Top Python Frameworks & Libraries for distributed computing 41
FEDML - The unified and scalable ML library for large-scale distributed training, model serving, and federated learning. FEDML Launch, a cross-cloud scheduler, fur...
A unified interface for distributed computing. Fugue executes SQL, Python, Pandas, and Polars code on Spark, Dask and Ray without any rewrites....
A SDK/library for decentralized web and distributing computing projects
A multi-user, distributed computing environment for running DL model training experiments on Intel® Xeon® Scalable processor-based systems...
SQLflow based on python development, support to Spark, as the underlying distributed computing engine, through a set of unified configuration file to complete the...
Exelixi is a distributed framework based on Apache Mesos, mostly implemented in Python using gevent for high-performance concurrency. It is intended to run cluster...
Distributed Deep Learning-based Offloading for Mobile Edge Computing Networks
A Light-Weight Access Layer for Distributed Computing Infrastructure and Reference Implementation of the SAGA Python Language Bindings....
A Raspberry Pi powered, distributed (edge) computing camera setups that runs a Tensorflow object detection model to determine whether a person is on the camera. A...
Efficient and Scalable Physics-Informed Deep Learning and Scientific Machine Learning on top of Tensorflow for multi-worker distributed computing...
IPDC(InterPlanetary Distributed Computing) is the Distributed Computation service, A peer-to-peer hypermedia protocol to make the computation faster, open, and mor...
A python package of Cross-edge Computation Offloading (CCO) algorithm and its distributed version, Decor for Mobile Edge Computing (MEC)....
Kestrel is a job scheduler and dispatcher for distributed computing systems, particularly Virtual Organization Clusters, and uses XMPP for monitoring the state of...
SOFA: A Cross-framework Performance Profiler for Heterogeneous Computing Systems and Distributed Machine Learning Systems....
The Distributed Computing library for python implemented using PyCOMPSs programming model for HPC.
A Secure Multiparty Computation (MPC) protocol for computing linear regression on vertically distributed datasets....
Implementation of the Bittorrent and Mainline DHT protocol for Distributed Computing applications
A lightweight Python library for distributed computing on Sun Grid Engines
Tool to distribute a list of computational tasks over a pool of compute resources. The pool can grow or shrink....
Dockerized Distributed Computing prototype for Docker Global hackathon and DoraHacks
Stream processing system for scalable stream processing with Kafka, Spark, InfluxDB/Cassandra which enables distributed time series related MapReduce computing wit...
Task queue, Long lived workers for work based parallelization, with processes and Redis as back-end. For distributed computing....
2-stage pruning to favor distributed inference (local device compute half of the model, upload the feature for further computing on stronger devices or cloud)....
Intelligent and cost-effective bidding on cloud computing instances for bioinformatics pipelines.
Sky Computing: Accelerating Geo-distributed Computing in Federated Learning
A multi-user, distributed computing environment for running DL model training experiments on Intel® Xeon® Scalable processor-based systems...
A Modular Library for Off-Policy Reinforcement Learning with a focus on SafeRL and distributed computing...
What is Python? Executive Summary Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. Its high-level built in data s...
FRACTAL: framework for distributed computing to trace large accurate lineages
A library to compute histograms on distributed environments, on streaming data
FogBus2: A Lightweight and Distributed Container-based Framework for Integration of IoT-enabled Systems with Edge and Cloud Computing...
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads....