#计算机科学#A Flexible and Powerful Parameter Server for large-scale machine learning
#计算机科学#Lightweight and Scalable framework that combines mainstream algorithms of Click-Through-Rate prediction based computational DAG, philosophy of Parameter Server and Ring-AllReduce collective communicat...
#计算机科学#extremely distributed machine learning
#计算机科学#自己实现的深度学习训练框架，纯java实现，没有过多的第三方依赖，可分布式训练
OpenEmbedding is an open source framework for Tensorflow distributed training acceleration.
PetPS: Supporting Huge Embedding Models with Tiered Memory
A fully adaptive, zero-tuning parameter manager that enables efficient distributed machine learning training
#计算机科学#WIP. Veloce is a low-code Ray-based parallelization library that makes machine learning computation novel, efficient, and heterogeneous.
Reduce the training time of CNNs by leveraging the power of multiple GPUs in 2 approaches, Multi-workers & Parameter Sever Training using TensorFlow 2
Distributed Fieldaware Factorization Machines based on Parameter Server
python lib for sparse parameter server using rocksdb, written in c++
#计算机科学#Serving layer for large machine learning models on Apache Flink
Machine Learning models for large datasets
ROS utility package for build-time configuration file generation and dumping/restoring contents of ROS parameter server to/from ROS bags.
A lightweight community-aware heterogeneous parameter server paradigm.
