Showing 537 open source projects for "compute"

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  • 1
    ngraph.path

    ngraph.path

    Path finding in a graph

    ngraph.path is a JavaScript library that implements efficient pathfinding algorithms for graphs, primarily designed to compute shortest paths in weighted or unweighted networks. It provides a clean API for constructing graph models, assigning weights to edges, and querying for optimal routes between nodes, making it useful for routing, games, maps, and network optimization. The library includes several algorithm implementations such as A*, Dijkstra’s, and breadth-first search, each suited to different types of graph structure and performance needs. ...
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  • 2
    DeployStack

    DeployStack

    Centralized credential vault, governance, and token optimization

    DeployStack is an open-source framework that helps developers and teams define and deploy production infrastructure stacks using modular, reusable templates, often with IaC (infrastructure as code) principles. It provides a structured way to compose resources such as cloud networking, compute, and managed services into coherent deployment blueprints that can be versioned and reused across projects. By abstracting common deployment patterns and capturing them as templates, Deploystack reduces duplication of effort that typically occurs when setting up stacks for different applications or environments. The project emphasizes repeatability and clarity, enabling teams to follow best practices for scalability, security, and operational reliability without hand-crafting deployment scripts for every new service. ...
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  • 3
    EC2Instances.info

    EC2Instances.info

    Amazon EC2 instance comparison site

    ec2instances is an open-source project that powers an intuitive, searchable comparison site for Amazon EC2 instance types, helping developers and cloud architects quickly evaluate compute options without the friction of navigating multiple AWS console screens. The site aggregates key metrics — including CPU, memory, storage, networking specs, and pricing — across many instance families, and lets users filter, sort, and visually compare configurations side by side. It was created to simplify decision-making for cloud provisioning, making it easier to choose the best instance type for performance and cost goals, and it’s maintained by the Vantage community to stay updated with current AWS offerings and user suggestions. ...
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  • 4
    sebastian/diff

    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. Internally, the library splits input into hunks and manages edge cases such as...
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  • 5
    EPLB

    EPLB

    Expert Parallelism Load Balancer

    ...The logic is implemented in eplb.py and supports predicting placements given estimated expert usage weights. EPLB aims to reduce hot-spotting and ensure more uniform usage of compute resources in large MoE deployments.
    Downloads: 0 This Week
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  • 6
    BertViz

    BertViz

    BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)

    ...The model view shows a bird's-eye view of attention across all layers and heads. The neuron view visualizes individual neurons in the query and key vectors and shows how they are used to compute attention.
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  • 7
    LinDB

    LinDB

    LinDB is a scalable, high performance, high availability database

    ...Horizontal scalable is made simple by adding more new broker and storage nodes without too much thinking and manual operations. And the tags-based sharding strategy resolves the hotspot problem. LinDB is designed to work under a Multi-Active IDCs cloud architecture. The compute layer of LinDB, called brokers, supports efficient Multi-IDCs aggregation query.
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  • 8
    NATS Go Client

    NATS Go Client

    Golang client for NATS, the cloud native messaging system

    ...With the ability to process millions of messages a second per server, you’ll find unparalleled efficiency with NATS. Save money by minimizing cloud costs with reduced compute and network usage for streams, services, and eventing. NATS self-heals and can scale up, down, or handle topology changes anytime with zero downtime to your system. Clients require zero awareness of NATS topology allowing you future proof your system to meet your needs of today and tomorrow.
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  • 9
    AWS SDK for Go v2

    AWS SDK for Go v2

    AWS SDK for the Go programming language

    Welcome to the AWS SDK for Go. The AWS SDK for Go V2 provides APIs and utilities that developers can use to build Go applications that use AWS services, such as Amazon Elastic Compute Cloud (Amazon EC2) and Amazon Simple Storage Service (Amazon S3). The SDK removes the complexity of coding directly against a web service interface. It hides a lot of the lower-level plumbing, such as authentication, request retries, and error handling. The SDK also includes helpful utilities. For example, the Amazon S3 download and upload manager can automatically break up large objects into multiple parts and transfer them in parallel. ...
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  • 10
    DCV Color Primitives

    DCV Color Primitives

    DCV Color Primitives Library

    ...You might want to propagate errors to the caller function or mix with some other error types. So far, buffers were sized taking into account the image pixel format and dimensions; However, you can use a function to compute how many bytes are needed to store an image of a given format and size. If your data is scattered in multiple buffers that are not necessarily contiguous, you can provide image planes. To take into account data which is not tightly packed, you can provide image strides.
    Downloads: 1 This Week
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  • 11
    oneDNN

    oneDNN

    oneAPI Deep Neural Network Library (oneDNN)

    This software was previously known as Intel(R) Math Kernel Library for Deep Neural Networks (Intel(R) MKL-DNN) and Deep Neural Network Library (DNNL). oneAPI Deep Neural Network Library (oneDNN) is an open-source cross-platform performance library of basic building blocks for deep learning applications. oneDNN is part of oneAPI. The library is optimized for Intel(R) Architecture Processors, Intel Processor Graphics and Xe Architecture graphics. oneDNN has experimental support for the...
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  • 12
    Alluxio

    Alluxio

    Open Source Data Orchestration for the Cloud

    ...It bridges the gap between computation frameworks and storage systems, bringing data from the storage tier closer to the data driven applications. This enables applications to connect to numerous storage systems through a common interface. It makes data local, more accessible and as elastic as compute.
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  • 13
    Meteroid

    Meteroid

    Open-source pricing and billing infrastructure

    Meteroid is an open-source, cloud-native pricing and billing infrastructure designed to support usage-based billing, subscription management, invoicing, and cost-tracking — particularly for SaaS or product-led businesses that need flexible billing models beyond flat subscriptions. It provides an API-driven billing engine: you feed Meteroid usage data from your application (e.g. API calls, storage usage, seats, feature usage), define custom pricing rules or plans, and Meteroid calculates...
    Downloads: 1 This Week
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  • 14
    VibeThinker

    VibeThinker

    Diversity-driven optimization and large-model reasoning ability

    VibeThinker is a compact but high-capability open-source language model released by WeiboAI (Sina AI Lab). It contains about 1.5 billion parameters, far smaller than many “frontier” models, yet it is explicitly optimized for reasoning, mathematics, and code generation tasks rather than general open-domain chat. The innovation lies in its training methodology: the team uses what they call the Spectrum-to-Signal Principle (SSP), where a first stage emphasizes diversity of reasoning paths (the...
    Downloads: 1 This Week
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  • 15
    cuDF

    cuDF

    GPU DataFrame Library

    ...The RAPIDS suite of open-source software libraries aims to enable the execution of end-to-end data science and analytics pipelines entirely on GPUs. It relies on NVIDIA® CUDA® primitives for low-level compute optimization but exposing that GPU parallelism and high-bandwidth memory speed through user-friendly Python interfaces.
    Downloads: 1 This Week
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  • 16
    LÖVR

    LÖVR

    Lua Virtual Reality engine

    An open-source framework for rapidly building immersive 3D experiences. You can use LÖVR to easily create VR experiences without much setup or programming experience. The framework is tiny, fast, open-source, and supports lots of different platforms and devices. Runs on Windows, Mac, Linux, Android, WebXR. Supports Vive/Index, Oculus Rift/Quest, Pico, Windows MR, and has a VR simulator. Simple VR scenes can be created in just a few lines of Lua. Writen in C99 and scripted with LuaJIT,...
    Downloads: 1 This Week
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  • 17
    qrcp

    qrcp

    Transfer files over wifi from your computer to your mobile device

    qrcp binds a web server to the address of your Wi-Fi network interface on a random port and creates a handler for it. The default handler serves the content and exits the program when the transfer is complete. When used to receive files, qrcp serves an upload page and handles the transfer. Most QR apps can detect URLs in decoded text and act accordingly (i.e. open the decoded URL with the default browser), so when the QR code is scanned the content will begin downloading by the mobile...
    Downloads: 1 This Week
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  • 18
    Colab-MCP

    Colab-MCP

    An MCP server for interacting with Google Colab

    ...Instead of relying on manual notebook usage, the system allows MCP-compatible agents to execute code, manage files, install dependencies, and orchestrate entire development workflows within Colab’s cloud infrastructure. This approach bridges the gap between local AI agents and remote high-performance compute environments, allowing users to offload heavy workloads such as machine learning training, data analysis, and dependency-heavy tasks to Colab’s GPU and TPU resources. By exposing Colab as an MCP server, the tool enables seamless integration with a wide range of AI assistants and agent frameworks, creating a standardized interface for tool use and execution.
    Downloads: 0 This Week
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  • 19
    Ploomber

    Ploomber

    The fastest way to build data pipelines

    Ploomber is an open-source framework designed to simplify the development and deployment of data science and machine learning pipelines. It allows developers to transform exploratory data analysis workflows into production-ready pipelines without rewriting large portions of code. The system integrates with common development environments such as Jupyter Notebook, VS Code, and PyCharm, enabling data scientists to continue working with familiar tools while building scalable workflows. Ploomber...
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  • 20
    Ling-V2

    Ling-V2

    Ling-V2 is a MoE LLM provided and open-sourced by InclusionAI

    Ling-V2 is an open-source family of Mixture-of-Experts (MoE) large language models developed by the InclusionAI research organization with the goal of combining state-of-the-art performance, efficiency, and openness for next-generation AI applications. It introduces highly sparse architectures where only a fraction of the model’s parameters are activated per input token, enabling models like Ling-mini-2.0 to achieve reasoning and instruction-following capabilities on par with much larger...
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  • 21
    LLMs-from-scratch

    LLMs-from-scratch

    Implement a ChatGPT-like LLM in PyTorch from scratch, step by step

    LLMs-from-scratch is an educational codebase that walks through implementing modern large-language-model components step by step. It emphasizes building blocks—tokenization, embeddings, attention, feed-forward layers, normalization, and training loops—so learners understand not just how to use a model but how it works internally. The repository favors clear Python and NumPy or PyTorch implementations that can be run and modified without heavyweight frameworks obscuring the logic. Chapters...
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  • 22
    Granite 3.0 Language Models

    Granite 3.0 Language Models

    New set of lightweight state-of-the-art, open foundation models

    This repository introduces Granite 3.0 language models as lightweight, state-of-the-art open foundation models built to natively support multilinguality, coding, reasoning, and tool usage. A central goal is efficient deployment, including the potential to run on constrained compute resources while remaining useful for a broad span of enterprise tasks. The repo positions the models for both research and commercial use under an Apache-2.0 license, signaling permissive adoption paths. Documentation highlights the capability mix (reasoning, tool use, code) and points to model artifacts and guidance for evaluation. ...
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  • 23
    MetaCLIP

    MetaCLIP

    ICLR2024 Spotlight: curation/training code, metadata, distribution

    ...The repository provides training logic, adaptation strategies (e.g. prompt tuning, adapter modules), and evaluation across base and target domains to measure how well the model retains its general knowledge while specializing as needed. It includes utilities to fine-tune vision-language embeddings, compute prompt or adapter updates, and benchmark across transfer and retention metrics. MetaCLIP is especially suited for real-world settings where a model must continuously incorporate new visual categories or domains over time.
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  • 24
    JEPA

    JEPA

    PyTorch code and models for V-JEPA self-supervised learning from video

    ...The repository provides training recipes, data pipelines, and evaluation utilities for image JEPA variants and often includes ablations that illuminate which masking and architectural choices matter. Because the objective is non-autoregressive and operates in embedding space, JEPA tends to be compute-efficient and stable at scale. The approach has become a strong alternative to contrastive or pixel-reconstruction methods for representation learning.
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  • 25
    GenAI Processors

    GenAI Processors

    GenAI Processors is a lightweight Python library

    ...The library offers built-in processors for classic turn-based Gemini calls as well as Live API streaming, so you can mix “batch” and real-time interactions in the same graph. It leans on Python’s asyncio to coordinate concurrency, handle network I/O, and juggle background compute threads without blocking.
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