Notebooks
Post talking about some problems with Jupyter Notebook, especially the reproducibility problem:
Blog
My personal blog containing short random notes that I collect over time on the most varied subjects.
Marimo
Interesting alternative to Jupyter Notebook, but with other goals and features. The idea is to embed everything inside a single .py file, instead of an .ipynb file. The .py file is used both for the graphical interface (interactive web app) and for command line execution. It tries to eliminate some of Jupyter's reproducibility issues. It has features such as integration with package and project managers, such as uv. It's worth checking out.
Internals
Internals refers to the inner workings of compilers or interpreters, detailing how they are structured and operate, documenting their internal structures such as the low-level runtime library, intermediate representations, control graph analysis and optimization, machine descriptions, and more.
HP-41
The 1979 HP-41 series programmable calculator, which was produced until 1990, and was used in the Space Shuttle missions, has a processor called "Coconut" (or 1LE3 CPU), RAM, ROM, I/O, and uses the interpreted programming language FOCAL ("Forty One Calculator Language"). The operating system and the interpreter are stored in ROM, and were programmed using the Coconut processor assembly language also called MCODE (or "M-Code").
Retrocomputing Archive
The site is a repository dedicated to the preservation and sharing of software and documentation for classical computer systems, including a wide variety of classical computer systems and their software, such as the CP/M operating system. The site hosts software and documentation of all types for classical computer systems, providing a valuable resource for enthusiasts and researchers interested in retrocomputing. Maintained by classiccmp.org community.
Loss Landscape
Very nice WebGL application to visualize the loss landscape for some common ANN. Currently features the models Resnet-20 (short/no-short), Resnet-56 (short/no-short), Vgg 16 and DenseNet 121.
Neural Network Optimization
Good post by Matthew Stewart's "Neural Network Optimization" from June 27, 2019.
https://towardsdatascience.com/neural-network-optimization-7ca72d4db3e0
Using PINN for Inverse Problems
Last edited: 2024-05-28
My personal notes about the seminar Using Physics-informed Neural Networks for Inverse Problems by João Pereira - IMPA at National Scientific Computing Laboratory (LNCC) on 2024-05-13.
LNCC SDumont supercomputer upgrade
The National Scientific Computing Laboratory (LNCC) and Eviden/Atos signed a new contract worth us$ 19.4 million, which will allow the machine to go from the current 5.1 Petaflop/s to 17 Petaflop/s of capacity. The technology will be based on the BullSequana XH3000 architecture, and with the expansion it will be the most powerful supercomputer in Latin America dedicated to academic studies.
https://agenciabrasil.ebc.com.br/geral/noticia/2024-04/supercomputador-mais-potente-do-pais-tera-capacidade-aumentada (in Portuguese)
LNCC SDumont website (in Portuguese): https://sdumont.lncc.br
Parallel Spectral Numerical Methods
Very nice Wikibook based on Parallel Spectral Numerical Methods by Chen et al. (2012) from University of Michigan. Discusses how to solve ordinary differential equations (ODE) and partial differential equations (PDE) using separation of variables. Next, it introduces numerical time-stepping schemes that can be used to solve ODEs and PDEs. This is followed by an introduction to pseudo spectral methods through an overview of the discrete Fourier Transform (DFT) and the Fast Fourier Transform (FFT) algorithm that is used to quickly calculate the DFT. Finally it will combine all of these to solve a couple of different PDEs first in a serial setting and then in a parallel setting. The programs will use Matlab and Fortran. A Python implementation of some of the Matlab programs is also provided.
https://en.wikibooks.org/wiki/Parallel_Spectral_Numerical_Methods