awesome-machine-learning-in-compilers
heinsen_sequence
awesome-machine-learning-in-compilers | heinsen_sequence | |
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5 | 1 | |
1,331 | 70 | |
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5.7 | 8.1 | |
18 days ago | 4 months ago | |
Creative Commons Zero v1.0 Universal | MIT License |
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awesome-machine-learning-in-compilers
- Awesome research papers on ML in Compilers
- Research Papers on ML in Compilers
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Compiler Optimizations Are Hard Because They Forget
This repo is a great collection of various papers & resources on the subject: https://github.com/zwang4/awesome-machine-learning-in-compilers
- Can artificial neural networks make better artificial neural networks than humans can make yet?
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I spent 5 years writing my own operating system
The list goes on.
Genode, unikernels like MirageOS, TempleOS, Singularity OS / Sing#, compiler services like Roslyn and Kotlin, MILEPOST GCC, Tensorflow / TPUs, GPT-3, all of the machine learning in compilers [1] and so much more. I truly think Deep Learning Compilers will be huge.
[1] https://github.com/zwang4/awesome-machine-learning-in-compil...
heinsen_sequence
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Minimal implementation of Mamba, the new LLM architecture, in 1 file of PyTorch
with only two calls to the PyTorch API. See the examples here:
https://github.com/glassroom/heinsen_sequence/blob/main/README.md
What are some alternatives?
kernel-ml - Machine Learning Framework for Operating Systems - Brings ML to Linux kernel
llm.f90 - LLM inference in Fortran
winix - A UNIX-style Operating System for the Waikato RISC Architecture Microprocessor (WRAMP)
ZenithOS - The Zenith Operating System is a modernized, professional fork of the 64-bit Temple Operating System.
rexsimulator - a forked copy of https://sourceforge.net/projects/rexsimulator/
awesome-tensor-compilers - A list of awesome compiler projects and papers for tensor computation and deep learning.
Parallel-Computing-Guide - Parallel Computing Guide
unikraft - A next-generation cloud native kernel designed to unlock best-in-class performance, security primitives and efficiency savings.