Numerical Analysis Group Internal Seminar

Please note that the list below only shows forthcoming events, which may not include regular events that have not yet been entered for the forthcoming term. Please see the past events page for a list of all seminar series that the department has on offer.

Past events in this series
20 February 2018
14:30
Bogdan Toader
Abstract

We consider the problem of localising non-negative point sources, namely finding their locations and amplitudes from noisy samples which consist of the convolution of the input signal with a known kernel (e.g. Gaussian). In contrast to the existing literature, which focuses on TV-norm minimisation, we analyse the feasibility problem. In the presence of noise, we show that the localised error is proportional to the level of noise and depends on the distance between each source and the closest samples. This is achieved using duality and considering the spectrum of the associated sampling matrix.

  • Numerical Analysis Group Internal Seminar
27 February 2018
14:00
Abstract

The object of this talk is a class of generalised Newtonian fluids with implicit constitutive law.
Both in the steady and the unsteady case, existence of weak solutions was proven by Bul\'\i{}\v{c}ek et al. (2009, 2012) and the main challenge is the small growth exponent qq and the implicit law.
I will discuss the application of a splitting and regularising strategy to show convergence of FEM approximations to weak solutions of the flow. 
In the steady case this allows to cover the full range of growth exponents and thus generalises existing work of Diening et al. (2013). If time permits, I will also address the unsteady case.
This is joint work with Endre Suli.

  • Numerical Analysis Group Internal Seminar
6 March 2018
14:00
Oliver Sheridan-Methven
Abstract

The latest CPUs by Intel and ARM support vectorised operations, where a single set of instructions (e.g. add, multiple, bit shift, XOR, etc.) are performed in parallel for small batches of data. This can provide great performance improvements if each parallel instruction performs the same operation, but carries the risk of performance loss if each needs to perform different tasks (e.g. if else conditions). I will present the work I have done so far looking into how to recover the full performance of the hardware, and some of the challenges faced when trading off between ever larger parallel tasks, risks of tasks diverging, and how certain coding styles might be modified for memory bandwidth limited applications. Examples will be taken from finance and Monte Carlo applications, inspecting some standard maths library functions and possibly random number generation.

  • Numerical Analysis Group Internal Seminar
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