Search Results for "computing" - Page 3
Sort By:
Showing 588 open source projects for "computing"
View related business solutions-
Stop Cyber Threats with VM-Series Next-Gen Firewall on AzureGain integrated visibility across all traffic in a single pass. Deploy Palo Alto Networks VM-Series to determine application identity and content while automating security policy updates via rich APIs.
-
Stop vibe-debugging.AppSignal's MCP server hands Claude, Cursor, or Zed your real errors, traces, and the deploy that shipped them. AI writes the fix; you review the diff.
-
1
MirageOS
MirageOS is a library operating system that constructs unikernels
A programming framework for building type-safe, modular systems. MirageOS is a library operating system that constructs unikernels for secure, high-performance network applications across a variety of cloud computing and mobile platforms. Code can be developed on a normal OS such as Linux or macOS, and then compiled into a fully standalone, specialized unikernel that runs under a Xen or KVM hypervisor. This lets your services run more efficiently, securely and with finer control than with a full conventional software stack. -
2
SymbolicUtils.jl
Symbolic expressions, rewriting and simplification
SymbolicUtils is a practical symbolic programming utility in Julia. It lets you create, rewrite and simplify symbolic expressions, and generate Julia code from them. SymbolicUtils.jl provides various utilities for symbolic computing. SymbolicUtils.jl is what one would use to build a Computer Algebra System (CAS). If you're looking for a complete CAS, similar to SymPy or Mathematica, see Symbolics.jl. If you want to build a crazy CAS for your weird Octonian algebras, you've come to the right place. Symbols in SymbolicUtils carry type information. Operations on them propagate this information. ... -
3
TimerOutputs.jl
Formatted output of timed sections in Julia
TimerOutputs.jl is a lightweight Julia package that provides a structured way to measure and report the execution time of different parts of code. It is particularly useful for performance profiling in scientific computing, allowing developers to annotate sections of code and generate readable timing summaries. TimerOutputs.jl supports nested timers and formatted output to both terminal and files, helping users easily identify bottlenecks in their programs. -
4
RuleGo
Component orchestration rule engine framework for Go
...It’s lightweight, embeddable, orchestration-ready, and built for flexible composition of business logic into reusable components. No external middleware dependencies, efficient data processing and linkage on low-cost devices, suitable for IoT edge computing. Embedded and Standalone Deployment modes. Supports embedding RuleGo into existing applications. It can also be deployed independently as middleware, providing rule engine and orchestration services. -
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.
-
5
Tau
Open source distributed Platform as a Service (PaaS)
tau is the core runtime and orchestration engine of the Taubyte platform, an event-driven, distributed computing framework for building and running decentralized applications. tau handles the dynamic deployment of code, services, and data across edge and cloud environments based on real-time events. It abstracts infrastructure and simplifies application delivery by combining GitOps principles with a secure, multi-tenant execution model. tau enables seamless scalability, event-based routing, and on-demand execution without managing underlying servers. -
6
Fury
A blazing fast multi-language serialization framework
...In serialization scenarios, Fury can achieve a 100x speed up compared to traditional serialization frameworks. If you use Java clusters on a large scale, this will save a lot of computing resources. -
7
Flower
Flower: A Friendly Federated Learning Framework
...Flower can be used with any machine learning framework, for example, PyTorch, TensorFlow, Hugging Face Transformers, PyTorch Lightning, scikit-learn, JAX, TFLite, MONAI, fastai, MLX, XGBoost, Pandas for federated analytics, or even raw NumPy for users who enjoy computing gradients by hand. -
8
RLax
Library of JAX-based building blocks for reinforcement learning agents
RLax (pronounced “relax”) is a JAX-based library developed by Google DeepMind that provides reusable mathematical building blocks for constructing reinforcement learning (RL) agents. Rather than implementing full algorithms, RLax focuses on the core functional operations that underpin RL methods—such as computing value functions, returns, policy gradients, and loss terms—allowing researchers to flexibly assemble their own agents. It supports both on-policy and off-policy learning, as well as value-based, policy-based, and model-based approaches. RLax is fully JIT-compilable with JAX, enabling high-performance execution across CPU, GPU, and TPU backends. ... -
9
mathjs
An extensive math library for JavaScript and Node.js
...One of its defining features is its expression parser, which allows users to evaluate and manipulate mathematical expressions written in a natural math-like syntax. mathjs is highly modular, enabling developers to include only the functionality they need for optimized application size and performance. The project is widely used in scientific computing, educational software, calculators, engineering tools, and data analysis applications. Its architecture combines accessibility for beginners. -
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
-
10
Bacalhau
Community-driven, simple, yet powerful framework
...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. -
11
Peroxide
Rust numeric library with high performance and friendly syntax
...This means that Peroxide can guarantee excellent performance for linear algebraic computations by leveraging the optimized routines provided by BLAS. For users familiar with numerical computing libraries like NumPy, MATLAB, or R, Rust's syntax might seem unfamiliar at first. This can make it more challenging to learn and use Rust libraries that heavily rely on Rust's unique features and syntax. -
12
Catlab.jl
A framework for applied category theory in the Julia language
Catlab.jl is a framework for applied and computational category theory, written in the Julia language. Catlab provides a programming library and interactive interface for applications of category theory to scientific and engineering fields. It emphasizes monoidal categories due to their wide applicability but can support any categorical structure that is formalizable as a generalized algebraic theory. First and foremost, Catlab provides data structures, algorithms, and serialization for... -
13
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. -
14
OpenQASM
Quantum assembly language for extended quantum circuits
OpenQASM is an imperative programming language designed for near-term quantum computing algorithms and applications. Quantum programs are described using the measurement-based quantum circuit model with support for classical feed-forward flow control based on measurement outcomes. OpenQASM presents a parameterized set of physical logic gates and concurrent real-time classical computations. Its main goal is to serve as an intermediate representation for higher-level compilers to communicate with quantum hardware. ... -
15
Kata Containers
Build a standard implementation of lightweight Virtual Machines (VMs)
Kata Containers is an open source container runtime, building lightweight virtual machines that seamlessly plug into the container ecosystem. Kata Containers is an open source community working to build a secure container runtime with lightweight virtual machines that feel and perform like containers, but provide stronger workload isolation using hardware virtualization technology as a second layer of defense. Since launching in December 2017, the community successfully merged the best parts... -
16
dlib
Toolkit for making machine learning and data analysis applications
Dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems. It is used in both industry and academia in a wide range of domains including robotics, embedded devices, mobile phones, and large high performance computing environments. Dlib's open source licensing allows you to use it in any application, free of charge. Good unit test coverage, the ratio of unit test lines of code to library lines of code is about 1 to 4. The library is tested regularly on MS Windows, Linux, and Mac OS X systems. No other packages are required to use the library, only APIs that are provided by an out of the box OS are needed. ... -
17
SIMD
C++ wrappers for SIMD intrinsics
SIMD is a C++ library that provides portable abstractions over SIMD (Single Instruction, Multiple Data) instructions, enabling developers to write high-performance vectorized code without dealing directly with architecture-specific intrinsics. SIMD instructions allow a single operation to be applied to multiple data elements simultaneously, significantly accelerating numerical and data-parallel computations. However, differences across CPU architectures and compilers make direct usage... -
18
JupyterLite
Wasm powered Jupyter running in the browser
JupyterLite is a browser-based distribution of the Jupyter ecosystem that enables interactive computing entirely within a web browser without requiring a backend server. Built using JupyterLab components and powered by WebAssembly technologies, it allows users to run Python and other language kernels directly in the browser through tools like Pyodide or Xeus. This architecture eliminates the need for installation or server infrastructure, making it highly accessible for education, demonstrations, and lightweight data science workflows. ... -
19
Google Highway
Performance-portable, length-agnostic SIMD with runtime dispatch
...This portability is achieved through dynamic or static dispatch mechanisms that select the best available instruction set at runtime or compile time. The library is designed for developers who need to maximize CPU performance in domains such as image processing, compression, cryptography, and scientific computing. -
20
AssemblyScript
A TypeScript-like language for WebAssembly
...AssemblyScript integrates with the WebAssembly ecosystem, enabling seamless interaction with JavaScript through standard APIs. It is widely used in scenarios where performance and portability are essential, such as gaming, data processing, and edge computing. -
21
CubeCL
Multi-platform high-performance compute language extension for Rust
CubeCL is a low-level compute language and compiler framework designed to simplify and optimize GPU programming for high-performance workloads, particularly in machine learning and numerical computing. It provides an abstraction layer that allows developers to write portable, hardware-efficient compute kernels without directly dealing with complex GPU APIs such as CUDA or OpenCL. CubeCL focuses on delivering predictable performance and composability by exposing explicit control over memory layouts, parallelism, and execution patterns while still maintaining a developer-friendly syntax. ... -
22
JAX Toolbox
Public CI, Docker images for popular JAX libraries
JAX Toolbox is a development toolkit designed to streamline and optimize the use of JAX for machine learning and high-performance computing on NVIDIA GPUs. It provides prebuilt Docker images, continuous integration pipelines, and optimized example implementations that help developers quickly set up and run JAX workloads without complex configuration. The project supports popular JAX-based frameworks and models, including architectures used for large-scale pretraining such as GPT and LLaMA variants. ... -
23
sebastian/diff
Diff implementation
diff is a standalone PHP library for computing and rendering textual differences, widely used to display “expected vs actual” output in testing tools. It supports line-based and character/word-granular comparisons so you can get both coarse and fine-grained views of changes. Output builders can produce formats like unified or context diffs, or more human-friendly renderings suitable for terminals and HTML reports. -
24
Behaviour Suite Reinforcement Learning
bsuite is a collection of carefully-designed experiments
...The framework supports automated logging and analysis, generating standardized output compatible with Jupyter notebooks for streamlined evaluation. It also integrates easily with existing RL libraries and can be used locally or via cloud computing platforms, including Google Cloud. -
25
OpenYurt
Extending your native Kubernetes to edge(project under CNCF)
OpenYurt is built based on upstream Kubernetes and is now hosted by the Cloud Native Computing Foundation(CNCF) as a Sandbox Level Project. OpenYurt has been designed to meet various DevOps requirements against typical edge infrastructures. It provides a consistent user experience for managing the edge applications as if they were running in the cloud infrastructure. It addresses specific challenges for cloud-edge orchestration in Kubernetes such as unreliable or disconnected cloud-edge networking, edge autonomy, edge device management, region-aware deployment, and so on. ...
