awesome-machine-learning-in-compil VS awesome-machine-learning-in-compilers

Compare awesome-machine-learning-in-compil vs awesome-machine-learning-in-compilers and see what are their differences.

awesome-machine-learning-in-compil

By zwang4
Suggest topics

DISCONTINUED

Suggest alternative
Edit details

awesome-machine-learning-in-compilers

Must read research papers and links to tools and datasets that are related to using machine learning for compilers and systems optimisation (by zwang4)
Machine Learning Compiler Optimisation parallel-computing parallel-programming Parallelism parallelisation Artificial intelligence operating-systems auto-tuning multi-cores
Source Code
Suggest alternative
Edit details
InfluxDB
Our great sponsors
  • InfluxDB - Power Real-Time Data Analytics at Scale
  • WorkOS - The modern identity platform for B2B SaaS
  • SaaSHub - Software Alternatives and Reviews
Our great sponsors
awesome-machine-learning-in-compil awesome-machine-learning-in-compilers
1 5
- 1,327
- -
- 5.9
- 9 days ago
- Creative Commons Zero v1.0 Universal
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

awesome-machine-learning-in-compil

Posts with mentions or reviews of awesome-machine-learning-in-compil. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-06-26.
  • I spent 5 years writing my own operating system
    9 projects | news.ycombinator.com | 26 Jun 2021
    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...

awesome-machine-learning-in-compilers

Posts with mentions or reviews of awesome-machine-learning-in-compilers. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-06-21.

What are some alternatives?

When comparing awesome-machine-learning-in-compil and awesome-machine-learning-in-compilers you can also consider the following projects:

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

awesome-tensor-compilers - A list of awesome compiler projects and papers for tensor computation and deep learning.

rexsimulator - a forked copy of https://sourceforge.net/projects/rexsimulator/

unikraft - A next-generation cloud native kernel designed to unlock best-in-class performance, security primitives and efficiency savings.

Parallel-Computing-Guide - Parallel Computing Guide

heinsen_sequence - Code implementing "Efficient Parallelization of a Ubiquitious Sequential Computation" (Heinsen, 2023)

awesome-machine-learning-in-compil vs ZenithOS awesome-machine-learning-in-compilers vs kernel-ml awesome-machine-learning-in-compil vs winix awesome-machine-learning-in-compilers vs winix awesome-machine-learning-in-compil vs wcc awesome-machine-learning-in-compilers vs awesome-tensor-compilers awesome-machine-learning-in-compil vs rexsimulator awesome-machine-learning-in-compilers vs ZenithOS awesome-machine-learning-in-compilers vs rexsimulator awesome-machine-learning-in-compilers vs unikraft awesome-machine-learning-in-compilers vs Parallel-Computing-Guide awesome-machine-learning-in-compilers vs heinsen_sequence