Search Results for "cluster computing"
Sort By:
30 projects for "cluster computing" with 1 filter applied:
-
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
-
1
Apache Sedona
Cluster computing framework for processing large-scale geospatial data
Apache Sedona™ is a cluster computing system for processing large-scale spatial data. Sedona extends existing cluster computing systems, such as Apache Spark and Apache Flink, with a set of out-of-the-box distributed Spatial Datasets and Spatial SQL that efficiently load, process, and analyze large-scale spatial data across machines. According to our benchmark and third-party research papers, Sedona runs 2X - 10X faster than other Spark-based geospatial data systems on computation-intensive query workloads. ... -
2
Kubeflow Trainer
Distributed AI Model Training and LLM Fine-Tuning on Kubernetes
...The platform supports a wide range of machine learning frameworks, including PyTorch, JAX, Hugging Face, DeepSpeed, and XGBoost, making it highly flexible for different AI use cases. One of its key innovations is the integration of MPI-based distributed computing within Kubernetes, allowing efficient communication between nodes for high-performance training. It also includes advanced scheduling capabilities through integrations with tools like Kueue and Volcano, enabling topology-aware resource allocation and multi-cluster job orchestration. -
3
Apache Seata
High-performance, open source distributed transaction solution
Seata is a distributed transaction solution for microservices that provides consistent, cross-service commits without forcing every team to adopt the same persistence model. Its architecture separates responsibilities into a global coordinator and per-service participants, so business services remain decoupled while transactions are orchestrated centrally. Multiple modes are supported—AT (automatic, SQL-based with undo logs), TCC (try-confirm-cancel), Saga (long-running compensation), and... -
4
Matrix
Multi-Agent daTa geneRation Infra and eXperimentation framework
Matrix is a distributed, large-scale engine for multi-agent synthetic data generation and experiments: it provides the infrastructure to run thousands of “agentic” workflows concurrently (e.g. multiple LLMs interacting, reasoning, generating content, data-processing pipelines) by leveraging distributed computing (like Ray + cluster management). The idea is to treat data generation as a “data-to-data” transformation: each input item defines a task, and the runtime orchestrates asynchronous, peer-to-peer agent workflows, avoiding global synchronization bottlenecks. That design makes Matrix particularly well-suited for large-batch inference, model benchmarking, data curation, augmentation, or generation — whether for language, code, dialogue, or multimodal tasks. ... -
Try Google Cloud Risk-Free With $300 in CreditUse your credit across every product. Compute, storage, AI, analytics. When it runs out, 20+ products stay free. You only pay when you choose to.
-
5
Mars Framework
Mars is a tensor-based unified framework for large-scale data
Mars is a distributed computing framework designed to scale scientific computing and data science workloads across large clusters while preserving the familiar programming interfaces of common Python libraries. The project provides a tensor-based execution model that extends the capabilities of tools such as NumPy, pandas, and scikit-learn so that large datasets can be processed in parallel without rewriting code for distributed environments. -
6
dispy
Distributed and Parallel Computing 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. -
7
Python/xarray tutorial
Python/xarray tutorial for GEOS-Chem users
If the page is loaded successfully, you should see a Jupyter notebook interface. Then, click on the first notebook to get started. Jupyter combines Python code, execution results, plots, custom texts, and even Latex formulas in a single page. Besides using the Jupyter program, you can also view the static notebook on GitHub (e.g the first notebook). Python is free & open-source so can be easily installed on any machines. To best way to get the scientific Python environment is using the Conda... -
8
A framework to run MATLAB programs as batch jobs. Features a structured input description, integrity constraints and GUI.Independent parts of a job can execute in parallel on a cluster computer. Developed at Freiburg Brain Imaging (FBI) - http://fbi.uniklinik-freiburg.de/
-
9
DMTK
Microsoft Distributed Machine Learning Toolkit
The Microsoft Distributed Machine Learning Toolkit (DMTK) is an open-source framework created to support scalable machine learning across distributed computing environments. Developed by Microsoft Research, the toolkit provides infrastructure and algorithms designed to train large models efficiently on clusters of machines rather than a single system. At its core is a parameter-server architecture called Multiverso, which manages model parameters and synchronizes updates across distributed... -
AI-generated apps that pass security reviewRetool 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.
-
10
Moscrack is a perl application designed to facilitate cracking WPA keys on a cluster of computers. This is accomplished with any one of Mosix clustering software, ssh, rsh or Pyrit connectivity to nodes. Cluster nodes can run any Un*x variant (includ
-
11
Summingbird
Streaming MapReduce with Scalding and Storm
Summingbird is a streaming + batch hybrid computation framework developed by Twitter. Its aim is to let developers express data aggregation pipelines in a unified way, where the same logic can run either in real time (stream) or in batch mode, and the results can be merged or reconciled. In effect, Summingbird abstracts over multiple execution engines (such as Storm, Scalding, etc.) to provide one high-level program that composes transformations and aggregations, and then executes them in... -
12
OpenSearchServer Store
A file server with a RESTFul web service.
An open source (Apache 2 license) file server software with a RESTFul web service for file management in a cluster of nodes. Including 4 set of API - Store API: Upload, download files and directories - Process API: Managing the long term process runs - Glacier API: Uploading from the server to Glacier - Cluster API: Manage the nodes in the cluster -
13
PBS Cluster Viz is a project to display information useful to admins and users about a computing cluster managed by a PBS-compatible resource manager. Information includes load and job distribution. Interactive as well as static output is available.
-
14
Equalizer is the standard middleware to create parallel OpenGL-based applications. Please visit https://github.com/Eyescale for current development information.
-
15
Scarlet is an extension for Atlassian JIRA, the leading Enterprise issue tracking and management software, allowing easy clustering of JIRA application instances, ensuring both high availability and linear scalability.
-
16
This modular software package forms an integration point for Grid/Cloud/Cluster products. If provides several adapters which can easily be used to build complete Services/integrate products. It enables federation between multiple sites.
-
17
Shared Questionnaire System(SQS) is a full-functional Optical Mark Reader(OMR) form processing system implemented in Java-Swing, XSL-FO and AJAX with straightforward GUIs. It is aimed at developing social platform to share knowledge about questionnaire.
-
18
A light weigth high performance cluster server to link several Java machines into one logical unit. Medusa does not compete with J2EE servers but allows clustering of standard Java code for fail-over, redundancy and processing power.
-
19
POV-Ray Animations for everyone from everyone. Use the power of many Computer connected to the Internet to raytrace long or complex Animations with the freeware Raytracer POVRay (http:/www.povray.org/). Each Client gets a "work unit" from the Server an
-
20
Cluster Networks are a new style of neural simulation / neural network modeling, that models networks of neural populations ("clusters") that transform and transmit information using precisely-timed, graded bursts ("pulses" or "volleys") of firing.
-
21
A small client/server/node application written in java for distributed computing, or clustering. you write your programs to use this system, you create an object with a meathod to run and send it to the server that assign it a node.
-
22
JCuckoo is the project aimed at creating a simple and universal platform for distributed computing and object migration in Java. JCuckoo will enable creating both small-scale (cluster-like) networks and wide-area (even worldwide) computing.
-
23
sharq is a batch-queueing system that allows for multiple users to make effective use of a beowulf cluster. sharq allows for prioritization based on a user's funding, and also based on the size of the job. sharq is very light-weight and easy to learn.
-
24
The software provides a means to form a simple Java cluster. It can be also viewed as a parallel computing library in Java. The project is based on the following <a href='http://www-106.ibm.com/developerworks/java/library/j-super.html'>article</a>
-
25
Generic clustering/load-balancing platform (over a LAN or internet) using java based P2P Aorta workers that execute java "tasklets". Various tasklets can be implemented to solve fractals, process images, render webpages, crack RSA "brute force".
