6 रिपॉजिटरी
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 is a Swift library that provides a wrapper for Grand Central Dispatch to simplify the management of asynchronous tasks and queues. It functions as a task scheduler for the execution, timing, and orchestration of code blocks. The project includes a task chainer to sequence operations across different threads without nested callback structures and a concurrent loop wrapper that distributes iterations across multiple threads. It also features a token-based cancellation system to track and remove pending operations from the execution queue before they run. The library covers concurrency ma
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.
यह प्रोजेक्ट iOS एप्लिकेशन विकास के लिए एक व्यापक फ्रेमवर्क है, जो मोबाइल एप्लिकेशन बनाने पर केंद्रित है जिसमें कस्टम यूजर इंटरफेस कंपोनेंट्स, एसिंक्रोनस कार्य प्रबंधन और स्थानीय डेटा पर्सिस्टेंस शामिल हैं। यह सॉफ़्टवेयर इंजीनियरिंग के लिए एक तकनीकी ज्ञान आधार के रूप में कार्य करता है, जो Markdown प्रारूप में आर्किटेक्चरल विश्लेषण और नोट्स को व्यवस्थित और प्रकाशित करने के लिए उपकरण प्रदान करता है। यह फ्रेमवर्क एक मजबूत दस्तावेज़-आधारित स्टोरेज लेयर के माध्यम से खुद को अलग करता है जो NoSQL दस्तावेज़ स्टोर के भीतर CRUD ऑपरेशन्स करने के लिए BSON-स्वरूपित रिकॉर्ड का उपयोग करता है। यह विशेष ऐप एक्सटेंशन संचार, क्रॉस-सैंडबॉक्स संदेश पासिंग और नेटिव शेयर शीट प्रस्तुति सहित व्यापक सिस्टम एकीकरण क्षमताएं प्रदान करता है, जो होस्ट एप्लिकेशन और सिस्टम-स्तरीय सेवाओं के बीच निर्बाध इंटरैक्शन की अनुमति देता है। यह प्रोजेक्ट थ्रेड-सेफ सिंक्रोनाइज़ेशन के साथ उन्नत समवर्ती प्रबंधन, रिस्पॉन्सिवनेस बनाए रखने के लिए बैकग्राउंड UI रेंडरिंग ऑफ़लोड और व्यापक अंतर्राष्ट्रीयकरण समर्थन सहित एक व्यापक क्षमता सतह को कवर करता है। इसमें स्टेटिक टाइप जनरेशन, स्वचालित एसेट मैपिंग और इंटरैक्टिव प्रोटोटाइप निर्माण के लिए डेवलपर-केंद्रित यूटिलिटीज के साथ-साथ भौगोलिक बीकन निगरानी और अनुकूली चार्ट निर्माण के लिए विशेष उपकरण भी शामिल हैं।
Executes loop bodies in parallel across multiple threads to improve performance on large collections.