Search Results for "programming"

... technology enables every application container, like a web server or a shell, to become a two phase commit application server. The client/server architecture of LIXA allows many application containers to share a single LIXA (state) server: this is ideal when horizontal scalability is a must and many identical application containers must refer to a single transactional environment. LIXA can be used with the C, C++, Java, Python and COBOL programming languages.

dispy is a generic and comprehensive, yet easy to use framework for creating and using compute clusters to execute computations in parallel across multiple processors in a single machine (SMP), among many machines in a cluster, grid or cloud. dispy is well suited for data parallel (SIMD) paradigm where a computation (Python function or standalone program) is evaluated with different (large) datasets independently. dispy supports public / private / hybrid cloud computing, fog / edge computing.

The purpose of the project is to develop a portable programming framework that facilitates distributed and multi-threaded programming for C++, Java, and Python. MADARA was originally developed as an agent-based middleware specifically for real-time, distributed artificial intelligence, but is now more general purpose for distributed timing, control, knowledge and reasoning, and quality-of-service. MADARA is composed of several tools and middleware, and the main entry point into the system...

asyncoro is a Python framework for developing concurrent, distributed, network programs with asynchronous completions and coroutines. Asynchronous completions implemented in asyncoro are sockets (non-blocking sockets), database cursors, sleep timers and locking primitives. Programs developed with asyncoro have same logic and structure as Python programs with threads, except for a few syntactic changes. asyncoro supports socket I/O notification mechanisms epoll, kqueue, /dev/poll (and poll...

Distributed Parallel Programming for Python! This package builds on traditional Python by enabling users to write distributed, parallel programs based on MPI message passing primitives. General python objects can be messaged between processors. Ru

Pydusa is a package for parallel programming using Python. It contains a module for doing MPI programming in Python. We have added parallel solver packages such as Parallel SuperLU for solving sparse linear systems.

Python Integrated Parallel Programming EnviRonment (PIPPER), Python pre-parser that is designed to manage a pipeline, written in Python. It enables automated parallelization of loops. Think of it like OpenMP for Python, but it works in a computer cluster

Design and development of visual programming interface to allow specification, loading, execution and termination of specified simulation runs. It should be capable of allowing secure remote control flow setup, execution / termination of simulation jobs

An implementation model for unifying Aspect Oriented Programming and Service Oriented Architecture.

MPY is an MPI implementation for Python using MPICH (or any other MPI implementation). MPY also provides helper functions for ease of programming, and a simple plug-in interface.

a distributed engine for abstract neural network development via natural-language programming