Plurrrr

a tumblelog
week 01, 2021

The M1 MacBook Air is the best computer I've ever owned

I started a new job recently so I had the opportunity to get one of the new M1 MacBooks, I decided to go with the Air. The reviews have been very positive and I’m here to tell you: it is indeed an amazing device. The performance feels a lot better than my MacBook Pro 16”, which is only a year old and about 3x the price.

When I got the Mac I set out with the goal of avoiding Intel builds of software as much as possible and using native whenever possible unless it’s absolutely impossible.

Source: The M1 MacBook Air is the best computer I've ever owned, an article by Bouke van der Bijl.

Deep Learning's Most Important Ideas - A Brief Historical Review

Deep Learning is an extremely fast-moving field and the huge number of research papers and ideas can be overwhelming. Even seasoned researchers have a hard time telling company PR from real breakthroughs. The goal of this post is to review those ideas that have stood the test of time, which is perhaps the only significance test one should rely on. These ideas, or improvements of them, have been used over and over again. They're known to work.

Source: Deep Learning's Most Important Ideas - A Brief Historical Review, an article by Denny Britz.

The Quest for Minimal Docker Images, part 1

When getting started with containers, it’s pretty easy to be shocked by the size of the images that we build. We’re going to review a number of techniques to reduce image size, without sacrificing developers’ and ops’ convenience. In this first part, we will talk about multi-stage builds, because that’s where anyone should start if they want to reduce the size of their images. We will also explain the differences between static and dynamic linking, as well as why we should care about that. This will be the occasion to introduce Alpine.

Source: The Quest for Minimal Docker Images, part 1, an article by Jérôme Petazzoni.

Why mmap is faster than system calls

When I ask my colleagues why mmap is faster than system calls, the answer is inevitably “system call overhead”: the cost of crossing the boundary between the user space and the kernel. It turns out that this overhead is more nuanced than I used to think, so let’s look under the hood to understand the performance differences.

Source: Why mmap is faster than system calls, an article by Alexandra (Sasha) Fedorova.

Scipy Lecture Notes

Tutorials on the scientific Python ecosystem: a quick introduction to central tools and techniques. The different chapters each correspond to a 1 to 2 hours course with increasing level of expertise, from beginner to expert.

Source: Scipy Lecture Notes.

How Tail Call Optimization Works

Most undergraduate computer sciences courses teach students about tail call optimization (TCO), and even if you don't have a formal computer science background the concept is talked about enough that you might be familiar with it anyway, especially if you've ever done any functional programming. However, I think the way TCO is normally taught is very confusing, because it's normally taught in the context of recursion. It's taught this way because without TCO many recursive functions can blow up the stack causing a stack overflow. Therefore by teaching people about TCO in the context of recursion, you can teach them why optimizing compilers (or interpreters) can run tail recursive code efficiently and without causing a stack overflow.

However, the recursion case for TCO is actually not the norm: in fact, if you're writing code in C, C++, or any most other languages with an optimizing compiler you're almost certainly having TCO applied all over your programs even if they don't use any recursion whatsoever. Understanding the non-recursive case of TCO is actually a lot simpler, and if you understand the non-recursive case you realize that there's actually nothing special whatsoever about how TCO is applied to recursive functions.

Source: How Tail Call Optimization Works, an article by Evan Klitzke.

Metaballs and Marching Squares

Something about making visually interesting simulations to play with just gets me really excited about programming, particularly when there’s some cool algorithm or bit of math backing it.

Source: Metaballs and Marching Squares, an article by Jamie Wong.

Two Weeks Without Evil Mode

In the last two weeks, I’ve challenged myself to leave the comfort of Vim and dive into the unknown chasm of Emacs with no Evil keybindings.

Two Weeks Without Evil Mode, an article by Patrick Skiba.

dd, bs= and why you should use conv=fsync

Long story short: If one uses dd with a bigger block size (>= 4096), be sure to use either the oflag=direct or conv=fsync option to have proper error reporting while writing data to a device. I would prefer conv=fsync, dd will then fsync() the file handle once and report the error, without having the performance impact which oflag=direct has.

Source: dd, bs= and why you should use conv=fsync, an article by Michael Ablassmeier.

The GL-MT300N A $20 hackable Linux Router

The Gl.iNET GL-MT300N is a $21/£19 travel router designed for WIFI on the go. The device runs a custom version of OpenWRT that is easily replaced with a standard release of OpenWRT making this device an ultra cheap hackable Dual NIC router/SBC.

Source: The GL-MT300N A $20 hackable Linux Router, an article by James Dawson.

Memory access on the Apple M1 processor

When a program is mostly just accessing memory randomly, a standard cost model is to count the number of distinct random accesses. The general idea is that memory access is much slower than most other computational tasks.

Source: Memory access on the Apple M1 processor, an article by Daniel Lemire.

How to Navigate Emacs using Evil Mode

Emacs Evil mode is an extensible Vi layer for Emacs. It adds a set of Vi(m) key bindings and features to Emacs to give it a more modal feel, and lets you rely less on the pinky-accessed CTRL key when manipulating text. Where Emacs uses more key combinations and commands, Evil mode brings Vi’s operators and motions to execute text operations.

Source: How to Navigate Emacs using Evil Mode.

Midnight Sun: A novel

He calls himself Ulf—as good a name as any, he thinks—and the only thing he’s looking for is a place where he won’t be found by Oslo’s most notorious drug lord: the Fisherman. He was once the Fisherman’s fixer, but after betraying him, Ulf is now the one his former boss needs fixed—which may not be a problem for a man whose criminal reach is boundless. When Ulf gets off the bus in Kåsund, on Norway’s far northeastern border, he sees a “flat, monotonous, bleak landscape . . . the perfect hiding place. Hopefully.”

In the evening I started in Midnight Sun: A novel by Jo Nesbø. This is the sequel to the excellent Blood on Snow so I have high expectations.

Tags are coming to tumblelog

The 19th of October I got an email from Jos of The Organization about his proposal for adding tags to tumblelog.

For the past months I have been thinking about this on and off. And I decided to use a YAML block to specify meta data, just like pandoc uses. For example:

---
tags: [tumblelog]
...

## Tags are coming to tumblelog

So, last Saturday I started tagging Plurrrr's articles. It took me 3 days, several hours each day, to do most of the 1600+ articles. Today I did the last few and some refinements. Next is adding the actual code to tumblelog as currently my version only skips tags.

The Strategic SwiftUI Data Flow Guide

SwiftUI offers several mechanisms to pass data between views.

Such abundance can make it hard to decide which data flow mechanism fits any particular situation.

Those decisions cannot be taken in isolation. As in many other cases, we need to keep an app’s architecture in mind to make the correct choice.

Source: The Strategic SwiftUI Data Flow Guide (+ Infographic).

Comment on Unix versus Emacs

I receive messages from time to time asking me to share my views on the topic of whether Emacs can fit into a Unix-centric workflow. One such email arrived in my inbox yesterday. I replied to it and asked whether I could publish the answer on my website, while omitting all private information.

Source: Comment on Unix versus Emacs, an article by Protesilaos Stavrou.

Blood on Snow: excellent

In the evening I finished Blood on Snow: A novel by Jo Nesbø. An excellent story and a quick read. Recommended!

Keep track of environment variables in go

When we configure our programs, we usually have three ways to do it: config files, cli flags and environment variables. While all of these three options are a solid way to go, with CI/CD environments you are usually instructed to use environment variables, e.g. envvars.

If we look at the golang’s os package documentation, we can see that it offers multiple ways to read envvars:

  • Environ which gives you raw list of strings in form of “key=value” which you can parse your self
  • Getenv which gives you the envvar value if it exists, or an empty string
  • LookupEnv which is similar to Getenv, but also returns you a boolean telling you if the variable exists or not

Source: Keep track of environment variables in go.