Performance

Introduction Multithreading is a cornerstone of modern software development, enabling applications to perform multiple operations concurrently, improve responsiveness, and fully exploit multicore processors. On Linux and other POSIX‑compliant systems, the libpthread library (commonly referred to as pthread) provides the standard API for creating and managing threads. This article is a deep dive into libpthread. We will explore its history, core concepts, API details, practical coding patterns, performance considerations, debugging techniques, and real‑world usage scenarios. By the end, you should be comfortable designing robust, high‑performance multithreaded applications that leverage libpthread effectively. ...

Table of Contents Introduction What Is Dispenso? Why Choose Dispenso Over Other Thread Pools? Core Concepts and Architecture 4.1 Task Representation 4.2 Worker Threads and Queues 4.3 Work Stealing Mechanics Getting Started: Building and Integrating Dispenso Basic Usage Patterns 6.1 Submitting Simple Tasks 6.2 Futures and Continuations 6.3 Parallel Loops with parallel_for Advanced Techniques 7.1 Task Dependencies with when_all and when_any 7.2 Custom Allocators and Memory Management 7.3 Thread‑Local Storage & Affinity 7.4 Integrating with Existing Codebases (e.g., OpenCV, Eigen) Performance Benchmarking 8.1 Micro‑benchmarks: Overhead vs. Raw Threads 8.2 Real‑World Scenario: Image Processing Pipeline Best Practices and Common Pitfalls Conclusion Resources Introduction Parallel programming in modern C++ has evolved dramatically since the introduction of the <thread> library in C++11. While the standard library provides low‑level primitives, most production‑grade applications need higher‑level abstractions that can efficiently schedule work across many cores, handle task dependencies, and minimize overhead. This is where Dispenso shines. ...

Introduction In today’s digital landscape, users expect instant gratification. A page that loads in a split second feels fast, trustworthy, and professional, while a sluggish page drives visitors away and hurts conversion rates. One of the most effective techniques to shave milliseconds—sometimes seconds—off perceived load time is lazy loading. Lazy loading (sometimes called deferred loading or on‑demand loading) postpones the retrieval of resources until they are actually needed. By doing so, you reduce the amount of data transferred during the initial page request, lower memory consumption, and give browsers (or native runtimes) more breathing room to render the most important content first. ...

Introduction A polling loop is one of the oldest and most ubiquitous patterns in software engineering. At its core, it repeatedly checks the state of a resource—be it a hardware register, a network socket, or a remote service—and reacts when a desired condition becomes true. While the concept is simple, writing a robust, efficient, and maintainable polling loop can be surprisingly subtle. In modern systems, developers often face a choice between pull‑based approaches (polling) and push‑based approaches (interrupts, callbacks, or event streams). The decision hinges on latency requirements, power constraints, architectural complexity, and the nature of the underlying API. ...

Introduction Since its launch in 2022, Bun has rapidly become one of the most talked‑about JavaScript runtimes. Built on top of the Zig programming language and the JavaScriptCore engine, Bun promises blazing‑fast start‑up times, low memory footprints, and a batteries‑included standard library that includes a modern HTTP server. If you’ve spent years building APIs with Node.js, Express, or Fastify, you might wonder whether Bun’s HTTP server can replace—or at least complement—your existing stack. This article dives deep into the Bun HTTP server, covering everything from installation and basic usage to advanced routing, middleware, WebSockets, performance tuning, and production deployment. By the end, you’ll have a production‑ready codebase and a clear understanding of where Bun shines and where you still might need to reach for other tools. ...