A big endian Gentoo port developed on a Pine64.org RockPro64

Overview

Gentoo-aarch64_be

A big endian Gentoo port developed on a Pine64.org RockPro64

The endian wars are over... little endian won. As a result, it is increasingly difficult to find systems that allow you to test for endian cleanliness... I developed this port to facilitate testing of device drivers and general software on a big endian system. QEMU is another approach for big endian testing, however performance suffers greatly and many race conditions are harder to find. The RockPro64 platform is affordable and unlike other small ARM systems, it supports a PCIe slot for testing hardware add in cards! DISCLAIMER: I am not associated with Pine64 in any way other than as a satisfied customer.

This port has only been tested on the RockPro64 4GB board, however it likely will run on any ARM based system that can boot the Gentoo Arm64 installation CD image.

This repository will be populated over the next few weeks - there are several cleanup activities that I would like to complete before publishing.

Owner
Rory Bolt
Senior fellow at Kioxia America, Inc
Rory Bolt
Kaggle Lyft Motion Prediction for Autonomous Vehicles 4th place solution

Lyft Motion Prediction for Autonomous Vehicles Code for the 4th place solution of Lyft Motion Prediction for Autonomous Vehicles on Kaggle. Discussion

44 Jun 27, 2022
A series of Jupyter notebooks with Chinese comment that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

Hands-on-Machine-Learning 目的 这份笔记旨在帮助中文学习者以一种较快较系统的方式入门机器学习, 是在学习Hands-on Machine Learning with Scikit-Learn and TensorFlow这本书的 时候做的个人笔记: 此项目的可取之处 原书的

Baymax 1.5k Dec 21, 2022
State-of-the-art data augmentation search algorithms in PyTorch

MuarAugment Description MuarAugment is a package providing the easiest way to a state-of-the-art data augmentation pipeline. How to use You can instal

43 Dec 12, 2022
The full training script for Enformer (Tensorflow Sonnet) on TPU clusters

Enformer TPU training script (wip) The full training script for Enformer (Tensorflow Sonnet) on TPU clusters, in an effort to migrate the model to pyt

Phil Wang 10 Oct 19, 2022
Data and Code for paper Outlining and Filling: Hierarchical Query Graph Generation for Answering Complex Questions over Knowledge Graph is available for research purposes.

Data and Code for paper Outlining and Filling: Hierarchical Query Graph Generation for Answering Complex Questions over Knowledge Graph is available f

Yongrui Chen 5 Nov 10, 2022
Implementation of the paper: "SinGAN: Learning a Generative Model from a Single Natural Image"

SinGAN This is an unofficial implementation of SinGAN from someone who's been sitting right next to SinGAN's creator for almost five years. Please ref

35 Nov 10, 2022
Repo for parser tensorflow(.pb) and tflite(.tflite)

tfmodel_parser .pb file is the format of tensorflow model .tflite file is the format of tflite model, which usually used in mobile devices before star

1 Dec 23, 2021
Independent and minimal implementations of some reinforcement learning algorithms using PyTorch (including PPO, A3C, A2C, ...).

PyTorch RL Minimal Implementations There are implementations of some reinforcement learning algorithms, whose characteristics are as follow: Less pack

Gemini Light 4 Dec 31, 2022
[CoRL 21'] TANDEM: Tracking and Dense Mapping in Real-time using Deep Multi-view Stereo

TANDEM: Tracking and Dense Mapping in Real-time using Deep Multi-view Stereo Lukas Koestler1*    Nan Yang1,2*,†    Niclas Zeller2,3    Daniel Cremers1

TUM Computer Vision Group 744 Jan 04, 2023
A Python library for working with arbitrary-dimension hypercomplex numbers following the Cayley-Dickson construction of algebras.

Hypercomplex A Python library for working with quaternions, octonions, sedenions, and beyond following the Cayley-Dickson construction of hypercomplex

7 Nov 04, 2022
Edge-aware Guidance Fusion Network for RGB-Thermal Scene Parsing

EGFNet Edge-aware Guidance Fusion Network for RGB-Thermal Scene Parsing Dataset and Results Test maps: 百度网盘 提取码:zust Citation @ARTICLE{ author={Zhou,

ShaohuaDong 10 Dec 08, 2022
NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.

NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.

880 Jan 07, 2023
Definition of a business problem according to Wilson Lower Bound Score and Time Based Average Rating

Wilson Lower Bound Score, Time Based Rating Average In this study I tried to calculate the product rating and sorting reviews more accurately. I have

3 Sep 30, 2021
Ppq - A powerful offline neural network quantization tool with custimized IR

PPL Quantization Tool(PPL 量化工具) PPL Quantization Tool (PPQ) is a powerful offlin

605 Jan 03, 2023
Python implementation of O-OFDMNet, a deep learning-based optical OFDM system,

O-OFDMNet This includes Python implementation of O-OFDMNet, a deep learning-based optical OFDM system, which uses neural networks for signal processin

Thien Luong 4 Sep 09, 2022
Stereo Radiance Fields (SRF): Learning View Synthesis for Sparse Views of Novel Scenes

Stereo Radiance Fields (SRF): Learning View Synthesis for Sparse Views of Novel Scenes

111 Dec 29, 2022
Generative Models for Graph-Based Protein Design

Graph-Based Protein Design This repo contains code for Generative Models for Graph-Based Protein Design by John Ingraham, Vikas Garg, Regina Barzilay

John Ingraham 159 Dec 15, 2022
Baseline powergrid model for NY

Baseline-powergrid-model-for-NY Table of Contents About The Project Built With Usage License Contact Acknowledgements About The Project As the urgency

Anderson Energy Lab at Cornell 6 Nov 24, 2022
Pytorch implementation of Learning with Opponent-Learning Awareness

Pytorch implementation of Learning with Opponent-Learning Awareness using DiCE

Alexis David Jacq 82 Sep 15, 2022
Disease Informed Neural Networks (DINNs) — neural networks capable of learning how diseases spread, forecasting their progression, and finding their unique parameters (e.g. death rate).

DINN We introduce Disease Informed Neural Networks (DINNs) — neural networks capable of learning how diseases spread, forecasting their progression, a

19 Dec 10, 2022