Search Results for "cloud computing in the matlab"
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Showing 15 open source projects for "cloud computing in the matlab"
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KubeEdge
Kubernetes Native Edge Computing Framework (project under CNCF)
KubeEdge is built upon Kubernetes and extends native containerized application orchestration and device management to hosts at the Edge. It consists of a cloud part and an edge part, and provides core infrastructure support for networking, application deployment, and metadata synchronization between the cloud and edge. It also supports MQTT which enables edge devices to access through edge nodes. With KubeEdge it is easy to get and deploy existing complicated machine learning, image... -
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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. ... -
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Bacalhau
Community-driven, simple, yet powerful framework
Bacalhau is a decentralized compute platform for running jobs on data stored across distributed networks, like IPFS or Filecoin, without moving the data to centralized cloud environments. It allows developers to run containerized workloads close to where the data lives, reducing latency, cost, and privacy risks. Bacalhau supports various runtime environments and is designed to make decentralized data processing as accessible as traditional cloud computing. It’s especially useful for large-scale AI/ML jobs, scientific research, and content indexing in Web3 ecosystems. -
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tsuru
Open source and extensible Platform as a Service (PaaS)
...Let your developers code and understand the business instead of solving infrastructure problems or handling large configuration files. We built the platform as a service atop of battle-tested technologies from Cloud Native Computing Foundation stack. Manage your distributed apps in many kubernetes clusters/regions with a single point of control. Tsuru is an open source project and, as such, we welcome contributions. Feel free to report or fix bugs, contribute to the documentation, or just give your opinion about the software. -
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FATE
An industrial grade federated learning framework
...Supporting various federated learning scenarios, FATE now provides a host of federated learning algorithms, including logistic regression, tree-based algorithms, deep learning and transfer learning. FATE became open-source in February 2019. FATE TSC was established to lead FATE open-source community, with members from major domestic cloud computing and financial service enterprises. FedAI is a community that helps businesses and organizations build AI models effectively and collaboratively, by using data in accordance with user privacy protection, data security, data confidentiality and government regulations. -
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Empact Foundation Class Library
Cross-platform C++ library for use as a default application framework.
...Features include: * Threading & synchronization * Socket programming: SSL, NanoMsg & ZMQ * File I/O utilities: zlib, ini, yaml * Native Database access: MySQL, SQLite, BerkleyDB, Postgre, REDIS and ODBC * Built-in mini XML parser; optional EXPAT, LIBXML and MSXML support * Network protocol stack: HTTP, FTP, SMTP, POP3, SOAP, XMLRPC * Scripting languages: Perl, Python, JavaScript, VBScript, Java, Lua, TCL, Squirrel * Cloud Computing: AWS * Encryption: OpenSSL * Platforms: Linux/Posix, Windows, Arduino * Over 500+ highly reusable classes. 4000+ fully documented functions. Follow the 'Wiki' link above to explore everything about the framework. -
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Erda
An enterprise-grade Cloud-Native application platform for Kubernetes
Erda is an open-source platform created by Terminus to ensure the development of microservice applications. It provides DevOps, microservice governance, and multi-cloud management capabilities. The multi-cloud architecture based on Kubernetes and application-centric DevOps and microservice governance can make the development, operation, monitoring, and problem diagnosis of complex business applications simpler and more efficient. erda is the core repository that implements all the RESTful... -
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Apache MXNet (incubating)
A flexible and efficient library for deep learning
Apache MXNet is an open source deep learning framework designed for efficient and flexible research prototyping and production. It contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations. On top of this is a graph optimization layer, overall making MXNet highly efficient yet still portable, lightweight and scalable. -
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CloudTest-Cloud java unit test framework
A redefined framework with new approach and methodology for unit test
CloudTest is a redefined unit testing approach and methodology, which can make your testing jobs become much more easy and efficient. It is a pure java lightweight framework integrated test cases management, test data management, assert management, automation regression, performance monitor and test report in one. -
Create and run cloud-based virtual machines.Computing infrastructure in predefined or custom machine sizes to accelerate your cloud transformation. General purpose (E2, N1, N2, N2D) machines provide a good balance of price and performance. Compute optimized (C2) machines offer high-end vCPU performance for compute-intensive workloads. Memory optimized (M2) machines offer the highest memory and are great for in-memory databases. Accelerator optimized (A2) machines are based on the A100 GPU, for very demanding applications.
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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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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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A scheduling and resource management system for using a farm of servers running VMware virtualisation products as a computing cloud. Currently, only the VMware VIM 1.4 proxy is considered 'working'. Out of active development for the moment.
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OSlash is a c++ framework for developing decentralized cloud computing services. It includes a programming environment and virtual machine for assembling networks of processing nodes coordinate their operations through message passing.
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An open-source configurable virtual testbed (based on the Eucalyptus cloud platform) for Intrusion Detection System Evaluation.
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