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Guidelines regarding when and how to optimize software performance.
Explore 13 awesome GitHub repositories matching software engineering & architecture · Performance Optimization Principles. Refine with filters or upvote what's useful.
This repository is a comprehensive collection of data structures and algorithms implemented in JavaScript, designed primarily as an educational resource for computer science study and technical interview preparation. It provides modular implementations of fundamental programming concepts, allowing developers to explore algorithmic logic and data organization through self-contained, verifiable code examples. The library distinguishes itself by pairing every implementation with formal Big O notation, providing predictable insights into time and space scaling requirements. Each algorithm is stru
Analyzes time and space complexity to ensure efficient data processing and predictable scaling.
LeetCode-Go is a competitive programming repository and Go algorithm library. It provides a collection of optimized solutions for LeetCode challenges, focusing on time and space complexity. The project serves as a reference for data structures and algorithms implemented in Go. It covers algorithm problem solving and performance optimization to meet strict memory and runtime constraints. The repository includes capabilities for technical interview preparation and the application of Go language idioms to complex computing problems. Each solution is paired with a test suite to verify correctnes
Optimizes algorithm runtime and memory usage for computationally intensive programming tasks.
Ciphey is an automated decryption and data obfuscation tool designed to identify and reverse complex, multi-layered encoding schemes. By utilizing statistical analysis and probability scoring, the system automatically detects unknown data formats and recovers human-readable plaintext from obfuscated input strings without requiring manual algorithm specification. The tool distinguishes itself through a recursive pipeline that processes nested data structures and strips formatting anomalies or invisible characters to ensure consistent input. It employs a heuristic search and multithreaded execu
Optimizes decryption speed by combining multithreading with heuristic search algorithms.
This project is a comprehensive container framework for Go that provides a suite of fundamental data structures and algorithms. It offers a standardized set of tools for managing, sorting, and traversing complex data collections, enabling developers to implement efficient storage and retrieval logic within their applications. The library distinguishes itself through an interface-driven design that allows for interchangeable use of different storage implementations. It supports custom ordering and sorting behavior through external comparison functions, which decouple the data structures from s
Provides optimized algorithmic implementations for search, sort, and traversal to ensure high performance.
This project is a collection of educational resources and technical guides focused on Go performance optimization. It provides instruction on improving execution speed and reducing memory usage through code and architectural refinements. The guides cover advanced strategies for low-level programming, including the use of assembly for SIMD instructions and unsafe pointers for direct memory manipulation. It also details concurrency optimization techniques such as lock sharding and cache-line padding to reduce contention and improve hardware utilization. The material encompasses broad capabilit
Offers techniques for analyzing and improving the time and space complexity of algorithms to prevent degradation.
EASTL is a C++ Standard Template Library implementation consisting of containers, iterators, and algorithms. It provides cross-platform data structures and a template-based algorithm library designed for use in resource-constrained game engine environments. The library focuses on game engine memory management, providing specialized utilities that ensure predictable memory allocation and high-performance access for real-time applications. These containers maintain consistent behavior across different operating systems and hardware platforms. The project covers high-performance C++ development
Implements optimized routines for performing complex computations and transformations on data collections.
This project is a comprehensive knowledge base and study resource designed for mastering technical interviews. It provides structured guides, roadmaps, and curricula focused on data structures, algorithms, system design, and frontend engineering to help candidates prepare for software engineering screenings. The repository distinguishes itself by offering a holistic approach to professional advancement. Beyond technical drills, it includes a career development handbook covering resume optimization, salary benchmarking, and strategic negotiation coaching. It also provides detailed methodologie
Guides the use of dynamic programming and optimal data structures to improve time and space complexity.
kafka-python is a pure-Python client library for Apache Kafka that implements the Kafka wire protocol directly, without any native bindings or JVM dependencies. It provides the core capabilities of a Kafka client: producing messages to topics, consuming records from topics, and administering cluster resources such as topics and partitions, all through a Pythonic API or command-line tools. The library distinguishes itself through its comprehensive support for advanced Kafka features. It includes an asynchronous producer with background batching for throughput, a consumer group rebalance protoc
Offloads CRC32C checksum calculation to an optimized C library to reduce CPU overhead.
rsync is a file synchronization and transfer tool that copies data between local and remote systems by sending only the differences between source and destination files. It computes matching blocks using checksums, so only the unmatched portions of files are transmitted, making repeated synchronizations much faster than full copies. The tool preserves file metadata such as ownership, permissions, and modification times during transfers. rsync supports multiple transfer methods, including direct connections through a dedicated daemon mode or via remote shells like SSH. It can mirror directory
Identifies matching blocks between source and destination using checksums, so only unmatched parts are transmitted.
oneDNN 是一个深度学习加速库,为神经网络训练和推理提供优化的构建块。它管理跨 CPU 和 GPU 硬件的张量计算,支持执行用于模型训练和神经网络推理优化的高性能原语。 该项目通过硬件特定的内核优化和使用即时编译来针对特定处理器指令集脱颖而出。它支持使用静态和动态量化来执行量化神经网络,以减少内存使用并提高吞吐量。 该库涵盖了广泛的功能,包括卷积、矩阵乘法和循环神经网络执行等深度学习原语。它实现了先进的性能优化,包括操作融合、计算图优化和内存格式管理。通过稳定的 C ABI 和 C++ 包装器提供集成,并支持 SYCL、OpenCL 和外部线性代数库。 该系统包括用于硬件性能分析、原语基准测试和详细执行日志记录的观测工具。
Selects between direct, Winograd, or implicit GEMM implementations to balance performance, memory, and numerical accuracy.
This repository serves as an educational resource for computer science concepts, providing a collection of fundamental data structures and algorithmic patterns implemented in Python. It functions as a programming reference for developers seeking to understand standard software engineering patterns and data manipulation strategies. The project focuses on the construction of essential storage formats, including arrays, graphs, hash tables, linked lists, stacks, and queues. It also provides implementations for standard algorithmic techniques such as dynamic programming, recursion, sorting, and g
Teaches techniques for analyzing and improving the time and space complexity of algorithms.
This project is an educational resource providing a structured curriculum for mastering fundamental computer science concepts, algorithmic logic, and data structure implementation using Python. It serves as a comprehensive tutorial for understanding how to organize information effectively and solve complex computational challenges through systematic programming techniques. The repository focuses on the practical application of core data structures, including arrays, linked lists, hash tables, stacks, queues, and trees. It emphasizes the development of algorithmic problem-solving skills by cov
Teaches techniques for analyzing and improving the time and space complexity of code.
This project is a comprehensive reference guide for computer science fundamentals, providing structured summaries of essential data structures and algorithmic principles. It serves as a technical resource for developers to review core programming concepts, memory layouts, and operational characteristics required for software development and technical assessments. The collection distinguishes itself by offering concise, implementation-focused documentation for a wide range of standard techniques. It covers the mechanics of various sorting and searching algorithms, graph and tree traversal stra
Provides analysis of time and memory requirements to evaluate algorithm scalability.