably the emergence of very low precisions on modern computer hardware. Low precision arithmetics have shown great potential in terms of speed but, when used on their own, they can only yield results of correspondingly low accuracy. We will present a variety of mixed precision algorithms that combine low and high precisions in order to achieve both high speed and high accuracy.

3.00 Break

3.05 Student talks commence

The meeting included 18 graduate student talks.  

4.00 Meeting closed

  Registration is closed.


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