This post documents the eradication of algae from my water cooled 4 GPU build.
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Removing Algae from my Water Loop
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Building the Ultimate Deep Learning Workstation
This blogpost documents the addition of a full custom water loop and two GTX 2080 Ti GPUs to my previous build. This work was done back in November/December of 2019 but didn’t get around to doing the write up until now.
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32 Core Threadripper + Dual 2080 Ti Build Log
This post documents my recent desktop PC build featuring a 32 core threadripper processor and two 2080 Ti graphics cards. It is specced to allow for another upgrade to four 2080 Ti graphics cards with a full custom water loop. I plan to use it mostly for machine learning and simulating reinforcement learning environments. As an added bonus, it can also run Crysis at 20FPS.
How to Read 100s of Millions of Records per Second from a Single Disk
This article gives an overview of the implementation and performance of two recent additions to LocustDB, an extremely fast open-source analytics database built in Rust. The first addition is support for persistent storage, the second is an lz4 compression pass for data stored on disk or cached in memory. Benchmarking LocustDB on a dataset of 1.46 billion taxi rides demonstrates excellent performance for cold queries, reaching > 95% of sequential read speed on SSD and > 70% of sequential read speed on HDD. Comparing to ClickHouse, queries with similar data volume are as fast or faster, and disk space usage is reduced by 40%.
How to Analyze Billions of Records per Second on a Single Desktop PC
Introduction
This article gives an overview of LocustDB [1], a new and extremely fast open-source analytics database built in Rust. Part 1 gives some background on analytical query systems and my goals for LocustDB. Part 2 presents benchmark results produced on a data set of 1.46 billion taxi rides and demonstrates median speedups of 3.6x over ClickHouse and 2.1x over tuned kdb+. Part 3 is an architecture deep dive that follows two SQL statements through the guts of the query engine. Part 4 concludes with random learnings, thoughts on Rust, and other incoherent ramblings. Continue reading
New roadmap after finishing multiplayer
I now have a working implementation for a multiplayer server that allows for running a game across separate machines that can run both the JavaScript and the JVM version (link to demo). It’s too slow to be really usable yet, but all the core algorithms are in place. Multiplayer was the last difficult technical problems that I wanted to tackle, so from now on I intend to focus mostly on improving existing features and getting the word out about CodeCraft. For this post, I have compiled an overview of what I want to do on the technical side of things over the next few weeks. If you have any feedback or suggestions, let me know in the comments or on twitter. Continue reading
Multiplayer
Ever since I began working on CodeCraft, I wanted to implement a multiplayer mode which would allow players anywhere in the world to pit their AIs against each other. With most other parts of CodeCraft taking shape, I now spent some time working on that aspect of the game. In this post I want to talk about some of the design challenges and outline my plans for multiplayer. Continue reading
@CodeCraftGame
CodeCraft now has a twitter account which I will use for frequent updates about new features. I think Twitter is a nice fit for this, and I should also be able to integrate the feed into the website which is neat. I will still use this blog whenever I have more substantial content.
codecraftgame.org has launched!
Took me long enough, but I finally launched www.codecraftgame.org. The website is still under construction, but I do have the first two missions of the interactive Javascript tutorial ready. Now that the foundations are laid I expect to push an update every few days to add additional content and polish.
CodeCraft.js demo
There is now a working Javascript/WebGL version of CodeCraft, go check it out: http://cswinter.github.io/codecraftjs-demo/
Getting this to work was surprisingly easy, mad props to everyone behind Scala.js for creating such an awesome piece of technology.
I will now be adding a Javascript API and an in-browser editor and command line and use that to create an interactive tutorial. So there is still some work to be done, but I expect to have most of this up and running by early August.