This is a living document. Everything in this document is made in good faith of being accurate, but like I just said; we don't yet know everything about what's going on.
Update: I've disabled comments as of 2025-01-26 to avoid everyone having notifications for something a year on if someone wants to suggest a correction. Folks are free to email to suggest corrections still, of course.
A list of playable boot sector games, most of which are on github. Fun to play, great to learn from. There are also many cool non-booting boot sectors out there that aren't games (so more like demos), but this page is just reserved to interactive boot sectors / games. This list is also not complete, but not on purpose, it is a best effort collection of games, so if you know of any fun boot sector games, please contribute.
This page lists a collection of 31 games spanning several authors: nanochess, me, daniel-e, shikhin, JulianSlzr, XanClic, QiZD90, darkvoxels, guyhill, w-shackleton, egtzori, VileR, ish_works, franeklubi, queso_fuego, franeklubi, Jethro82, waternine9, tevoran, palma3k, taylor-hartman. peterferrie should also be mentioned as he has touched a lot of these games.
https://github.com/daniel-e/tetros
Tetris Clone. Full color, no score. This was one of the older boot sector games out there. 
In response to this brief blog entry, @antirez tweeted for some documentation on high-performance techniques for Redis. What I present here are general high-performance computing (HPC) techniques. The examples are oriented to Redis. but they work well for any program designed to be single- or worker-threaded and asynchronous (e.g. uses epoll).
The motivation for using these techniques is to maximize performance of our system and services. By isolating work, controlling memory, and other tuning, you can achieve significant reduction in latency and increase in throughput.
My perspective comes from the microcosm of my own bare-metal (vs VM), on-premises deployment. It might not be suitable for all scenarios, especially cloud deployments, as I have little experience with HPC there. After some discussion, maybe this can be adapted as [redis.io documentation](https://redis.io/do
A curated list of awesome Java frameworks, libraries and software.
| package main | |
| import ( | |
| "os" | |
| "os/signal" | |
| "runtime/pprof" | |
| "syscall" | |
| ) | |
| func main() { |
| # alias to edit commit messages without using rebase interactive | |
| # example: git reword commithash message | |
| reword = "!f() {\n GIT_SEQUENCE_EDITOR=\"sed -i 1s/^pick/reword/\" GIT_EDITOR=\"printf \\\"%s\\n\\\" \\\"$2\\\" >\" git rebase -i \"$1^\";\n git push -f;\n}; f" | |
| # git alias to tag and push a version | |
| tagpush = "!f(){ t=${1#v}; git tag v$t && git push origin v$t; }; f" | |
| # git alias to download single file from a repo in format of user/repo file | |
| fetch-file = "!f() { out=\"${4:-$(basename \"$2\")}\"; if gh api \"repos/$1/contents/$2\" ${3:+-f ref=$3} --jq '.content' 2>/dev/null | base64 --decode > \"$out\" 2>/dev/null; then echo \"Downloaded $2 → $out\"; else echo \"Failed\"; rm -f \"$out\"; fi; }; f" |
L1 cache reference ......................... 0.5 ns
Branch mispredict ............................ 5 ns
L2 cache reference ........................... 7 ns
Mutex lock/unlock ........................... 25 ns
Main memory reference ...................... 100 ns
Compress 1K bytes with Zippy ............. 3,000 ns = 3 µs
Send 2K bytes over 1 Gbps network ....... 20,000 ns = 20 µs
SSD random read ........................ 150,000 ns = 150 µs
Read 1 MB sequentially from memory ..... 250,000 ns = 250 µs
| #!/usr/bin/python | |
| ## gitsh (pronounced like "glitch"), an interactive wrapper for git. | |
| ## | |
| ## gitsh parses the output of "git status" and numbers the files for | |
| ## you, for easy operations on multiple files. | |
| ## | |
| ## $ gitsh status | |
| ## 1) M foo/bar.py | |
| ## 2) M foo/baz.py | |
| ## 3) A blah.sh |
As configured in my dotfiles.
start new:
tmux
start new with session name: