6 repositorios
Utilities for transforming standard sequential loops into parallel versions for concurrent execution.
Distinct from Sequential Iterators: Distinct from Sequential Iterators: focuses on the transformation of loop constructs into parallel versions.
Explore 6 awesome GitHub repositories matching data & databases · Parallel Loop Transformers. Refine with filters or upvote what's useful.
Genesis is an embodied AI simulation platform and parallelized robotics simulator designed for training general-purpose robotic agents. It integrates a physics engine for robotics that calculates collisions and movements for rigid bodies, soft tissues, and fluids, alongside a photorealistic 3D rendering engine. The platform features a domain randomization framework to vary environment parameters across parallel simulations, aiding in sim-to-real transfer. It supports the integration of real-world captured light fields and Gaussian splatting to provide photorealistic backgrounds within simulat
Automatically distributes top-level execution loops across available hardware threads to improve performance.
Rayon is a data parallelism library for Rust that provides a framework for converting sequential computations into parallel operations. It enables the transformation of standard data structures and loops into parallel iterators, allowing workloads to be distributed across multiple processor cores. By utilizing a work-stealing scheduler, the library dynamically balances tasks to maximize throughput and minimize execution time. The library distinguishes itself through its focus on safe, scoped task synchronization, which ensures that all spawned operations complete before a scope exits to preve
Transforms standard sequential loops into parallel versions to process collection elements concurrently.
TileLang is a Python-embedded domain-specific language compiler that JIT-compiles and autotunes GPU kernels. It uses a tile-based DSL, automatic software pipelining, and parallel autotuning to generate optimized GPU kernels at runtime. It supports tensor core operations with Pythonic syntax, automatic memory management, and thread mapping. The compiler searches over tile sizes, thread counts, and scheduling policies, compiling and benchmarking candidates in parallel to find the fastest kernel. It also caches compiled binaries and tuning results to disk for reuse across sessions. TileLang inc
Enforces restrictions on parallel loops over local fragment buffers to ensure correctness in GPU kernels.
Async es una librería Swift que proporciona un wrapper para Grand Central Dispatch para simplificar la gestión de tareas y colas asíncronas. Funciona como un planificador de tareas para la ejecución, temporización y orquestación de bloques de código. El proyecto incluye un encadenador de tareas para secuenciar operaciones a través de diferentes hilos sin estructuras de callback anidadas y un wrapper de bucle concurrente que distribuye iteraciones a través de múltiples hilos. También cuenta con un sistema de cancelación basado en tokens para rastrear y eliminar operaciones pendientes de la cola de ejecución antes de que se ejecuten. La librería cubre la gestión de concurrencia mediante la coordinación de grupos asíncronos y la sincronización de múltiples tareas para activar acciones tras la finalización colectiva.
Transforms standard sequential loops into parallel versions for concurrent execution across multiple threads.
Joblib is a suite of utilities for parallelizing computational workloads and optimizing the storage of large numerical datasets and function results. It functions as a parallel computing library and multiprocessing wrapper that distributes function execution across multiple CPU cores to accelerate independent tasks and computational loops. The project provides a disk caching framework that persists expensive function outputs to the filesystem, re-evaluating them only when input arguments change. It further specializes in the serialization of large numerical arrays, utilizing efficient compres
Enables the transformation of standard sequential loops into parallel versions for execution across multiple CPU cores.
This project is a comprehensive framework for iOS application development, centered on building mobile applications that feature custom user interface components, asynchronous task management, and local data persistence. It serves as a technical knowledge base for software engineering, providing tools to organize and publish architectural analyses and notes in Markdown format. The framework distinguishes itself through a robust document-based storage layer that utilizes BSON-formatted records to perform CRUD operations within a NoSQL document store. It provides extensive system integration ca
Executes loop bodies in parallel across multiple threads to improve performance on large collections.