Search Results for "distributed computing" - Page 6
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Showing 1331 open source projects for "distributed computing"
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Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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Your monitoring isn't a stack. It's a pile. Fix that.Replace Datadog, New Relic, and Sentry without adding three more dashboards.
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Blazegraph (powered by bigdata)
Fast, scalable, robust graph database platform
Blazegraph has moved to Github. Please see https://github.com/blazegraph/database/. -
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DRBL provides diskless or systemless environment. It uses distributed hardware resources and makes it possible for clients to fully access local hardware. It also includes Clonezilla, a partition and disk cloning utility similar to Ghost.
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Nebula docs
Documentation repo of nebula orchestration system
Nebula is a open source distributed Docker orchestrator designed for massive scales (tens of thousands of servers/worker devices), unlike Mesos/Swarm/Kubernetes it has the ability to have workers distributed on high latency connections (such as the internet) yet have the pods(containers) be managed centrally with changes taking affect (almost) immediately, this makes Nebula ideal for managing a vast cluster of servers\devices across the globe, some example use cases are appliances\virtual appliances located at clients data centers, edge computing, and POS systems. ... -
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Nebula reporter
The optional reporter container which reads nebula reports from Kafka
Nebula is an open source-distributed Docker orchestrator designed for massive scales (tens of thousands of servers/worker devices), unlike Mesos/Swarm/Kubernetes it has the ability to have workers distributed on high latency connections (such as the internet) yet have the pods(containers) be managed centrally with changes taking effect (almost) immediately, this makes Nebula ideal for managing a vast cluster of servers\devices across the globe. Ever wandered how your going to push an update... -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Nebula worker
The worker node manager container which manages nebula nodes
Nebula is a open source distributed Docker orchestrator designed for massive scales (tens of thousands of servers/worker devices), unlike Mesos/Swarm/Kubernetes it has the ability to have workers distributed on high latency connections (such as the internet) yet have the pods(containers) be managed centrally with changes taking affect (almost) immediately, this makes Nebula ideal for managing a vast cluster of servers\devices across the globe, some example use cases are IoT devices, appliances\virtual appliances located at clients data centers, and edge computing. -
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slurm-roll
Slurm Resource Manager for Rocks Clusters
Slurm is a replacement for other resource management software and schedulers like gridengine or torque. The slurm roll integrates very well into a rocks clusters installation. In the folder addons, there are a lot of useful rolls for rocks clusters 6.1 and 6.2. These rolls do not depend on slurm. Please see Discussion for further information and support -
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dupost
Dual Porosity Stokes model implemented with FEniCS
...Douglas, X. Hu, B. Bai, X. He, M. Wei and J. Hou, "A Data Assimilation Enabled Model for Coupling Dual Porosity Flow with Free Flow," 2018 17th International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES), Wuxi, 2018, pp. 304-307. doi: 10.1109/DCABES.2018.00085 2. Hu X., Douglas C.C. (2019) An Implementation of a Coupled Dual-Porosity-Stokes Model with FEniCS. In: Rodrigues J. et al. (eds) Computational Science – ICCS 2019. ICCS 2019. Lecture Notes in Computer Science, vol 11539. ... -
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spark-ml-source-analysis
Spark ml algorithm principle analysis and specific source code
...Each section discusses both the mathematical principles behind the algorithms and how Spark implements them in a distributed computing environment. By studying these implementations, readers gain insight into how large-scale machine learning pipelines operate across distributed data systems. -
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Prometheus Spec
Censorship-resistant trustless state channels for machine learning
Censorship resistant decentralised computing is a new topic in distributed systems theory. With the recent rise in popularity of Bitcoin as a censorship-resistant financial and transactional system a new technological field of blockchain and its applications appeared. This work addresses the problem of computational integrity proofs (correctness of the actual computations) made by some non-trusted (anonymous) third party without repeating the whole volume of the actual computing. ... -
Build Securely on AWS with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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Wally
Distributed Stream Processing
...By eliminating infrastructure complexity, going from prototype to production has never been simpler. When we set out to build Wally, we had several high-level goals in mind. Create a dependable and resilient distributed computing framework. Take care of the complexities of distributed computing "plumbing," allowing developers to focus on their business logic. Provide high-performance & low-latency data processing. Be portable and deploy easily (i.e., run on-prem or any cloud). Manage in-memory state for the application. Allow applications to scale as needed, even when they are live and up-and-running. ... -
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data-science-ipython-notebooks
Data science Python notebooks: Deep learning
...Many notebooks introduce concepts step by step, then apply them to real datasets so readers can see techniques in action. Advanced sections touch on neural networks and distributed computing topics, helping you bridge from basics to production-adjacent workflows. The collection is suitable for self-paced study, quick reference, or as teaching materials in workshops. By combining narrative explanations with executable code, it shortens the path from theory to working prototypes. -
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JumboMem is a fully user-level piece of software that gives programs access to memory spread across multiple computers. When a program exceeds the memory in one computer, it automatically spills over into the memory of the next computer.
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MarDRe
MapReduce-based tool to remove duplicate DNA reads
...MarDRe is the Big Data counterpart of ParDRe (link above), which employs HPC technologies (i.e., hybrid MPI/multithreading) to reduce runtime on multicore systems. Instead, MarDRe takes advantage of the MapReduce programming model to significantly improve ParDRe performance on distributed systems, especially on cloud-based infrastructures. Written in pure Java to maximize cross-platform compatibility, MarDRe is built upon the open-source Apache Hadoop project, the most popular distributed computing framework for Big Data processing. -
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HSRA
Hadoop spliced read aligner for RNA-seq data
...This tool allows bioinformatics researchers to efficiently distribute their mapping tasks over the nodes of a cluster by combining a fast multithreaded spliced aligner (HISAT2) with Apache Hadoop, which is a distributed computing framework for scalable Big Data processing. HSRA currently supports single-end and paired-end read alignments from FASTQ/FASTA datasets. Moreover, our tool uses the Hadoop Sequence Parser (HSP) library (link above) to efficiently read the input datasets stored on the Hadoop Distributed File System (HDFS), being able to process datasets compressed with Gzip and BZip2 codecs. -
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The Grid Programming Environment (GPE) turns a collection of computer systems into a Grid and provides graphical user interfaces and interoperable GridBeans for application development. It supports Globus Toolkit and Unicore-based infrastructures.
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Jadex is a Belief Desire Intention (BDI) reasoning engine that allows for programming intelligent software agents in XML and Java. The resoning engine is very flexible.
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ATTENTION: For more info and latest version, refer to https://github.com/estigma88/jdhtuq. jDHTUQ is a peer-to-peer DHT system based in Chord algorithm, but built like API to generalize the implementation of peer-to-peer DHT systems. jDHTUQ have two fundamental services , put and get of resource.
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GPU, a Global Processing Unit
A framework for distributed computing
An extensible framework for distributed computing on P2P grids. We support peaceful free and open research and build an internet supercomputer. We render movies, solve Eternity puzzles, predict climate and improve a ~30 GHz cluster of clients. -
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SAFMQ: Store and Forward Message Queue, message oriented middleware. Uses include Assured Async Messaging, SOA, Delayed/Batch, and Cluster/Grid Computing. The SAFMQ server provides cross platform communication among C++, PHP, Java, and .NET clients.
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JPPF
The open source grid computing solution
JPPF makes it easy to parallelize computationally intensive tasks and execute them on a Grid. -
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Slimgrid is a Java library for grid computations which is lighter than other ones (JPPF, Hadoop, ...). The main design goals are: minimalism, simplicity, pervasiveness. If you need to grab something which does not require you to comprehend massive and complex API's, do exhaustive configurations and installations, is robust and reliable, uses just one port for all management and communication, then SlimGrid is the right choice. The SlimGrid is built on top of the Apache's ZooKeeper library...
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Madara
Middleware for distributed applications
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... -
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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/
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ChunJun
A data integration framework
ChunJun is a distributed integration framework, and currently is based on Apache Flink. It was initially known as FlinkX and renamed ChunJun on February 22, 2022. It can realize data synchronization and calculation between various heterogeneous data sources. ChunJun has been deployed and running stably in thousands of companies so far. Based on the real-time computing engine--Flink, and supports JSON template and SQL script configuration tasks. -
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darc
Durham Adaptive-optics Real-time Controller
darc, the Durham Adaptive optics Real-time Controller. For documentation or darctalk client only, select "View all files". For the latest bleeding-edge version, please use: git clone git://git.code.sf.net/p/darc2/code darc (no password required) (this changed May 2013 due to a sourceforge update). If you use darc, please cite with: Basden, A and Myers, R, MNRAS Vol 242, page 1483, 2012
