The Art of Writing Efficient Programs Second Edition Master high-performance C++ and modern concurrency by understanding how… (Fedor G. Pikus) (z-library.sk, 1lib.sk, z-lib.sk)

【One-Line Pitch】 A practical, architecture-aware guide to making modern C++ fast: it explains how CPUs, memory, compilers, and concurrency actually behave, then shows how to design code that exploits them. Best for experienced C++ developers who need to reason about performance rather than guess at it. 【Book Arc】 - **Opening (~0%–10%)**: Frames the end of the "free lunch"—clock speeds have plateaued, so speed must now come from deliberate use of CPU, memory, and concurrency resources rather than from newer hardware alone. - **Early (~10%–30%)**: Builds the hardware foundation: CPU architecture and instruction processing, including ARM alongside x86, plus memory paging and access behavior. This stage supplies the mental model later optimizations depend on. - **Middle (~30%–55%)**: Turns the model into measurement and code-level decisions—profiling, evaluating compiler choices, and using vectorization and memory-access patterns to remove real bottlenecks. - **Late (~55%–80%)**: Moves into concurrency: multithreaded and lock-free design, atomic operations and smart pointers, and memory-order guarantees that trade correctness against speed. - **Ending (~80%–100%)**: Applies these ideas at scale—NUMA-aware development, coroutine-based execution models, and APIs that remain efficient under concurrent load, including advanced throughput techniques such as "helping" in concurrent data structures. 【Key Takeaways】 - **Performance is now an engineering discipline, not a hardware gift** (Opening): the book's premise is that developers must actively exploit available computing resources because frequency scaling no longer delivers automatic gains. - **Hardware knowledge precedes optimization** (Early): understanding CPU architecture, instruction processing, and memory paging—across both x86 and ARM—is what lets you predict which changes will actually help. - **Memory access patterns often matter more than clever algorithms** (Middle): the excerpts emphasize improving access patterns across architectures, a recurring theme in high-performance C++ work. - **The compiler is a collaborator to be evaluated, not trusted blindly** (Middle): assessing compiler decisions and leveraging vectorization are presented as core, learnable skills. - **Concurrency correctness and speed are inseparable** (Late): atomic operations, smart pointers, and memory-order guarantees are framed as tools for both thread safety and performance. - **Lock-free and thread-safe structures require deliberate design** (Late): the second edition rewrites its concurrent data structures material and adds throughput techniques like "helping." - **Modern C++ concurrency has moved on** (Ending): atomic shared pointers and coroutine-based flow control are treated as current tools for building scalable APIs. - **NUMA awareness is part of production-grade performance** (Ending): the book positions NUMA-aware development as a best practice rather than a niche concern. 【Reading Tips】 - Read the CPU and memory chapters slowly; they are the conceptual spine, and later concurrency material assumes you understand them. - Treat profiling and compiler/vectorization sections as hands-on: apply them to your own code rather than reading passively. - For the concurrency chapters, pay special attention to memory-order guarantees—this is the hardest material and the easiest to get subtly wrong. - Skim material on architectures you never target (for example, ARM if you only ship x86), but note the general principles. - Keep the book's stated audience in mind: it assumes experienced C++ fluency, so beginners should build that first. 【Coverage Limits】 The available excerpts consist of the book's front matter and description, so this guide reflects the book's stated scope and structure rather than its detailed chapter contents; specific examples, benchmarks, and code walkthroughs are not covered here.