6 रिपॉजिटरी
Awesome GitHub RepositoriesLoop Optimizations
Compiler transformations that optimize iteration structures to reduce runtime overhead.
Distinguishing note: None of the candidates describe compiler-level loop transformation; they focus on agent loops, event loops, or infinite loops.
Explore 6 awesome GitHub repositories matching programming languages & runtimes · Loop Optimizations. Refine with filters or upvote what's useful.
Awesome Loop Optimizations GitHub Repositories
AI के साथ बेहतरीन रिपॉजिटरी खोजें।हम AI का उपयोग करके सबसे सटीक रिपॉजिटरी खोजेंगे।
- federico-busato/modern-cpp-programming
federico-busato/Modern-CPP-Programming
15,808GitHub पर देखेंThis project is a comprehensive educational resource and programming course covering C++ language semantics and features from C++03 through C++26. It provides structured tutorials and technical guides focused on modern C++ development. The material offers specialized instruction on template metaprogramming, including the use of type traits and compile-time computations. It features detailed guides on concurrency and parallelism for multi-core execution, as well as a reference for software design applying SOLID principles and RAII. Additionally, it covers build performance optimization to redu
Covers compiler-level loop transformations including fission, fusion, and tiling to improve execution speed.
HTMLc-plus-pluscode-qualitycompilers - cython/cython
cython/cython
10,767GitHub पर देखेंCython is a compiler that translates Python code into C or C++ to create high-performance extension modules. It functions as a static typing optimizer and a C extension generator, allowing developers to declare C types within Python code to reduce interpreter overhead and increase execution speed. The project enables the wrapping of external C libraries to provide high-level interfaces to low-level system capabilities. It also serves as a native binary packager, capable of freezing scripts and their dependencies into standalone executable binaries for distribution. The system covers a broad
Transforms integer loops into efficient C implementations to reduce runtime overhead and execution time.
Cythonbig-dataccpp - openvinotoolkit/openvino
openvinotoolkit/openvino
10,414GitHub पर देखेंOpenVINO is an AI inference engine and model serving platform designed to execute optimized deep learning models across CPUs, GPUs, and NPUs through a unified API. It includes a model optimization toolkit for converting, quantizing, and compressing models from various frameworks, alongside a specialized generative AI runtime for large language models. The project distinguishes itself through a plugin-based hardware acceleration layer that maps neural network operations to vendor-specific drivers. It features advanced execution mechanisms such as continuous batching, speculative decoding, and
Detects and replaces parameter-result pairs in models containing loops to reduce inference latency.
C++aicomputer-visiondeep-learning - databricks/scala-style-guide
databricks/scala-style-guide
2,784GitHub पर देखेंRecommends using while loops over for loops or functional transformations in performance-critical code.
- intel/llvm
intel/llvm
1,497GitHub पर देखेंThe project is a reusable collection of modular compiler and toolchain technologies designed for building optimizers, code generators, and multi-language programming environments. It provides foundational compiler frontend technologies that translate source code written in C, C++, and Objective-C into a low-level programming language and intermediate code format. This intermediate representation enables cross-language analysis, program transformation, and target-independent optimization alongside a cross-platform programming framework that allows developers to write single-source accelerated a
Transforms control flow structures using mathematical models and linear programming to determine the most efficient execution layouts.
LLVMintelllvmoneapi - tiramisu-compiler/tiramisu
Tiramisu-Compiler/tiramisu
Tiramisu is a polyhedral C++ compiler framework designed to express and optimize data-parallel algorithms for diverse hardware accelerators. It provides a programming interface that allows developers to define mathematical expressions, manage loop iteration spaces, and organize functions targeting heterogeneous architectures. The system features an advanced compilation infrastructure that abstracts computations into a hardware-agnostic intermediate representation before lowering them into native machine code or hardware configuration bitstreams. It calculates exact data flow dependencies thro
Applies mathematical polytope models to reorder loop iterations and optimize data locality across multi-dimensional arrays.
C++code-generationcompilerdeep-neural-networks
