release winning entries of IOCCC28 under the year 2024
Congratulations to: * 2024/anders - Prize in sound coding - layered music generator * 2024/burton - Prize in pentagrammatology - wordle hard mode solver * 2024/cable1 - Prize in bot talk - LLM inference engine * 2024/cable2 - Prize in murky waters - salmon recipe * 2024/carlini - Prize in perfect timing - Intel 4004 emulation * 2024/codemeow - Prize in tray planting - bonsai generator * 2024/endoh1 - Prize in patient pointillism - slow ray tracer in CPP * 2024/endoh2 - Prize in solid body physics - rotating rigid body simulation * 2024/ferguson1 - Prize in diabolical logistics - Oregon trail pact with the devil * 2024/ferguson2 - Prize in yil-tas - Navajo code talker translator * 2024/howe - Nice accent eh-ward - mini vi * 2024/kramer - Prize in linguistic arithmetic - natural language numerical calculator * 2024/kurdyukov1 - Prize in phased periodicity - phase of the Moon * 2024/kurdyukov2 - Prize in art restoration - JPEG artifact removal * 2024/kurdyukov3 - Prize in virtual quietus - gaming VM and doom * 2024/kurdyukov4 - Prize in embiggening - encode without literals * 2024/maffiodo - Prize in creative interpretation - Jav\*script interpreter * 2024/mills - Prize in ℤ₃ - Infocom v3 story interpreter * 2024/stedolan - Best one liner - icon from MD5 * 2024/straadt - Prize in imitative rebooting - OpenRISC CPU and Linux * 2024/tmarrec - Prize in cyclonic coding - 3D tornado simulation * 2024/tompng - Prize in quasi bijection - vortex encryptor decryptor * 2024/weaver - Sur prize - rickroll Ran `make update` to perform the above. new file: 2024/burton/.entry.json
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## To build:
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``` <!---sh-->
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make all
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./get_model.sh
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```
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**NOTE**: You must accept the license to run the program.
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## To use:
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**NOTE**: You must have successful run the
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[2024/cable1/get_model.sh](%%REPO_URL%%/2024/cable1/get_model.sh) script
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before running the program.
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``` <!---sh-->
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./prog
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```
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## Try:
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``` <!---sh-->
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echo 'Describe yourself.' | ./prog
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echo 'Describe yourself.' | ./linux
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echo 'ls' | ./linux
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echo 'Describe yourself.' | ./eeyore
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echo 'Why are you so sad?' | ./eeyore
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echo 'Describe yourself.' | ./snoop
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echo 'Tell me a silly joke.' | ./snoop
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echo 'Describe yourself.' | ./rainman
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echo 'How 2+2 can equal 5?' | ./rainman
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```
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### Fun things to try
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Here are some fun things give as input:
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> Why did this entry win IOCCC28?
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> Translate "Plurima responsa non recta esse supponamus"
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> Write a C program that writes a C program.
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> Write a sentence so that contains a split infinitive.
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> Rewrite the previous sentence so that it ends in a preposition.
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> How much wood does a woodchuck?
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> Tell me a silly joke.
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> Write a poem about a poet who is illiterate.
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> Give examples, based on mathematics, where 2+2 can equal 5.
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Please note that the quality and accuracy of the answers you receive may vary. :-)
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We do **NOT** recommend believing everything you read from this program.
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**Caveat lector!**
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## Alternate code:
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### Alternate build:
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**NOTE**: You must have successful run the
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[2024/cable1/get_model.sh](%%REPO_URL%%/2024/cable1/get_model.sh) script
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before running the program.
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``` <!---sh-->
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make openmp
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```
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### Alternate use:
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``` <!---sh-->
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./prog_openmp
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```
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## Judges' remarks:
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This entry may benefit from OpenMP (via `prog_openmp`) for platforms that
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support compiling with OpenMP. Even on a cheap 8-core laptop, the produces
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tokens with a tolerable speed, at least for the first few lines.
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Without OpenMP, one must patiently await answers.
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To preserve this entry for posterity, one thing to explore is to find the
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minimal model which exhibits a sensible behavior: for example, printing
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"Hello, world!" as the response to any input.
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We took the liberty of making the program terminate gracefully at the end
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of input, at the cost of 2 extra bytes, and preserving the original in
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`prog.orig.c`.
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**NOTE**: Even with OpenMP, this tool is not the fastest. A mild level of patience is advised.
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**DISCLAIMER**: _riPlurima responsa non recta esse supponamus_!
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### IMPORTANT Download
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ChatIOCCC runs Meta's open source `llama2-7b-chat` model. Before using ChatIOCCC, you'll need to accept Meta's license
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and download the model weights (~7GB):
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``` <!---sh-->
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./get_model.sh
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```
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## Author's remarks:
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ChatIOCCC - the world's smallest and best LLM inference engine
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### About
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ChatIOCCC is the world's smallest LLM (large language model) inference engine - a "generative AI chatbot" in
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plain-speak. ChatIOCCC runs a modern open-source model (Meta's LLaMA 2 with 7 billion parameters) and has a
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good knowledge of the world, can understand and speak multiple languages, write code, and many other things. Aside from
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the model weights, it has no external dependencies and will run on any 64-bit platform with enough RAM.
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LLM inference engines are extremely complex, incorporating a tokenizer (SentencePiece or byte-pair encoding), embedding layer,
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transformer layers (including multi-head self-attention, feed-forward neural network, activation, layer norm and
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residual connections), key/value caching for performance, output projection, decoding, and a state machine to control
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the data flow. Implementing all of that machinery, with no external dependencies, generally takes thousands or tens of
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thousands of lines of code. ChatIOCCC is a full LLM implementation in under 1800 bytes of C, and even supports
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UTF-8/Unicode input and output and parallel processing over multiple CPU cores via OpenMP.
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The author was inspired by [llama2.c](https://github.com/karpathy/llama2.c) which aims to foster understanding of how LLMs work via a simple
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implementation. Unfortunately, even AI experts don't actually understand why LLMs work at all. This core truth led to
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an epiphany: as LLMs are already maximally incomprehensible, obfuscation cannot make them more so. So, in the spirit of
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the IOCCC we can set aside the futility of aiming for comprehensibility, and instead focus purely on size.
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Since smaller is always better, and ChatIOCCC is the world's smallest LLM inference engine, it is therefore also the
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world's best LLM inference engine.
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Whether or not you fail to disagree that this paragraph, and those above, are or are not in and of themselves maximally
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incomprehensible, they represent in either case the origin story of this IOCCC submission, which implements an LLM
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inference engine in an impossibly minimal quantity of maximally incomprehensible C code.
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### Requirements
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In addition to using `./get_model.sh` to download the `llama2-7b-chat` model (see above), you'll need around 11GB of free RAM to run ChatIOCCC.
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### Fun things to ask
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Here are some fun things you can ask ChatIOCCC to do for you:
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> Tell me a surprising fact about an animal of your choice.
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> Write a short story for a 5 year old girl, featuring Sobieski the dog and Pepe the cat.
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> Write a C program which sorts a list using the bubble sort algorithm.
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> Write a poem about a little boy who builds a rocket to fly to the moon. In Japanese, please.
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> Translate into English: 这个项目会成为 2024 年 IOCCC 的赢家吗？
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> Tell me about the IOCCC and its history. Then, write a poem in French about it.
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### Personalities
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ChatIOCCC allows the LLM's system prompt to be defined at compile time (by using `-DS="prompt..."`).
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The supplied `Makefile` includes three example personalities (set via system prompts) you can try: `eeyore`, `snoop` and `linux` (and
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their OpenMP versions, `eeyore_openmp`, `snoop_openmp`, `linux_openmp`).
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The `eeyore` and `snoop` personalities are self-explanatory. The `linux` personality makes ChatIOCCC act like a Linux
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machine. Try for example:
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``` <!---sh-->
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make linux
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./linux
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```
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Or for much better performance:
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``` <!---sh-->
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make linux_openmp
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./linux_openmp
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```
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Then try typing some Linux commands. You can even run an imaginary C compiler inside the LLM:
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``` <!---sh-->
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pwd
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cat /etc/passwd
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echo 'int main() { for (int i = 1; i <= 10; i++) printf("IOCCC %d\n", i); }' > test.c; gcc test.c; ./a.out
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ls -la a.out
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```
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### Limitations
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The `llama2-7b-chat` model has a context window of 4096 tokens (around 2000 words). As you use
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ChatIOCCC, the context window fills up from your prompts and from the model's responses,
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and the model gets progressively slower due to the attention mechanism needing to do more work. This is normal.
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When the context window is full, ChatIOCCC will clear it and at that point the model will
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'forget' prompts/responses from earlier in the session. Various more sophisticated techniques
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exist to handle context window overflow (summarization, rolling window, NTK-aware scaled RoPE etc.), the implementation
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of which is left to the reader with too much time on his/her hands.
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### Footnotes
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The length of this entry's source code is 1750 bytes. Many interesting things happened in 1750, including:
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- The Industrial Revolution begins in Great Britain
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- British astronomer Thomas Wright first proposes that the Milky Way is a disk-shaped system of stars, with our Solar System near its center
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- Benjamin Franklin first proposes the idea that lightning is electrical in nature
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- Adwaita the giant tortoise, who lived until 2006, is born
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- Johann Sebastian Bach dies
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As a final note, the author is pleased to report that this entry is [absolutely totally impossible](https://chatgpt.com/share/6839d275-c644-8004-9301-0ea781d8f5aa) according to ChatGPT. But, to quote Walt Disney, "it's kind of fun to do the impossible".
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<!--
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Copyright © 1984-2025 by Landon Curt Noll and Leonid A. Broukhis. All Rights Reserved.
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You are free to share and adapt this file under the terms of this license:
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Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
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For more information, see:
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https://creativecommons.org/licenses/by-sa/4.0/
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-->
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