Search Results for "computing" - Page 7
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Showing 588 open source projects for "computing"
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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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Lucet
Lucet, the Sandboxing WebAssembly Compiler.
...Developed by the Bytecode Alliance, it focuses on ahead-of-time compilation, converting WebAssembly modules into native machine code before execution to achieve fast startup times and predictable performance. Lucet is particularly notable for its use in edge computing environments, where low latency and efficient resource usage are critical, such as in content delivery networks. It leverages the Cranelift code generator to produce optimized native binaries and provides a runtime that enforces strict sandboxing, ensuring that untrusted code cannot compromise the host system. The project is designed to embed easily into applications, allowing developers to extend systems with plugin-like architectures powered by WebAssembly. -
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The Community Scheduler Framework (CSF) is a set of Grid Services, implemented using the Globus Toolkit, which provides an environment for the development of metaschedulers that can dispatch jobs to resource managers such as LSF, SGE, PBS and Condor.
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s(ASP)
Implements the stable model semantics without grounding.
...Work on s(ASP) is supported by the National Science Foundation under Grant No. 1423419. Details of how s(ASP) works can be found in the following paper: Marple, Kyle, Elmer Salazar, and Gopal Gupta. "Computing Stable Models of Normal Logic Programs Without Grounding." arXiv preprint arXiv:1709.00501 (2017) (https://arxiv.org/abs/1709.00501). -
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PMCGPU
Parallel simulators for Membrane Computing on the GPU
Membrane Computing is a new research area (within Natural Computing) that aims to provide computing devices abstracted from the functioning and structure of living cells. These devices are called P systems. The objective of this project (PMCGPU) is to bring together all the researchers working on the development of parallel simulators for P systems, specially those using the GPU (e.g. -
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The Fission CL
Command-line interface for Fission
...Users want data ownership and privacy without compromising on a seamless experience. You want to build a resilient application that is fast, cost-effective, and efficient. We build local-first and edge computing tools that make all of this possible. Fission builds open source protocols and managed solutions that empower developers to construct humane software applications. -
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PRMLT
Matlab code of machine learning algorithms in book PRML
...Many tricks for speeding up Matlab code are applied (e.g. vectorization, matrix factorization, etc.). Usually, functions in this package are orders faster than Matlab builtin ones (e.g. kmeans). Many tricks for numerical stability are applied, such as computing probability in logrithm domain, square root matrix update to enforce matrix symmetry. -
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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. Ever wandered how your going to push an update to that smart fridge your company is working on as it's thousands of devices around the globe? wish you could have the assurance that your service will always use the latest code\envvars\etc in all of it's edge locations? want the ability to stop\start a globally distributed service with a single command? ... -
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X-DeepLearning
An industrial deep learning framework for high-dimension sparse data
...Storage and communication optimization, parameters are automatically allocated globally without manual intervention, and requests are merged to completely eliminate computing/storage/communication hotspots of ps. Complete streaming training features including feature admission, feature elimination, model incremental export, feature counting statistics, etc. Background: XDL1.0 focuses on throughput optimization and adopts the one request per thread processing model, which can significantly improve the limit throughput under ultra-high concurrency. -
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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... -
Error to trace to log to deploy. One click. No SSH.AppSignal links every error to the trace, the trace to the log, the log to the deploy that shipped it.
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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. Nebula imposes no limits on the scale of the cluster, each component in it is designed to scale out to allow millions of workers to be managed by it. Designed to connect to devices that are spread around the globe Nebula is tolerant of network connection issues and will resync the device when it reconnects. With a single API call you can deploy a new container version to managed devices around the globe in minutes. -
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Go + hardware
A directory of hardware related libs, tools, and tutorials for Go
...By organizing ecosystem resources in one place, it lowers the barrier to entry for hardware experimentation with Go. Overall, go-hardware functions as both a roadmap and reference point for developers bridging software and physical computing. -
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Probability Cheatsheet
A comprehensive 10-page probability cheatsheet
...The cheat sheet is intended as a quick reference for students, data scientists, statisticians, or anyone needing to recall core probability formulas without diving into textbooks. It may include visual diagrams (e.g. distributions’ shapes), tips or mnemonic notes, and examples of application (e.g. computing probabilities or expectations). Formats could include Markdown, PDF, or images for easy inclusion in study materials or slides. -
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rest-dev-vnc-docker
Restful / SOAP API Development with common tools in VNC/noVNC Docker
The idea is to use Docker with VNC/noVNC to aggregate all the needed and related Developments tools/IDEs within a single Docker as an agile way to stand up specific collections of tools quick within a Container quick computing needs. REST Development (this GIT) to cover end-to-end needs from JSON/XML, REST connection, Swagger, MongoDB, Test, etc. The use-cases of this kind of VNC/noVNC docker container is just limited by your imaginations and your device or network limitations. Virtually it's accessible ubiquitously from Your favorite smartphones, tablets, e.g., iPad, SurfacePro, Amazon Fire tablet, Chrome PC, Desktop PC, etc. ... -
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VRTK
An example of how to use the Tilia packages to create great content
VRTK is a collection of useful, reusable solutions to common problems found when building for virtual reality. VRTK aims to help productivity by speeding up the creation process from prototyping ideas to building complete solutions. The passion behind VRTK is to try and enable as many people as possible to build for VR, from seasoned developers to complete beginners who have a wonderful idea in their head but are unsure of how to create it. VRTK aims to be easy to understand so the absolute... -
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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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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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Teach Me Quantum
Practical Course on Quantum Information Science and Quantum Computing
A university-level course on Quantum Computing and Quantum Information Science that incorporates IBM Q Experience and Qiskit. This course is adequate for general audiences without prior knowledge on Quantum Mechanics and Quantum Computing (see prior knowledge), has an estimated average duration of 10 weeks at 3h/week (see duration), and is meant to be the entrypoint into the Quantum World. -
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BeakerX
Beaker Extensions for Jupyter Notebook
BeakerX is a collection of kernels and extensions to the Jupyter interactive computing environment. It provides JVM support, Spark cluster support, polyglot programming, interactive plots, tables, forms, publishing, and more. BeakerX supports Groovy, Scala, Clojure, Kotlin, Java, and SQL, including many magics. Widgets for time-series plotting, tables, forms, and more (there are Python and JavaScript APIs in addition to the JVM languages). -
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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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Functional, Data Science Intro To Python
[tutorial]A functional, Data Science focused introduction to Python
...The sections after that, involve varying levels of difficulty and cover topics as diverse as Machine Learning, Linear Optimization, build systems, command line tools, recommendation engines, Sentiment Analysis and Cloud Computing. -
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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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Avian Parallel Computing
Develop parallel programs. Try various thread configs. GUI front-end.
Avian Computing seeks to efficiently create parallel programs by changing how we think about parallel programs. Avian Computing discourages thinking about lines of code and encourages us to use a new model: flocks of birds. Changing the model to flocks of birds makes it easier to think about the actions that we want to perform concurrently, which leads to simpler and quicker development of working parallel programs. -
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Transcrypt
Python in the Browser
Lean and mean Python 3.6 to JavaScript compiler. Supports multiple inheritance, operator overloading and Python source level debugging, even of minified Javascript files. Transcrypt code is as fast and compact as its Javascript counterpart, and it is precompiled for page load speed. You can now develop your web applications completely in Python, with full access to any Javascript library. -
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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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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...
