18 repository-uri
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Apache Mesos este un kernel de sisteme distribuite și un manager de resurse de cluster care abstractizează CPU-ul, memoria și stocarea pe un pool de noduri. Acesta funcționează ca un orchestrator de infrastructură distribuită, oferind un strat pentru a rula mai multe framework-uri de orchestrare pe un set partajat de mașini fizice sau virtuale. Sistemul acționează ca un motor de izolare a resurselor, împărțind un cluster partajat în containere izolate pentru a rula diverse sarcini de lucru simultan. Acesta permite orchestrarea multi-framework, permițând diferitelor framework-uri de aplicații distribuite să partajeze o singură infrastructură pentru a maximiza utilizarea hardware-ului. Proiectul acoperă distribuția de calcul la scară largă și gestionarea clusterelor distribuite. Capabilitățile sale includ gestionarea resurselor distribuite și izolarea puterii de calcul pe mai multe aplicații pentru a preveni interferențele și a asigura o performanță stabilă pe serverele partajate.
Distributes cluster resources by offering available CPU and memory to frameworks for acceptance or rejection.
Side-Menu.Android este o componentă UI reutilizabilă pentru aplicațiile Android care oferă un meniu de navigare de tip slide-out. Este concepută pentru a ajuta dezvoltatorii să organizeze secțiunile aplicației și opțiunile utilizatorului într-un panou structurat, ascuns, care menține o interfață curată pentru zona de conținut principal. Componenta se distinge prin prezentarea sa vizuală, care urmează ghidurile Material Design pentru a asigura o experiență de utilizator consistentă și intuitivă. Dispune de o ierarhie de meniu bazată pe date care permite gruparea logică a elementelor de navigare și încorporează animații fluide de tip circular reveal pentru a oferi tranziții vizuale rafinate atunci când meniul este deschis sau închis. Prin încapsularea logicii complexe de layout și interacțiune într-o singură clasă modulară, biblioteca simplifică implementarea navigării pe mai multe ecrane. Suportă tranziții bazate pe evenimente, permițând dezvoltatorilor să decupleze interacțiunile din meniu de actualizările de conținut pentru a menține o arhitectură de aplicație curată și responsivă.
Provides mechanisms for assigning tasks to resources with capacity and availability constraints.
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.
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.