Search Results for "computing" - Page 5
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Showing 1576 open source projects for "computing"
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Data-Juicer
Data processing for and with foundation models
Data-Juicer is an open-source data processing and augmentation framework designed to enhance the quality and diversity of datasets for machine learning tasks. It includes a modular pipeline for scalable data transformation. -
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RunMat
The Fast, Free, Modern MATLAB / Octave code runtime
...Its website positions RunMat as a drop-in engine for current codebases, with an OSS development model inviting contributors to inspect the code or build from source. Overall, the goal is to give researchers, students, and engineers a fast, portable runtime for numerical computing workloads. -
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LAMMPS
Public development project of the LAMMPS MD software package
LAMMPS is a large-scale classical molecular dynamics simulator for modeling atoms, molecules, coarse-grained particles, and other particle-based systems. It is designed for high-performance computing and can run efficiently on desktops, clusters, and supercomputers. The software is widely used in materials science, chemistry, physics, nanotechnology, soft matter, and computational engineering. It supports many interaction models, including pair potentials, many-body potentials, reactive force fields, bonded interactions, long-range electrostatics, and user-extendable packages. ... -
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FLUX.2-klein-4B
Flux 2 image generation model pure C inference
FLUX.2-klein-4B is a compact, high-performance C library implementation of the Flux optimization algorithm — an iterative approach for solving large-scale optimization problems common in scientific computing, machine learning, and numerical simulation. Written with a strong emphasis on simplicity, correctness, and performance, it abstracts the core logic of flux-based optimization into a minimal C API that can be embedded in broader applications without pulling in heavy dependencies. Because the implementation is in plain C and focuses on data locality and vectorized operations, flux2.c can be integrated into performance-critical code paths where control over memory layout and execution behavior matters, such as GPU kernels, embedded systems, or custom ML runtime engines. -
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ROOT
Analyzing, storing and visualizing big data, scientifically
...It is reliable, performant and well supported, easy to use and obtain, and strives to maximize the quantity and impact of scientific results obtained per unit cost, both of human effort and computing resources. ROOT provides a very efficient storage system for data models, that demonstrated to scale at the Large Hadron Collider experiments: Exabytes of scientific data are written in columnar ROOT format. ROOT comes with histogramming capabilities in an arbitrary number of dimensions, curve fitting, statistical modeling, and minimization, to allow the easy setup of a data analysis system that can query and process the data interactively or in batch mode, as well as a general parallel processing framework, RDataFrame, that can considerably speed up an analysis. -
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Unikraft
A next-generation cloud native kernel designed to unlock performance
Unikraft powers the next generation of cloud-native, containerless applications by enabling you to radically customize and build custom OS/kernels; unlocking best-in-class performance, security primitives, and efficiency savings. Unikraft optimizes resource utilization, leading to smaller footprints (meaning higher server saturation) and improved efficiency in resource-constrained environments. Unikraft is an open-source project driven by a vibrant community of over 100 developers, fostering... -
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OSMO
The developer-first platform for scaling complex Physical AI workloads
OSMO is a developer-first orchestration platform designed to scale complex physical AI workflows across heterogeneous computing environments, including cloud GPUs, simulation clusters, and edge devices. It was originally built internally at NVIDIA to support robotics and embodied AI systems, where workflows span multiple stages such as data generation, training, simulation, and hardware testing. The platform addresses what NVIDIA refers to as the “three computer problem” by unifying these stages into a single pipeline defined through simple YAML configurations. ... -
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...Flyte enables rapid experimentation with production-grade software. Debug in the cloud by iterating on the workflows locally to achieve tighter feedback loops. As your data and ML workflows expand and demand more computing power, your workflow orchestration platform must keep up. If it’s not designed to scale, your platform will require constant monitoring and maintenance. Flyte was built with scalability in mind, ready to handle changing workloads and resource needs.
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kubeinvaders
Gamified Chaos Engineering Tool for Kubernetes
This project is part of the landscape of Cloud Native Computing Foundation in the Observability and Analysis - Chaos Engineering section. Backed by the teams at platform engineering.it and devopstribe.it, which provides enterprise-grade features and certified resilience services for your Kubernetes infrastructure. -
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Smile
Statistical machine intelligence and learning engine
Smile is a fast and comprehensive machine learning engine. With advanced data structures and algorithms, Smile delivers the state-of-art performance. Compared to this third-party benchmark, Smile outperforms R, Python, Spark, H2O, xgboost significantly. Smile is a couple of times faster than the closest competitor. The memory usage is also very efficient. If we can train advanced machine learning models on a PC, why buy a cluster? Write applications quickly in Java, Scala, or any JVM... -
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Smilei
Particle-in-cell code for plasma simulation
Smilei is an open-source electromagnetic Particle-In-Cell code for kinetic plasma simulation. It is designed for high-performance computing and can run on modern supercomputing architectures. The software is co-developed by physicists and computer scientists, which gives it both strong numerical physics capabilities and serious parallel-performance engineering. Smilei supports a wide range of plasma studies, including laser-plasma interaction, accelerator physics, space physics, and astrophysical plasmas. ... -
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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. -
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TinyGo
Go compiler for small place
...You can compile and run TinyGo programs on over 60 different microcontroller boards such as the BBC micro:bit and the Arduino Uno. TinyGo can also produce WebAssembly (WASM) code which is very compact in size. You can compile programs for web browsers, as well as for server and edge computing environments that support the WebAssembly System Interface (WASI) family of interfaces. TinyGo is a Go compiler intended for use in small places such as microcontrollers, WebAssembly (Wasm), and command-line tools. It reuses libraries used by the Go language tools alongside LLVM to provide an alternative way to compile programs written in the Go programming language. ... -
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LFortran
Official main repository for LFortran
LFortran is a modern open-source (BSD licensed) interactive Fortran compiler built on top of LLVM. It can execute the user’s code interactively to allow exploratory work (much like Python, MATLAB or Julia) as well as compile binaries with the goal of running the user’s code on modern architectures such as multi-core CPUs and GPUs. LFortran is in alpha (it is expected to not work on third-party codes and users enthusiastically participate in bug reporting and fixing). -
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sparklyr
R interface for Apache Spark
sparklyr is an R package that provides seamless interfacing with Apache Spark clusters—either local or remote—while letting users write code in familiar R paradigms. It supplies a dplyr-compatible backend, Spark machine learning pipelines, SQL integration, and I/O utilities to manipulate and analyze large datasets distributed across cluster environments. -
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StaticArrays.jl
Statically sized arrays for Julia
StaticArrays.jl is a Julia package that provides statically sized arrays with fast, stack-allocated memory storage and optimized performance for small array computations. It is particularly useful in numerical computing where small fixed-size matrices or vectors are used frequently, such as in robotics, physics simulations, or linear algebra. StaticArrays eliminate dynamic memory allocation overhead and enable compile-time optimizations for performance close to hand-written loops. -
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TensorZero
TensorZero is an open-source stack for industrial-grade LLM apps
tensorzero is a lightweight C++ library designed for tensor operations and numerical computing. It offers a minimal and readable implementation of core tensor functionality, making it ideal for educational purposes, lightweight applications, or those wanting to understand how tensor libraries work under the hood. With no external dependencies, tensorzero is easy to integrate into C++ projects needing basic multi-dimensional array support. -
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MathPHP
Powerful modern math library for PHP
...It covers a wide range of topics, including linear algebra, calculus, statistics, probability, and numerical analysis. Math PHP is designed for developers and data scientists who require precise and efficient mathematical computations in PHP, making it suitable for scientific computing and data processing. -
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rpm-ostree
Hybrid image/package system with atomic upgrades and package layering
...This approach enables atomic upgrades and rollbacks, ensuring system stability and consistency across deployments. rpm-ostree is particularly suited for scenarios where reliable and reproducible system states are critical, such as in containerized or edge computing environments. -
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Neboa
Type-safe NoSQL with Node & SQLite
Neboa is a lightweight, decentralized NoSQL database designed for distributed applications. It offers peer-to-peer synchronization and ensures data integrity across multiple nodes without relying on centralized servers, making it ideal for edge computing and offline-first applications. -
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GitHub Actions for DigitalOcean
GitHub Actions for DigitalOcean - doctl
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Pluto.jl
Simple reactive notebooks for Julia plutojl.org
We are on a mission to make scientific computing more accessible and fun. Writing a notebook is not just about writing the final document, Pluto empowers the experiments and discoveries that are essential to getting there. -
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py-multiaddr
multiaddr implementation in Python
py-multiaddr is a multiaddr implementation in Python. Every choice in computing has a tradeoff. This includes formats, algorithms, encodings, and so on. And even with a great deal of planning, decisions may lead to breaking changes down the road, or to solutions that are no longer optimal. Allowing systems to evolve and grow is important. The Multiformats Project is a collection of protocols that aim to future-proof systems, today. -
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libSQL
libSQL is a fork of SQLite that is both Open Source
...It aims to modernize SQLite by optimizing for performance and availability, targeting distributed and low-latency applications. SQLite has solidified its place in modern technology stacks, embedded in nearly any computing device you can think of. Its open source nature and public domain availability make it a popular choice for modification to meet specific use cases. libSQL will always be able to ingest and write the SQLite file format. We would love to add extensions like encryption, and CRC that require the file to be changed. But we commit to always doing so in a way that generates standard SQLite files if those features are not used. -
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LINKERD
Ultralight, security-first service mesh for Kubernetes
Enterprise power without enterprise complexity. Linkerd adds security, observability, and reliability to any Kubernetes cluster. 100% open source, CNCF graduated, and written in Rust. Instantly add latency-aware load balancing, request retries, timeouts, and blue-green deploys to keep your applications resilient. Incredibly small and blazing fast Linkerd2-proxy micro-proxy written in Rust for security and performance. Self-contained control plane, incrementally deployable data plane, and...
