5 个仓库
Awesome GitHub RepositoriesPerformance Optimization Patterns
Coding patterns and techniques for optimizing performance in hot code paths, including loop selection and allocation avoidance.
Distinguishing note: None of the candidates relate to performance optimization; they all describe agentic or code refinement loops in AI/ML contexts.
Explore 5 awesome GitHub repositories matching software engineering & architecture · Performance Optimization Patterns. Refine with filters or upvote what's useful.
Awesome Performance Optimization Patterns GitHub Repositories
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- braydie/howtobeaprogrammer
braydie/HowToBeAProgrammer
16,218在 GitHub 上查看HowToBeAProgrammer is a comprehensive software engineering career guide and professional development framework. It serves as a curated-knowledge repository and handbook designed to help programmers acquire technical habits and social competencies necessary for professional advancement. The project distinguishes itself by integrating technical craftsmanship with a detailed manual for technical leadership and organizational navigation. It provides specific strategies for career progression, such as compensation negotiation, promotion readiness, and the management of professional boundaries to p
Describes coding patterns for reducing execution time by minimizing expensive memory or I/O calls in hot paths.
learningprogramming - piglei/one-python-craftsman
piglei/one-python-craftsman
7,211在 GitHub 上查看This project is a comprehensive Python coding guide and software engineering resource focused on professional development practices. It provides a detailed collection of idiomatic techniques, design patterns, and architectural strategies to improve code quality and maintainability. The guide emphasizes advanced design patterns such as dependency injection, data-driven design, and the application of SOLID principles for object-oriented design. It distinguishes itself by covering sophisticated structural strategies, including class-based decorators, the separation of interfaces from implementat
Details performance optimization patterns such as efficient iterator use and container selection to reduce memory usage.
articlesbookpython - juanitofatas/fast-ruby
JuanitoFatas/fast-ruby
5,730在 GitHub 上查看该项目是一个 Ruby 性能优化指南和重构资源。它提供了一系列经过基准测试的编码模式和惯用法对比，旨在提高 Ruby 应用的执行速度并减少内存分配。 该资源专注于将常见的语言结构映射到其计算效率最高的等效形式。它使用对比计时分析和分配计数分析来识别能够替代对象密集型表达式的高性能惯用法。 该项目涵盖了应用运行时调优和内存管理，通过识别能够减少垃圾回收开销的模式来实现。它采用基准驱动开发来评估特定语言特性对系统内存和执行速度的影响。
Provides benchmarked coding patterns and techniques for optimizing performance in hot code paths.
Ruby - databricks/scala-style-guide
databricks/scala-style-guide
2,784在 GitHub 上查看Provides guidelines for using while loops over for loops to avoid iterator allocation in performance-critical code.
- packtpublishing/learn-cuda-programming
PacktPublishing/Learn-CUDA-Programming
1,258在 GitHub 上查看This project serves as a comprehensive educational resource for learning parallel programming and high-performance computing using graphics processing units. It provides technical guidance on the fundamental paradigms required to offload computationally intensive tasks from a host system to specialized hardware accelerators. The materials cover the core methodologies for managing data-parallel operations, including the orchestration of memory between host and device spaces and the organization of threads into structured grids and blocks. It details the execution models necessary to distribute
Provides comprehensive strategies for analyzing execution metrics, identifying bottlenecks, and optimizing kernel performance in parallel computing environments.
Cuda
