rexsimulator
awesome-machine-learning-in-compilers
| rexsimulator | awesome-machine-learning-in-compilers | |
|---|---|---|
| 1 | 5 | |
| 5 | 1,331 | |
| - | - | |
| 1.8 | 5.7 | |
| over 3 years ago | 17 days ago | |
| C# | ||
| - | Creative Commons Zero v1.0 Universal |
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rexsimulator
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I spent 5 years writing my own operating system
The simulator https://github.com/halfer53/rexsimulator
The BIOS has already been written for the serial ports, etc. So it is quite easy for me to interact with the devices in the OS.
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...
What are some alternatives?
ZenithOS - The Zenith Operating System is a modernized, professional fork of the 64-bit Temple Operating System.
kernel-ml - Machine Learning Framework for Operating Systems - Brings ML to Linux kernel
winix - A UNIX-style Operating System for the Waikato RISC Architecture Microprocessor (WRAMP)
wcc - WRAMP C Compiler
unikraft - A next-generation cloud native kernel designed to unlock best-in-class performance, security primitives and efficiency savings.
awesome-tensor-compilers - A list of awesome compiler projects and papers for tensor computation and deep learning.
awesome-machine-learning-in-compil
Parallel-Computing-Guide - Parallel Computing Guide
heinsen_sequence - Code implementing "Efficient Parallelization of a Ubiquitious Sequential Computation" (Heinsen, 2023)