
Sparsely thinking of 2021
A selection of research on numerical analysis, mathematical optimisation, and hardware accelerators published in the past year
en , Parallel computing , Linear algebra , Numerical analysis , Mathematical optimisation ·The year 2021 is gone, which means it’s time to take a look at which publications were captured by my Google Scholar queries.

Tidying up my Google Scholar queries
Lately, I’ve realised that the diversity of my reads since the start of the pandemic has increased. This has got to the point that I feel like my Google Scholar queries don’t reflect everything I’m interested in these days.

Solving the advectiondiffusion equation in a couple of lines of code
Let’s implement the advection equation

Numerical algorithms, optimisation, and computer performance: a selection of research from 2020
I won’t bore you with clichés about how weird and difficult this year has been. Instead, I’d like to point out straightaway how large this year’s selection of papers is: more than 400 papers, which is more than twice the papers I selected last year.

A selection of papers on numerical linear algebra and parallel computing published in 2019
This year has been particularly exciting for the fields of numerical linear algebra and parallel computing. I managed to add 267 entries to my bibliography, which means a new paper about every 1.7 days on average! To me, this is a big step up compared to last year’s 56 papers.

A selection of papers on numerical linear algebra and parallel computing published in 2018
About two years ago, I setup a Google Scholar alert to stay uptodate with the literature on the topics I discussed in >my PhD dissertation</a>. I took the habit of recording the most interesting papers on Jabref, together with their abstract. Here is a list of such papers for 2018 (up until today):