dmlc/dmlc-core

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C++
License
Apache License 2.0
Created about 9 years ago
Updated 2 months ago

dmlc/dmlc-core

dmlc

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A common bricks library for building scalable and portable distributed machine learning.

Distributed Machine Learning Common Codebase

DMLC-Core is the backbone library to support all DMLC projects, offers the bricks to build efficient and scalable distributed machine learning libraries.

Developer Channel

What's New

Note on Parameter Module for Machine Learning

Contents

Known Issues

RecordIO format is not portable across different processor endians. So it is not possible to save RecordIO file on a x86 machine and then load it on a SPARC machine, because x86 is little endian while SPARC is big endian.

Contributing

Contributing to dmlc-core is welcomed! dmlc-core follows google's C style guide. If you are interested in contributing, take a look at feature wishlist and open a new issue if you like to add something.

DMLC-Core uses C++11 standard. Ensure that your C++ compiler supports C++11.
Try to introduce minimum dependency when possible

CheckList before submit code

Type make lint and fix all the style problems.
Type make doc and fix all the warnings.

NOTE

deps:

libcurl4-openssl-dev

xgboost

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

dgl

Python package built to ease deep learning on graph, on top of existing DL frameworks.

gluon-cv

Gluon CV Toolkit

gluon-nlp

nnvm

decord

An efficient video loader for deep learning with smart shuffling that's super easy to digest

ps-lite

A lightweight parameter server interface

minpy

NumPy interface with mixed backend execution

mshadow

Matrix Shadow:Lightweight CPU/GPU Matrix and Tensor Template Library in C++/CUDA for (Deep) Machine Learning

cxxnet

move forward to https://github.com/dmlc/mxnet

dlpack

common in-memory tensor structure

treelite

Universal model exchange and serialization format for decision tree forests

minerva

Minerva: a fast and flexible tool for deep learning on multi-GPU. It provides ndarray programming interface, just like Numpy. Python bindings and C++ bindings are both available. The resulting code can be run on CPU or GPU. Multi-GPU support is very easy.

parameter_server

moved to https://github.com/dmlc/ps-lite

mxnet-notebooks

Notebooks for MXNet

Jupyter Notebook

rabit

Reliable Allreduce and Broadcast Interface for distributed machine learning

mxnet.js

MXNetJS: Javascript Package for Deep Learning in Browser (without server)

MXNet.jl

MXNet Julia Package - flexible and efficient deep learning in Julia

tensorboard

Standalone TensorBoard for visualizing in deep learning

wormhole

mxnet-memonger

Sublinear memory optimization for deep learning, reduce GPU memory cost to train deeper nets

difacto

Distributed Factorization Machines

XGBoost.jl

XGBoost Julia Package

mxnet-model-gallery

Pre-trained Models of DMLC Project

GNNLens2

Visualization tool for Graph Neural Networks

HalideIR

Symbolic Expression and Statement Module for new DSLs

mxnet-gtc-tutorial

MXNet Tutorial for NVidia GTC 2016.

Jupyter Notebook

experimental-lda

MXNet.cpp

C++ interface for mxnet

experimental-mf

cache-friendly multithread matrix factorization

web-data

The repo to host all the web data including images for documents in dmlc projects.

Jupyter Notebook

nnvm-fusion

Kernel Fusion and Runtime Compilation Based on NNVM

dmlc.github.io

cub

tl2cgen

TL2cgen (TreeLite 2 C GENerator) is a model compiler for decision tree models

mxnet-deepmark

Benchmark speed and other issues internally, before push to deep-mark

mxnet-examples

xgboost-bench

drat

Drat Repository for DMLC R packages

nn-examples

gluon-nlp-notebooks

docs-redirect-for-mxnet

redirect mxnet.readthedocs.io to mxnet.io