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AI-generated apps that pass security review
Stop waiting on engineering. Build production-ready internal tools with AI—on your company data, in your cloud.
Retool lets you generate dashboards, admin panels, and workflows directly on your data. Type something like “Build me a revenue dashboard on my Stripe data” and get a working app with security, permissions, and compliance built in from day one. Whether on our cloud or self-hosted, create the internal software your team needs without compromising enterprise standards or control.
Distributed and ParallelComputing with/for Python.
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.
Aims to enable researcher to tap in to mobile computing capability
This is a software agent based computing program that will enable researchers and other users to tap in computing power of machine available by sharing work load on the fly with zero configuration on network & resources
A self organizing agent program that will understand network and its resource. where as the only job left to researcher is to split up jobs in several chunks of programs either parallel or sequential jobs and go issue the job (A visual Modeler or Scripting support need to be yet designed)
Software agents will automatically manage the rest or resource management, sharing , cloning of tasks etc.
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PuSSH is Pythonic, Ubiquitous SSH, a Python wrapper/script that runs commands in parallel on clusters/ranges of linux/unix machines via SSH, ideally where SSH is configured to use Kerberos, RSA/DSA keys, or ssh-agent as to avoid password authentication.
GXP is a parallel/distributed shell, plus a parallel task execution
engine that runs your Makefile in parallel on distributed machines.
Very easy to install (no need to compile. install it on YOUR machine
and use it on ALL machines).
Host and run your applications without the need to manage infrastructure. Scales up from and down to zero automatically.
Cloud Run is the fastest way to deploy containerized apps. Push your code in Go, Python, Node.js, Java, or any language and Cloud Run builds and deploys it automatically. Get fast autoscaling, pay only when your code runs, and skip the infrastructure headaches. Two million requests free per month. And new customers get $300 in free credit.
A utility to transport files and execute at remote in prarallel
Are you maitaining many machines and bored with the tedious operation of logging to those machines one by one just for checking the machine's status? Or are you losing patient for your simple script that have to run command in those machines in sequence?
The corunner is just for those senarios. It's designed to speed up execution in your machines. It can executes command in handreds of or thousands of machines concurrently. Provide it with your files and command and the machines' location,...
PyDSH is a remote administration tool, consisting of pydsh and pydcp. Pydsh allows you to run a command on multiple hosts in parallel over RSH, SSH or Telnet, OR manage your SSH public keys. The pydcp command allows copying files to/from multiple hosts.
Platform for parallel computation in the Amazon cloud, including machine learning ensembles written in R for computational biology and other areas of scientific research. Home to MR-Tandem, a hadoop-enabled fork of X!Tandem peptide search engine.
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
PyMW is a Python module for parallel master-worker computing in a variety of environments. With the PyMW module, users can write a single program that scales from multicore machines to global computing platforms.
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Start your next project with $300 in free Google Cloud credit. Spin up VMs, run containers, query exabytes in BigQuery, or build AI apps with Vertex AI and Gemini. Once your credits are used, keep building with 20+ products with free monthly usage, including Compute Engine, Cloud Storage, GKE, and Cloud Run functions. Sign up to start building right away.
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
Simple Distributed Job Management Tools facilitates parallel, distributed execution of simple commands, on a network of UNIX-like machines. Components include a job dependency/exclusivity language and load-balanced remote execution facility.
This tool lets you login with SSH to a group of machines and interact with them as if they were one machine. Each command that you enter is run in parallel on all machines in the group. The output from each machine is printed separately.
Maui Scheduler is an advanced reservation HPC parallel batch scheduler for use with Linux and BSD clusters. Maui provides a complete scientific scheduling solution, supporting running custom parallel and MPI jobs over Myrinet and ethernet.