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Entirely by chance, while looking over the event calendar of Bike PGH, I came across the Rail 66 Clarion Summerfest 2023 Time Trial. I had never done something like this, so I signed up.

Imagine a shared resource, such as a compute server. Users can submit jobs to the server. The resource is “free”, in the sense that no costs are imposed on the users. The question is how to best assign and prioritize jobs when multiple users submit jobs simultaneously.

The (notorious) Dirac delta-function is usually introduced as a function with the following properties: \[ \delta(x) = \begin{cases} 0 & \qquad x \neq 0 \\ \text{“$\infty$”} & \qquad x = 0 \end{cases} \]

Over the holidays, I sat down and wrote a casual turn-based strategy game. Aside from the obvious fun aspect, one major motivation was to gain experience with the pyglet game library, which I wanted to evaluate as a potentially general, light-weight GUI library for Python.

Over the holidays, I had the opportunity to work on a spare time project, and so I sat down and wrote a casual, turn-based strategy game; a variant (you might say: a clone) of the KDE game Konquest.

Finding a realistic (or at least, realistic looking) initial configuration of game objects or simulation particles can be a challenge. The desired configuration should appear to be both “random” and at the same time “spatially uniform”, without objects clustering together or overlapping.

I have started to get interested in Hidden Markov Models (HMM). As a warm-up, I prepared a pure Python implementation of the relevant algorithms (github).

This site is generated using Hugo. Getting the site up and running was nothing short of a nightmare, which I have documented elsewhere. But things are working now, and Hugo makes adding new content very easy indeed. It therefore seems a good opportunity to reflect back and revisit the whole “Static Site Generator” a.k.a. “JamStack” topic, from a greater distance.

The “Newsvendor Problem” is a classic problem in inventory and supply-chain management: how much product to carry in stock in the face of uncertain demand?

The problem is obviously of interest in its own right, but it is also an archetypical problem, meaning that variations of it arise frequently and in different contexts. It is therefore valuable to know “how to think about” this kind of problem; in particular, since in its simplest form, it has a closed-form, analytic solution.

In a moment of nostalgia, I picked up my copy of “The Art of UNIX Programming” by Eric S. Raymond (esr) and flipped through it again. It’s a book I’ve had since when it came out in 2004, and that I’ve always been quite fond of. I was looking forward to a review of “the way the future was”, as viewed from the early 2000s. So, it came as a bit of a surprise to me to find that the book seems to have aged rather poorly.