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Bernat Font

@fontb.bsky.social

Assistant Professor in Data-Informed CFD at TU Delft. Interested in turbulent flow simulations 🌀 data-driven models 🤖 numerical methods ∫→∑ and high-performance computing ⚡️. I generally talk about open source, music, and science.

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Lorena A Barba@labarba.bsky.social · 10mo ago

𝗖𝗼𝗺𝗲𝘁 𝗿𝘂𝗻𝘀 𝗰𝗶𝗿𝗰𝗹𝗲𝘀 𝗮𝗿𝗼𝘂𝗻𝗱 𝗝𝘂𝗽𝘆𝘁𝗲𝗿 Friends, I watched an AI agent complete my students' coding exercises in real-time, and I'm shook 🤯 I tested Perplexity's Comet browser on a Jupyter notebook with eigenvalue problems I assigned to my class… (video at the bottom of this thread)

Bernat Font@fontb.bsky.social · 11mo ago

Slides for the talk avaliable here! b-fg.github.io/EFDC2_2025/m... I'm loving this quarto + reveal.js for creating html presentations. Now that's portable!

main

b-fg.github.io

Bernat Font@fontb.bsky.social · 12mo ago

Tomorrow at noon, I will be presenting at EFDC2 in Dublin! I will talk about our new mesh-free SINDy framework, collaboration with M. Gao and N. Kutz, for system dynamics identification on unstructured, scarce, and noisy data 🗓️ Session: tinyurl.com/c7up564z 🔗 Preprint: arxiv.org/abs/2505.16058

Bernat Font@fontb.bsky.social · last yr.

I am happy to share that I have been awarded a Dutch Research Council (NWO) Veni personal grant! www.nwo.nl/en/news/200-...

200 researchers receive Veni grants | NWO

Identifying when children are most at risk of being taken into care within youth protection programmes. Improving the quality of surgery with video analysis. The interaction between wind and vegetation for optimising the resilience of coastal dunes. Developing reliable algorithms for statistical learning with interactive decision science. These are four of the two hundred research projects by researchers who have been awarded a Veni grant. Each researcher will receive a maximum of 320,000 euros. The grant is an incentive for adventurous, talented and groundbreaking researchers to further develop their own research ideas over the next three years.

nwo.nl

JuliaHub@juliahub.bsky.social · last yr.

Makie v0.24 is out! One of the biggest architectural updates yet—bringing better performance, cleaner internals, and new plotting capabilities. A big step toward Makie 1.0. makie.org/website/blog... #JuliaLang #OpenSource #Visualization #Plotting #HPC #MakiePlots #WGLMakie #Makie

Makie v0.24 focuses on a comprehensive overhaul of our internal architecture, specifically replacing Observables in our backend code with a more robust system. This fundamental change touches nearly every component of the codebase, making it one of our most ambitious refactoring efforts to date.

makie.org

Bernat Font@fontb.bsky.social · last yr.

This seminar is now available in our YouTube channel. Check it out! 🔗 youtu.be/ly7mBFf8esM

Large-Scale CFD seminar series 8. Dr. Francesc Verdugo

YouTube video by Large-scale CFD

youtu.be

Bernat Font@fontb.bsky.social · last yr.

We would like to invite you to join the next Large-scale CFD online seminar by Dr. Francesc Verdugo (UV Amsterdam) on "Large-scale sparse linear algebra with PartitionedArrays" github.com/PartitionedA... Date: 27/03/2025, 5pm CET Seminar link: tinyurl.com/4hy47ezv #HPC #MPI #JuliaLang

Abstract: We present PartitionedArrays, a large-scale sparse linear algebra library fully implemented in the Julia programming language. The key differentiating feature of PartitionedArrays with respect to related libraries is that it introduces an alternative programming model to implement its distributed algorithms. This model allows one to decouple the logic behind data partition and communication from the number of processing units used to run the code. A logically distributed algorithm can be run both on a single and multiple process. This delivers an improved balance between code productivity and performance in the development of large-scale scientific computing applications. The parallel logic can be debugged on a single process, avoiding deadlocks, race conditions, and other practical challenges of debugging parallel code, and permits using standard sequential debuggers. At the same time, the resulting code can be deployed on a supercomputer with performance similar of native MPI-based applications. PartitionedArrays provides distributed linear algebra data structures (vectors and sparse matrices), and key computational kernels (distributed sparse matrix-vector product and sparse matrix-matrix products), as well as distributed algebraic multigrid preconditioners. These tools have been successful in the implementation of finite element solvers scaling to tens of thousands of CPU cores. In this presentation, we show the software design of PartitionedArrays and a hands-on overview to its main features. The source code of the library is freely available at https://github.com/PartitionedArrays/PartitionedArrays.jl.
Bernat Font@fontb.bsky.social · last yr.

using an explicit LES model and a central difference scheme for the convective flux, we match nicely experimental results from the 70s! (doi.org/10.1017/S002...) Results with N=64^3 cells and Smagorinsky-Lilly turbulence model

Energy cascade of decaying homogeneous isotropic turbulence with N=64^3 cells
Bernat Font@fontb.bsky.social · last yr.

Playing a bit with our WaterLily.jl #CFD #JuliaLang solver and homogeneous isotropic decaying turbulence 🌀 128^3 grid running on my local #GPU ⚡ visualizing in real-time with @makie.org github.com/WaterLily-jl...