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18 रिपॉजिटरी

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

AI के साथ बेहतरीन रिपॉजिटरी खोजें।हम AI का उपयोग करके सबसे सटीक रिपॉजिटरी खोजेंगे।
  • pola-rs/polarspola-rs का अवतार

    pola-rs/polars

    38,855GitHub पर देखें↗

    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
    GitHub पर देखें↗38,855
  • ml-explore/mlxml-explore का अवतार

    ml-explore/mlx

    27,047GitHub पर देखें↗

    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
    GitHub पर देखें↗27,047
  • zhisheng17/flink-learningzhisheng17 का अवतार

    zhisheng17/flink-learning

    15,071GitHub पर देखें↗

    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
    GitHub पर देखें↗15,071
  • openstf/stfopenstf का अवतार

    openstf/stf

    13,904GitHub पर देखें↗

    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
    GitHub पर देखें↗13,904
  • plantuml/plantumlplantuml का अवतार

    plantuml/plantuml

    13,093GitHub पर देखें↗

    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
    GitHub पर देखें↗13,093
  • risingwavelabs/risingwaverisingwavelabs का अवतार

    risingwavelabs/risingwave

    9,093GitHub पर देखें↗

    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
    GitHub पर देखें↗9,093
  • microsoft/ufomicrosoft का अवतार

    microsoft/UFO

    9,017GitHub पर देखें↗

    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
    GitHub पर देखें↗9,017
  • apache/beamapache का अवतार

    apache/beam

    8,612GitHub पर देखें↗

    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
    GitHub पर देखें↗8,612
  • flyteorg/flyteflyteorg का अवतार

    flyteorg/flyte

    7,095GitHub पर देखें↗

    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
    GitHub पर देखें↗7,095
  • lyft/flytelyft का अवतार

    lyft/flyte

    7,095GitHub पर देखें↗

    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
    GitHub पर देखें↗7,095
  • tailwindlabs/tailwindcss-typographytailwindlabs का अवतार

    tailwindlabs/tailwindcss-typography

    6,249GitHub पर देखें↗

    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
    GitHub पर देखें↗6,249
  • nvidia/warpNVIDIA का अवतार

    NVIDIA/warp

    6,233GitHub पर देखें↗

    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
    GitHub पर देखें↗6,233
  • countly/countly-servercountly का अवतार

    countly/countly-server

    5,875GitHub पर देखें↗

    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
    GitHub पर देखें↗5,875
  • yalantis/kolodaYalantis का अवतार

    Yalantis/Koloda

    5,400GitHub पर देखें↗

    Koloda is an iOS gesture interaction library and SwiftUI view component used to create swipeable card interfaces. It provides a stack-based view component that manages overlapping views, ensuring only the top-most element remains actively interactive. The library allows for the customization of card appearance, including the configuration of overlays and animations that dictate how background cards move during a swipe. It manages drag behavior and swipe directions, triggering specific logic when cards are swiped, tapped, or fully exhausted. The component covers the implementation of gesture-

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

    Swift
    GitHub पर देखें↗5,400
  • apache/mesosapache का अवतार

    apache/mesos

    5,369GitHub पर देखें↗

    Apache Mesos is a distributed systems kernel and cluster resource manager that abstracts CPU, memory, and storage across a pool of nodes. It functions as a distributed infrastructure orchestrator, providing a layer to run multiple orchestration frameworks on a shared set of physical or virtual machines. The system acts as a resource isolation engine, dividing a shared cluster into isolated containers to run diverse workloads concurrently. It enables multi-framework orchestration, allowing different distributed application frameworks to share a single infrastructure to maximize hardware utiliz

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

    C++
    GitHub पर देखें↗5,369
  • yalantis/side-menu.androidYalantis का अवतार

    Yalantis/Side-Menu.Android

    5,212GitHub पर देखें↗

    Side-Menu.Android, Android एप्लिकेशन्स के लिए एक पुन: प्रयोज्य UI कंपोनेंट है जो स्लाइड-आउट नेविगेशन ड्रॉअर प्रदान करता है। इसे डेवलपर्स को एप्लिकेशन सेक्शन्स और यूज़र ऑप्शन्स को एक स्ट्रक्चर्ड, छिपे हुए पैनल में व्यवस्थित करने में मदद करने के लिए डिज़ाइन किया गया है, जो प्राथमिक कंटेंट क्षेत्र के लिए एक साफ़ इंटरफ़ेस बनाए रखता है। यह कंपोनेंट अपने विज़ुअल प्रेजेंटेशन के माध्यम से अलग है, जो सुसंगत और सहज यूज़र अनुभव सुनिश्चित करने के लिए Material Design दिशानिर्देशों का पालन करता है। इसमें एक डेटा-ड्रिवन मेनू पदानुक्रम है जो नेविगेशन आइटम्स के तार्किक समूहीकरण की अनुमति देता है, और इसमें मेनू खोले या बंद किए जाने पर पॉलिश विज़ुअल ट्रांज़िशन प्रदान करने के लिए फ्लूइड सर्कुलर रिवील एनिमेशन शामिल हैं। जटिल लेआउट और इंटरैक्शन लॉजिक को एक ही मॉड्यूलर क्लास में एनकैप्सुलेट करके, यह लाइब्रेरी कई स्क्रीन्स पर नेविगेशन के कार्यान्वयन को सरल बनाती है।

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

    Javaandroidanimationdrawer-layout
    GitHub पर देखें↗5,212
  • portapack-mayhem/mayhem-firmwareportapack-mayhem का अवतार

    portapack-mayhem/mayhem-firmware

    5,199GitHub पर देखें↗

    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
    GitHub पर देखें↗5,199
  • worklenz/worklenzWorklenz का अवतार

    Worklenz/worklenz

    2,921GitHub पर देखें↗

    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
    GitHub पर देखें↗2,921
  1. Home
  2. Data & Databases
  3. Resource Allocation

सब-टैग एक्सप्लोर करें

  • Device Allocators3 सब-टैग्सMechanisms 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.