Reading and writing, part 1: locations and locks

Transport-Oriented Growth and Procedural Trees

Helios: hyperscale indexing for the cloud & edge – part 1

Issue #24

10/26/2020

A Byte of Coding Issue #24
Greetings Ƹ̵̡Ӝ̵̨̄Ʒ
I hope you all had a lovely weekend. I've moved into a high-rise building for the time being, and had the realization that I totally feel like a modern day wizard. I spend all day alone inside my tower, making something fantastical out of symbols and characters using my mysterious box powered by magical rocks that hum with energy. All I'm missing is the pointy hat and long beard.

What are some cool projects you guys and gals have seen recently? Or worked on? I'd love to hear about them, so let me know!

Abra-ca-dabra, here's the issue.

Reading and writing, part 1: locations and locks

Published: 28 September 2020
Tags: javascript, ruby, java


Data races are a huge pain in the ass in programming. They're hard to identify when you're both writing code and running it. It's always worth learning techniques that can help you spot the problems before they actually arise. In this exemplary article, James Coglan uses examples in JavaScript, Ruby, and Java to highlight simple scenarios in which these pesky errors can occur. Don't be fooled by the triviality of the examples though; their existence in your own code might seem unlikely, but that might just be because they're masked by complexity.

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Transport-Oriented Growth and Procedural Trees

Published: 26 October 2020
Tags: cpp, math, graphics


Trees are pretty cool. The tallest one is ~116 m, they turn CO2 into oxygen, for some their leaves change color seasonally, others don't change at all, and they can be found pretty much everywhere. And when you model them with math, you can come up with some cool graphics. Nicholas McDonald's article is all about using C++ and a binary tree to model tree branch growth, specifically focusing on the splitting process, leading to some very pretty graphics of trees growing.

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Helios: hyperscale indexing for the cloud & edge – part 1

Published: 26 October 2020
Tags:
networking, optimization, data


Currently a lot of the computing structure in the world is based on a very centralized system. You have clients, who query some central server, that carries out any computation and data storage, then returns the results. Although this is fine when you're not processing a lot of data or requests, it become very expensive or very slow, very quickly when scaled up. In this introductory article, Adrian Colyer present Microsoft's solution for large scale computation and data storage; 'a federated differential dataflow style system that processes and materializes just what is needed at each layer'.

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Stats (updated daily)

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Opens: 666

Clicks: 192

Link Clicks Clicks % Unique Clicks Unique Clicks %
Read Full Article 74 38.54% 57 35.85
Read Full Article 64 33.33% 56 35.22
Read Full Article 45 23.44% 37 23.27
differential dataflow 5 2.60% 5 3.14
one 2 1.04% 2 1.26
Donate Here 2 1.04% 2 1.26

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