Awesome GitHub RepositoriesZero-Copy Array Slicing

nom is a parser combinator framework for Rust used to build complex parsers by combining small, reusable parsing functions. It functions as a zero-copy parsing tool that minimizes memory overhead by returning slices of the original input instead of allocating new memory. The framework is designed for diverse data formats, serving as a binary data parser with configurable endianness and a bitstream processing library capable of extracting values of arbitrary bit length. It also functions as a streaming data parser that can process data arriving in chunks and signal when additional input is req

100 Go Mistakes is a reference book and code review companion that catalogues frequent Go programming anti-patterns and provides corrected implementations for each one. It covers a wide range of common pitfalls, from range loop variable capture and interface nil handling to error wrapping and map iteration randomization, helping developers recognize and avoid these issues in their own code. The project distinguishes itself by offering a structured, example-driven approach to learning idiomatic Go. It covers core design decisions such as when to use pointer versus value receivers, how to apply

language-ext is a functional programming framework for C# that provides a suite of immutable data structures and monadic types. It enables the implementation of pure functional programming patterns, utilizing containers to manage side effects, optional values, and error handling. The library is distinguished by its advanced concurrency and state management tools, including a software transactional memory system and lock-free atomic references. It also provides specialized utilities for distributed systems, such as vector clocks for causality tracking and deterministic data conflict resolution

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

Acest proiect este un ghid cuprinzător de programare pentru performanță și o referință pentru limbajul Go, concentrându-se pe eficiența runtime și optimizarea memoriei. Oferă o colecție de tipare și tehnici concepute pentru a crește viteza de execuție prin reducerea overhead-ului garbage collection-ului și optimizarea utilizării memoriei. Resursa se distinge prin implementări de referință detaliate pentru optimizarea memoriei, cum ar fi escape analysis, object pooling și alinierea memoriei structurilor. Oferă strategii specifice pentru reducerea dimensiunii binarului și îmbunătățirea eficienței cache-ului CPU prin optimizarea layout-ului memoriei structurilor și utilizarea placeholder-elor cu alocare zero. Proiectul acoperă o gamă largă de capabilități de inginerie backend, inclusiv gestionarea concurenței cu worker pools și primitive de sincronizare, RPC de înaltă performanță și rutare HTTP, precum și strategii de caching distribuit. Include, de asemenea, îndrumări privind observabilitatea prin profilarea CPU și a memoriei, precum și tipare de asigurare a calității pentru unit testing funcțional și generarea de obiecte mock. Conținutul este structurat ca o serie de tutoriale, exemple arhitecturale și ghiduri de benchmarking pentru a ajuta dezvoltatorii să analizeze și să remedieze blocajele de performanță.

xtensor is a C++ multidimensional array library for numerical computing that provides N-dimensional containers with an interface mirroring the NumPy API. It utilizes a lazy evaluation expression engine to defer numerical computations until assignment, which minimizes memory allocations and intermediate copies. The library features a foreign memory array adaptor that allows it to wrap external buffers, such as NumPy arrays, to perform numerical operations in-place without duplicating data. It further optimizes performance through lazy broadcasting and a system that manages the lifetime of temp