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18 个仓库

Awesome GitHub RepositoriesResource Allocation

Configures hardware and memory requirements for data processing tasks.

Distinguishing note: Focuses on resource sizing, distinct from environment or cluster management.

Explore 18 awesome GitHub repositories matching data & databases · Resource Allocation. Refine with filters or upvote what's useful.

Awesome Resource Allocation GitHub Repositories

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  • pola-rs/polarspola-rs 的头像

    pola-rs/polars

    38,855在 GitHub 上查看↗

    Polars is a high-performance columnar data processing library designed for efficient analytical workflows. It functions as a structured data library that organizes information into typed columns, utilizing the Apache Arrow memory format to enable zero-copy data sharing and cache-friendly, vectorized operations. The engine is built to handle large-scale tabular datasets, providing both local and distributed analytical runtimes that scale from single-machine environments to multi-node clusters. The project distinguishes itself through a sophisticated lazy query engine that constructs abstract e

    Sets hardware requirements for remote query execution by specifying CPU and memory needs.

    Rustarrowdataframedataframe-library
    在 GitHub 上查看↗38,855
  • ml-explore/mlxml-explore 的头像

    ml-explore/mlx

    27,047在 GitHub 上查看↗

    This project is a machine learning array framework and tensor computation library designed for high-performance numerical computing. It provides a comprehensive suite of tools for constructing and training neural networks, featuring an automatic differentiation engine that facilitates gradient-based optimization and complex mathematical modeling. The library distinguishes itself through a unified memory architecture that allows data to be shared across CPU and GPU devices without explicit copies, significantly reducing data movement overhead. Its execution model relies on a lazy evaluation en

    Directs array operations and memory allocation to specific hardware accelerators for consistent execution.

    C++mlx
    在 GitHub 上查看↗27,047
  • zhisheng17/flink-learningzhisheng17 的头像

    zhisheng17/flink-learning

    15,071在 GitHub 上查看↗

    This project is a collection of educational resources and reference implementations for the Apache Flink stream processing framework. It provides a learning resource focused on mastering distributed stream processing through implementation guides, performance tuning tutorials, and practical examples. The repository features detailed walkthroughs for building real-time data pipelines using the DataStream and Table APIs. It includes specific integration examples for connecting Apache Flink with Kafka brokers and Elasticsearch indices, as well as reference implementations for real-time deduplica

    Configures hardware and memory requirements, including task slots, to distribute workloads across compute nodes.

    Javaclickhouseelasticsearchflink
    在 GitHub 上查看↗15,071
  • openstf/stfopenstf 的头像

    openstf/stf

    13,904在 GitHub 上查看↗

    STF is a web-based Android device management platform used to organize and control fleets of Android hardware. It functions as a device farm orchestrator and inventory manager, providing a centralized system for monitoring battery health, hardware specifications, and system versions across multiple devices. The platform distinguishes itself through a web-based screen streamer that allows for real-time interaction and application installation via a browser. It includes a remote ADB controller for executing shell commands and establishing port tunnels, as well as a booking system for time-limit

    Provides a booking system to track and lock device availability, preventing simultaneous multi-user access.

    JavaScriptandroidandroid-developmentdevice-farm
    在 GitHub 上查看↗13,904
  • plantuml/plantumlplantuml 的头像

    plantuml/plantuml

    13,093在 GitHub 上查看↗

    PlantUML is a text-to-diagram generator that translates human-readable markup into structured graphical representations. It functions as a diagram-as-code tool, allowing users to create and maintain technical documentation, architectural models, and flowcharts by decoupling diagram content from visual layout. The project distinguishes itself through a comprehensive rendering pipeline that processes domain-specific markup into various output formats, including vector and raster graphics. It utilizes a graph-based layout engine to calculate spatial positioning, while a declarative styling layer

    Task resource allocation allows users to assign tasks to specific resources with capacity percentages and manage resource availability or time-off periods.

    Javadiagramdiagram-as-codediagrams
    在 GitHub 上查看↗13,093
  • risingwavelabs/risingwaverisingwavelabs 的头像

    risingwavelabs/risingwave

    9,093在 GitHub 上查看↗

    RisingWave is a cloud-native streaming database and real-time analytics engine that uses standard SQL to process continuous data streams. It functions as a streaming data lakehouse, combining the capabilities of a streaming SQL database with a platform that integrates streaming ingestion with open table formats. The system is distinguished by its use of the PostgreSQL wire protocol, allowing it to integrate with existing SQL tools and drivers. It employs a decoupled compute and storage architecture, persisting streaming state and materialized views in cloud object storage to enable independen

    Assigns dedicated nodes for ingestion or batch execution to prevent resource competition in production.

    Rustapache-icebergdata-engineeringdatabase
    在 GitHub 上查看↗9,093
  • microsoft/ufomicrosoft 的头像

    microsoft/UFO

    9,017在 GitHub 上查看↗

    UFO is a multi-device task orchestrator and LLM agent orchestration framework designed to decompose natural language requests into executable task graphs. It functions as a cross-platform UI automation tool capable of performing interactions on Windows and mobile devices while routing tasks to distributed agents based on their hardware and software capabilities. The system is distinguished by its RAG-enhanced agent architecture, which integrates external documentation and previous execution traces to improve decision-making. It employs a hybrid UI detection approach that combines computer vis

    Assigns tasks to the most suitable device based on platform capabilities, resource monitoring, and performance history.

    Pythonagentautomationcopilot
    在 GitHub 上查看↗9,017
  • apache/beamapache 的头像

    apache/beam

    8,612在 GitHub 上查看↗

    Apache Beam is a distributed data pipeline framework and unified data processing model designed to handle both bounded batch data and unbounded real-time streams. It provides a system for building scalable, data-parallel workflows that operate across compute clusters using a single programming model. The framework utilizes a cross-runner pipeline abstraction that decouples the data processing logic from the underlying execution backend, allowing the same pipeline to run on different distributed compute engines. It supports multi-language pipeline development by translating high-level code fro

    Allows specifying hardware or runtime requirements for pipeline stages to optimize execution performance and resource allocation.

    Java
    在 GitHub 上查看↗8,612
  • flyteorg/flyteflyteorg 的头像

    flyteorg/flyte

    7,095在 GitHub 上查看↗

    Flyte is a Kubernetes-based machine learning orchestrator and containerized pipeline manager designed for coordinating AI workflows and data pipelines. It functions as an engine for defining and executing resilient pipelines, utilizing a data lineage tracker to maintain immutable execution states and ensure reproducible outputs. The platform distinguishes itself by packaging individual tasks into separate containers to ensure dependency isolation and environment consistency. It provides specialized capabilities for machine learning, including the transformation of trained models into scalable

    Dynamically assigns CPU and GPU resources at the task level, including support for spot and preemptible instances.

    Go
    在 GitHub 上查看↗7,095
  • lyft/flytelyft 的头像

    lyft/flyte

    7,095在 GitHub 上查看↗

    Flyte is a distributed machine learning pipeline manager and MLOps workflow engine. It functions as a Kubernetes-native orchestrator used to coordinate data, models, and compute resources for executing machine learning pipelines and autonomous agents at scale. The platform provides specialized infrastructure for the full machine learning lifecycle, including a dedicated model serving platform to deploy trained models as scalable production-ready inference services. It also enables the coordination and state management of autonomous AI agents. The system manages scalable pipeline execution th

    Adjusts CPU and memory limits for individual tasks based on specific workload requirements.

    Go
    在 GitHub 上查看↗7,095
  • tailwindlabs/tailwindcss-typographytailwindlabs 的头像

    tailwindlabs/tailwindcss-typography

    6,249在 GitHub 上查看↗

    Tailwind CSS Typography is a plugin for the Tailwind CSS framework that provides hand-tuned typographic defaults for blocks of vanilla HTML content, such as content from Markdown or a CMS. It applies beautiful prose styles to HTML content using a single class, eliminating the need for custom CSS to style rich text. The plugin distinguishes itself by offering deep customization and control over typography. Users can adjust the overall font size of prose content across five predefined sizes, select from five built-in gray-scale palettes to match a project's color scheme, and seamlessly adapt ty

    Applies styles based on device capabilities like pointer type and orientation using variants.

    JavaScript
    在 GitHub 上查看↗6,249
  • nvidia/warpNVIDIA 的头像

    NVIDIA/warp

    6,233在 GitHub 上查看↗

    Warp is a Python framework that JIT-compiles Python functions into CUDA kernels for GPU-accelerated parallel computation, with built-in automatic differentiation and multi-framework array interoperability. At its core, it provides a GPU kernel compilation system that enables writing and executing custom GPU kernels directly from Python, while supporting automatic gradient computation through those kernels for integration with machine learning pipelines. The framework also includes tile-based cooperative computing, where thread blocks partition into tiles for shared-memory and tensor-core opera

    Switches the default compute device for allocations and kernel launches within a code block.

    Pythoncudadifferentiable-programminggpu
    在 GitHub 上查看↗6,233
  • countly/countly-servercountly 的头像

    countly/countly-server

    5,875在 GitHub 上查看↗

    Countly is a self-hosted product analytics and engagement platform that tracks user behavior across mobile, web, and desktop applications. It collects and analyzes device properties, user actions, and session lifecycle data to understand engagement patterns, while also providing crash reporting, push notification delivery, and A/B testing capabilities. The platform is designed for privacy-first deployment, with built-in consent management and the ability to run entirely on private infrastructure. The platform distinguishes itself through its comprehensive feature set that combines analytics w

    Allows overriding device properties like OS version in analytics data.

    JavaScript
    在 GitHub 上查看↗5,875
  • yalantis/kolodaYalantis 的头像

    Yalantis/Koloda

    5,400在 GitHub 上查看↗

    Koloda 是一款 iOS 手势交互库和 SwiftUI 视图组件,用于创建可滑动的卡片界面。它提供了一个基于堆栈的视图组件,用于管理重叠视图,确保只有最顶层的元素保持活跃交互。 该库允许自定义卡片外观,包括配置覆盖层和动画,这些动画决定了滑动过程中背景卡片的移动方式。它管理拖拽行为和滑动方向,在卡片被滑动、点击或完全耗尽时触发特定逻辑。 该组件涵盖了手势驱动视图转换的实现,以及用户通过常见选择交互模式关闭的卡片堆栈的渲染。

    Tracks availability and project assignments via a calendar to staff projects and plan capacity.

    Swift
    在 GitHub 上查看↗5,400
  • apache/mesosapache 的头像

    apache/mesos

    5,369在 GitHub 上查看↗

    Apache Mesos 是一个分布式系统内核和集群资源管理器,抽象了节点池中的 CPU、内存和存储。它作为一个分布式基础设施编排器,提供了一个在共享物理或虚拟机器集上运行多个编排框架的层。 该系统充当资源隔离引擎,将共享集群划分为隔离的容器以并发运行各种工作负载。它实现了多框架编排,允许不同的分布式应用框架共享单个基础设施,从而最大化硬件利用率。 该项目涵盖了大规模计算分发和分布式集群管理。其功能包括管理分布式资源,并跨多个应用隔离计算能力,以防止干扰并确保共享服务器上的稳定性能。

    Distributes cluster resources by offering available CPU and memory to frameworks for acceptance or rejection.

    C++
    在 GitHub 上查看↗5,369
  • yalantis/side-menu.androidYalantis 的头像

    Yalantis/Side-Menu.Android

    5,212在 GitHub 上查看↗

    Side-Menu.Android is a reusable UI component for Android applications that provides a slide-out navigation drawer. It is designed to help developers organize application sections and user options into a structured, hidden panel that maintains a clean interface for the primary content area. The component distinguishes itself through its visual presentation, which follows Material Design guidelines to ensure a consistent and intuitive user experience. It features a data-driven menu hierarchy that allows for logical grouping of navigation items, and it incorporates fluid circular reveal animatio

    Provides mechanisms for assigning tasks to resources with capacity and availability constraints.

    Javaandroidanimationdrawer-layout
    在 GitHub 上查看↗5,212
  • portapack-mayhem/mayhem-firmwareportapack-mayhem 的头像

    portapack-mayhem/mayhem-firmware

    5,199在 GitHub 上查看↗

    Mayhem-Firmware is a custom firmware for the PortaPack add-on that transforms a HackRF software-defined radio into a standalone handheld device capable of receiving, transmitting, and analyzing radio signals across a wide frequency range. The firmware provides a complete operational environment with an event-driven touchscreen interface, a menu-driven application launcher, and a real-time sample streaming pipeline that connects the hardware abstraction layer to a suite of modular applications. All user data, including frequency presets, captures, and configuration files, are stored on a remova

    Provides on-screen menus to configure SDR hardware parameters, display, and calibration settings.

    Chackrfhackrf-componentsportapack
    在 GitHub 上查看↗5,199
  • worklenz/worklenzWorklenz 的头像

    Worklenz/worklenz

    2,921在 GitHub 上查看↗

    Worklenz is a project management platform and professional services automation tool designed for planning work, tracking tasks via Kanban boards, and managing team collaboration. It functions as a combined resource management tool and time tracking software, providing a centralized workspace to analyze team capacity, balance workloads, and log work hours. The platform is distinguished by its deep integration with GitHub and Slack, allowing for the synchronization of repository activity and the delivery of real-time project notifications to external communication channels. It further streamlin

    Analyzes member capacity across projects to prevent overloading and balance resource distribution.

    TypeScriptexpressjspostgresqlproject-management
    在 GitHub 上查看↗2,921
  1. Home
  2. Data & Databases
  3. Resource Allocation

探索子标签

  • Device Allocators3 个子标签Mechanisms for mapping data structures to specific hardware devices. **Distinct from Resource Allocation:** Distinct from Resource Allocation: focuses on device-level memory placement for tensors, not general resource sizing.
  • Offer-Based AllocationResource distribution via offers of available CPU and memory to frameworks for acceptance. **Distinct from Resource Allocation:** Distinct from static sizing: implements a dynamic offer-and-accept mechanism between master and framework
  • Project Resource AllocatorsMechanisms for assigning tasks to resources with capacity and availability constraints. **Distinct from Resource Allocation:** Distinct from data-processing resource allocation: focuses on human or project-based resource capacity management rather than hardware or memory sizing.