The blog post "Beware of Fast-Math" warns against indiscriminately using the -ffast-math compiler optimization. While it can significantly improve performance, it relaxes adherence to IEEE 754 floating-point standards, leading to unexpected results in programs that rely on precise floating-point behavior. Specifically, it can alter the order of operations, remove or change rounding operations, and assume no special values like NaN and Inf. This can break seemingly innocuous code, especially comparisons and calculations involving edge cases. The post recommends carefully considering the trade-offs and only using -ffast-math if you understand the implications and have thoroughly tested your code for numerical stability. It also suggests exploring alternative optimizations like -fno-math-errno, -funsafe-math-optimizations, or specific flags targeting individual operations if finer-grained control is needed.
The C++ to Rust Phrasebook provides a quick reference for C++ developers transitioning to Rust. It maps common C++ idioms and patterns to their Rust equivalents, covering topics like memory management, error handling, data structures, and concurrency. The guide focuses on demonstrating how familiar C++ concepts translate into Rust's ownership, borrowing, and lifetime systems, aiming to ease the learning curve by providing concrete examples and highlighting key differences. It's designed as a practical resource for quickly finding idiomatic Rust solutions to problems commonly encountered in C++.
Hacker News users discussed the usefulness of the C++ to Rust Phrasebook, generally finding it a helpful resource, particularly for those transitioning from C++ to Rust. Several commenters pointed out specific examples where the phrasebook's suggested translations weren't ideal, offering alternative Rust idioms or highlighting nuances between the two languages. Some debated the best way to handle memory management and ownership in Rust compared to C++, focusing on the complexities of borrowing and lifetimes. A few users also mentioned existing tools and resources, like c2rust and the Rust book, as valuable complements to the phrasebook. Overall, the sentiment was positive, with commenters appreciating the effort to bridge the gap between the two languages.
The blog post "Learning C3" details the author's experience learning the C3 linearization algorithm used for multiple inheritance in programming languages like Python and R. They found the algorithm initially complex and confusing due to its recursive nature and reliance on Method Resolution Order (MRO). Through a step-by-step breakdown of the algorithm's logic and the use of visual aids like diagrams, the author gained a deeper understanding. They highlight how the algorithm prevents unexpected behavior from the "diamond problem" in multiple inheritance by establishing a predictable and consistent method lookup order. The post concludes with the author feeling satisfied with their newfound comprehension of C3 and its importance for robust object-oriented programming.
HN commenters generally praised the article for its clarity and approachable explanation of C3, a complex topic. Several appreciated the author's focus on practical usage and avoidance of overly academic language. Some pointed out that while C3 is important for understanding multiple inheritance and mixins, it's less relevant in languages like Python which use a simpler method resolution order. One commenter highlighted the importance of understanding the underlying concepts even if using languages that abstract away C3, as it aids in debugging and comprehending complex inheritance hierarchies. Another commenter pointed out that Python's MRO is actually a derivative of C3. A few expressed interest in seeing a follow-up article covering the performance implications of C3.
The blog post details performance improvements made to the rav1d AV1 decoder. By optimizing assembly code, particularly SIMD vectorization for x86 and ARM architectures, and refining C code for frequently used functions, the decoder saw significant speedups. Specifically, film grain synthesis, inverse transforms, and CDEF (Constrained Directional Enhancement Filter) saw substantial performance gains, resulting in a roughly 10-20% overall decoding speed increase depending on the content and platform. These optimizations contribute to faster AV1 decoding, making rav1d more competitive with other decoders and benefiting real-world playback scenarios.
Hacker News users discussed potential reasons for rav1d's performance improvements, including SIMD optimizations, assembly code usage, and more efficient memory access patterns. Some expressed skepticism about the benchmark methodology, wanting more detail on the specific clips and encoding settings used. Others highlighted the importance of these optimizations for real-world applications like video conferencing and streaming, particularly on lower-powered devices. There was also interest in whether these gains would translate to other AV1 decoders like dav1d. A few commenters praised the detailed analysis and clear presentation of the findings in the original blog post.
The author attempted to optimize a simple matrix multiplication kernel for GPUs, expecting minimal gains due to its simplicity. Surprisingly, they achieved significant performance improvements by focusing on memory access patterns. By transposing one of the input matrices and padding it to align with the GPU's memory layout, they drastically reduced non-coalesced memory accesses, leading to a 4x speedup. This highlighted the importance of considering memory access patterns even in seemingly straightforward GPU operations, proving that even "pointless" optimizations can yield substantial results.
HN commenters generally agreed with the article's premise that premature optimization is wasteful. Several pointed out that profiling is crucial before attempting optimization, and that often the biggest gains come from algorithmic improvements rather than low-level tweaks. Some discussed the value of simpler code, even if slightly less performant, emphasizing maintainability and developer time. One commenter highlighted the importance of considering the entire system, noting that optimizing one component might shift the bottleneck elsewhere. Others offered alternative optimization strategies for the specific scenario described in the article, including using half-precision floats and vectorized operations. A few commenters expressed skepticism about the author's conclusions, suggesting they might be specific to their hardware or implementation.
The author envisions a future (2025 and beyond) where creating video games without a traditional game engine becomes increasingly viable. This is driven by advancements in web technologies like WebGPU, which offer native performance, and readily available libraries handling complex tasks like physics and rendering. Combined with the growing accessibility of AI tools for asset creation and potentially even gameplay logic, the barrier to entry for game development lowers significantly. This empowers smaller teams and individual developers to bring their unique game ideas to life, focusing on creativity rather than wrestling with complex engine setup and low-level programming. This shift mirrors the transition seen in web development, moving from manual HTML/CSS/JS to higher-level frameworks and tools.
Hacker News users discussed the practicality and appeal of the author's approach to game development. Several commenters questioned the long-term viability of building and maintaining custom engines, citing the significant time investment and potential for reinventing the wheel. Others expressed interest in the minimalist philosophy, particularly for smaller, experimental projects where creative control is paramount. Some pointed out the existing tools like raylib and Love2D that offer a middle ground between full-blown engines and building from scratch. The discussion also touched upon the importance of understanding underlying principles, regardless of the chosen tools. Finally, some users debated the definition of a "game engine" and whether the author's approach qualifies as engine-less.
Jason Thorsness's blog post "Tower Defense: Cache Control" uses the analogy of tower defense games to explain how caching improves website performance. Just like strategically placed towers defend against incoming enemies, various caching layers intercept requests for website assets (like images and scripts), preventing them from reaching the origin server. These layers, including browser cache, CDN, and server-side caching, progressively filter requests, reducing server load and latency. Each layer has its own "rules of engagement" (cache-control headers) dictating how long and under what conditions resources are stored and reused, optimizing the delivery of content and improving the overall user experience.
Hacker News users discuss the blog post about optimizing a Tower Defense game using aggressive caching and precomputation. Several commenters praise the author's in-depth analysis and clear explanations, particularly the breakdown of how different caching strategies impact performance. Some highlight the value of understanding fundamental optimization techniques even in the context of a seemingly simple game. Others offer additional suggestions for improvement, such as exploring different data structures or considering the trade-offs between memory usage and processing time. One commenter notes the applicability of these optimization principles to other domains beyond game development, emphasizing the broader relevance of the author's approach. Another points out the importance of profiling to identify performance bottlenecks, echoing the author's emphasis on data-driven optimization. A few commenters share their own experiences with similar optimization challenges, adding practical perspectives to the discussion.
The blog post details achieving remarkably fast CSV parsing speeds of 21 GB/s on an AMD Ryzen 9 9950X using SIMD instructions. The author leverages AVX-512, specifically the _mm512_maskz_shuffle_epi8 instruction, to efficiently handle character transpositions needed for parsing, significantly outperforming scalar code and other SIMD approaches. This optimization focuses on efficiently handling quoted fields containing commas and escapes, which typically pose performance bottlenecks for CSV parsers. The post provides benchmark results and code snippets demonstrating the technique.
Hacker News users discussed the impressive speed demonstrated in the article, but also questioned its practicality. Several commenters pointed out that real-world CSV data often includes complexities like quoted fields, escaped characters, and varying data types, which the benchmark seemingly ignores. Some suggested alternative approaches like Apache Arrow or memory-mapped files for better real-world performance. The discussion also touched upon the suitability of using AVX-512 for this task given its power consumption, and the possibility of achieving comparable performance with simpler SIMD instructions. Several users expressed interest in seeing benchmarks with more realistic datasets and comparisons to other CSV parsing libraries. Finally, the highly specialized nature of the code and its reliance on specific hardware were highlighted as potential limitations.
This post explores implementing a "struct of arrays" (SoA) data structure in C++ as a performance optimization. Instead of grouping data members together by object like a traditional struct (AoS - array of structs), SoA groups members of the same type into contiguous arrays. This allows for better vectorization and improved cache locality, especially when iterating over a single member across many objects, as demonstrated with benchmarks involving summing and multiplying vector components. The post details the implementation using std::span and explores variations using templates and helper functions for easier data access. It concludes that SoA, while offering performance advantages in certain scenarios, comes with added complexity in access patterns and code readability, making AoS the generally preferred approach unless performance demands necessitate the SoA layout.
Hacker News users discuss the benefits and drawbacks of Structure of Arrays (SoA) versus Array of Structures (AoS). Several commenters highlight the performance advantages of SoA, particularly for SIMD operations and reduced cache misses due to better data locality when accessing a single field across multiple elements. However, others point out that AoS can be more intuitive and simpler to work with, especially for smaller data sets where the performance gains of SoA might not be significant. Some suggest that the choice between SoA and AoS depends heavily on the specific use case and access patterns. One commenter mentions the "Structure of Arrays Layout" feature planned for C++ which would provide the benefits of SoA without sacrificing the ease of use of AoS. Another user suggests using a library like Vc or Eigen for easier SIMD vectorization. The discussion also touches upon related topics like data-oriented design and the challenges of maintaining code that uses SoA.
JetBrains' C/C++ IDE, CLion, is now free for non-commercial projects, including personal learning, open-source contributions, and academic purposes. This free version offers the full functionality of the professional edition, including code completion, refactoring tools, and debugger integration. Users need a JetBrains Account and must renew their free license annually. While primarily aimed at individuals, some qualifying educational institutions and classroom assistance scenarios can also access free licenses through separate programs.
HN commenters largely expressed positive sentiment towards JetBrains making CLion free for non-commercial use. Several pointed out that this move might be a response to the increasing popularity of VS Code with its extensive C/C++ extensions, putting competitive pressure on CLion. Some appreciated the clarification of what constitutes "non-commercial," allowing open-source developers and hobbyists to use it freely. A few expressed skepticism, wondering if this is a temporary measure or a lead-in to a different pricing model down the line. Others noted the continued absence of a free community edition, unlike other JetBrains IDEs, which might limit broader adoption and contribution. Finally, some discussed the merits of CLion compared to other IDEs and the potential impact of this change on the competitive landscape.
Terry Cavanagh has released the source code for his popular 2D puzzle platformer, VVVVVV, under the MIT license. The codebase, primarily written in C++, includes the game's source, assets, and build scripts for various platforms. This release allows anyone to examine, modify, and redistribute the game, fostering learning and potential community-driven projects based on VVVVVV.
HN users discuss the VVVVVV source code release, praising its cleanliness and readability. Several commenters highlight the clever use of fixed-point math and admire the overall simplicity and elegance of the codebase, particularly given the game's complexity. Some share their experiences porting the game to other platforms, noting the ease with which they were able to do so thanks to the well-structured code. A few commenters express interest in studying the game's level design and collision detection implementation. There's also a discussion about the use of SDL and the challenges of porting older C++ code, with some reflecting on the game development landscape of the time. Finally, several users express appreciation for Terry Cavanagh's work and the decision to open-source the project.
The author recounts how Matt Godbolt inadvertently convinced them to learn Rust by demonstrating C++'s complexity. During a C++ debugging session using Compiler Explorer, Godbolt showed how seemingly simple C++ code generated a large amount of assembly, highlighting the hidden costs and potential for unexpected behavior. This experience, coupled with existing frustrations with C++'s memory management and error-proneness, prompted the author to finally explore Rust, a language designed for memory safety and performance predictability. The contrast between the verbose and complex C++ output and the cleaner, more manageable Rust equivalent solidified the author's decision.
HN commenters largely agree with the author's premise, finding the C++ example overly complex and fragile. Several pointed out the difficulty in reasoning about C++ code, especially when dealing with memory management and undefined behavior. Some highlighted Rust's compiler as a significant advantage, enforcing memory safety and preventing common errors. Others debated the relative merits of both languages, acknowledging C++'s performance benefits in certain scenarios, while emphasizing Rust's increased safety and developer productivity. A few users discussed the learning curve associated with Rust, but generally viewed it as a worthwhile investment for long-term project maintainability. One commenter aptly summarized the sentiment: C++ requires constant vigilance against subtle bugs, while Rust provides guardrails that prevent these issues from arising in the first place.
Nnd is a terminal-based debugger presented as a modern alternative to GDB and LLDB. It aims for a simpler, more intuitive user experience with a focus on speed and ease of use. Key features include a built-in disassembler, register view, memory viewer, and expression evaluator. Nnd emphasizes its clean and responsive interface, striving to minimize distractions and improve the overall debugging workflow. The project is open-source and written in Rust, currently supporting debugging on Linux for x86_64, aarch64, and RISC-V architectures.
Hacker News users generally praised nnd for its speed and simplicity compared to GDB and LLDB, particularly appreciating its intuitive TUI interface. Some commenters noted its current limitations, such as a lack of support for certain features like conditional breakpoints and shared libraries, but acknowledged its potential given it's a relatively new project. Several expressed interest in trying it out or contributing to its development. The focus on Rust debugging was also highlighted, with some suggesting its specialized nature in this area could be a significant advantage. A few users compared it favorably to other debugging tools like gdb -tui and even IDE debuggers, suggesting its speed and simplicity could make it a preferred choice for certain tasks.
This blog post explores optimizing bitonic sorting networks on GPUs using CUDA SIMD intrinsics. The author demonstrates significant performance gains by leveraging these intrinsics, particularly __shfl_xor_sync, to efficiently perform the comparisons and swaps fundamental to the bitonic sort algorithm. They detail the implementation process, highlighting key optimizations like minimizing register usage and aligning memory access. The benchmarks presented show a substantial speedup compared to a naive CUDA implementation and even outperform CUB's radix sort for specific input sizes, demonstrating the potential of SIMD intrinsics for accelerating sorting algorithms on GPUs.
Hacker News users discussed the practicality and performance implications of the bitonic sorting algorithm presented in the linked blog post. Some questioned the real-world benefits given the readily available, highly optimized existing sorting libraries. Others expressed interest in the author's specific use case and whether it involved sorting short arrays, where the bitonic sort might offer advantages. There was a general consensus that demonstrating a significant performance improvement over existing solutions would be key to justifying the complexity of the SIMD/CUDA implementation. One commenter pointed out the importance of considering data movement costs, which can often overshadow computational gains, especially in GPU programming. Finally, some suggested exploring alternative algorithms, like radix sort, for potential further optimizations.
ROSplat integrates the fast, novel 3D reconstruction technique called Gaussian Splatting into the Robot Operating System 2 (ROS2). It provides a ROS2 node capable of subscribing to depth and color image streams, processing them in real-time using CUDA acceleration, and publishing the resulting 3D scene as a point cloud of splats. This allows robots and other ROS2-enabled systems to quickly and efficiently generate detailed 3D representations of their environment, facilitating tasks like navigation, mapping, and object recognition. The project includes tools for visualizing the reconstructed scene and offers various customization options for splat generation and rendering.
Hacker News users generally expressed excitement about ROSplat, praising its speed and visual fidelity. Several commenters discussed potential applications, including robotics, simulation, and virtual reality. Some raised questions about the computational demands and scalability, particularly regarding larger point clouds. Others compared ROSplat favorably to existing methods, highlighting its efficiency improvements. A few users requested clarification on specific technical details like licensing and compatibility with different hardware. The integration with ROS2 was also seen as a significant advantage, opening up possibilities for robotic applications. Finally, some commenters expressed interest in seeing the technique applied to dynamic scenes and discussed the potential challenges involved.
"Compiler Reminders" serves as a concise cheat sheet for compiler development, particularly focusing on parsing and lexing. It covers key concepts like regular expressions, context-free grammars, and popular parsing techniques including recursive descent, LL(1), LR(1), and operator precedence. The post briefly explains each concept and provides simple examples, offering a quick refresher or introduction to the core components of compiler construction. It also touches upon abstract syntax trees (ASTs) and their role in representing parsed code. The post is meant as a handy reference for common compiler-related terminology and techniques, not a comprehensive guide.
HN users largely praised the article for its clear and concise explanations of compiler optimizations. Several commenters shared anecdotes of encountering similar optimization-related bugs, highlighting the practical importance of understanding these concepts. Some discussed specific compiler behaviors and corner cases, including the impact of volatile keyword and undefined behavior. A few users mentioned related tools and resources, like Compiler Explorer and Matt Godbolt's talks. The overall sentiment was positive, with many finding the article a valuable refresher or introduction to compiler optimizations.
A hobby operating system, RetrOS-32, built from scratch, is now functional on a vintage IBM ThinkPad. Written primarily in C and some assembly, it supports a 32-bit protected mode environment, features a custom kernel, and boasts a simple command-line interface. Currently, functionalities include keyboard input, text-based screen output, and disk access, with the developer aiming to eventually expand to a graphical user interface and more advanced features. The project, RetrOS-32, is available on GitHub and showcases a passion for low-level programming and operating system development.
Hacker News users generally expressed enthusiasm for the RetrOS-32 project, praising the author's dedication and the impressive feat of creating a hobby OS. Several commenters reminisced about their own experiences with older hardware and OS development. Some discussed the technical aspects of the project, inquiring about the choice of programming language (C) and the possibility of adding features like protected mode or multitasking. A few users expressed interest in contributing to the project. There was also discussion about the challenges and rewards of working with older hardware, with some users sharing their own experiences and advice.
Berkeley Humanoid Lite is an open-source, 3D-printable miniature humanoid robot designed for research and education. It features a modular design, allowing for customization and experimentation with different components and actuators. The project provides detailed documentation, including CAD files, assembly instructions, and software, enabling users to build and program their own miniature humanoid robot. This low-cost platform aims to democratize access to humanoid robotics research and fosters a community-driven approach to development.
HN commenters generally expressed excitement about the open-sourcing of the Berkeley Humanoid Lite robot, praising the project's potential to democratize robotics research and development. Several pointed out the significantly lower cost compared to commercially available alternatives, making it more accessible to smaller labs and individuals. Some discussed the potential applications, including disaster relief, home assistance, and research into areas like gait and manipulation. A few questioned the practicality of the current iteration due to limitations in battery life and processing power, but acknowledged the value of the project as a starting point for further development and community contributions. Concerns were also raised regarding the safety implications of open-sourcing robot designs, with one commenter suggesting the need for careful consideration of potential misuse.
GCC 15.1, the latest stable release of the GNU Compiler Collection, is now available. This release brings substantial improvements across multiple languages, including C, C++, Fortran, D, Ada, and Go. Key enhancements include improved experimental support for C++26 and C2x standards, enhanced diagnostics and warnings, optimizations for performance and code size, and expanded platform support. Users can expect better compile times and generated code quality. This release represents a significant step forward for the GCC project and offers developers a more robust and feature-rich compiler suite.
HN commenters largely focused on specific improvements in GCC 15. Several praised the improved diagnostics, making debugging easier. Some highlighted the Modula-2 language support improvements as a welcome addition. Others discussed the benefits of the enhanced C++23 and C2x support, including modules and improved ranges. A few commenters noted the continuing, though slow, progress on static analysis features. There was also some discussion on the challenges of supporting multiple architectures and languages within a single compiler project like GCC.
Microsoft has removed its official C/C++ extension from downstream forks of VS Code, including VSCodium and Open VSX Registry. This means users of these open-source alternatives will lose access to features like IntelliSense, debugging, and other language-specific functionalities provided by the proprietary extension. While the core VS Code editor remains open source, the extension relies on proprietary components and Microsoft has chosen to restrict its availability solely to its official, Microsoft-branded VS Code builds. This move has sparked controversy, with some accusing Microsoft of "embrace, extend, extinguish" tactics against open-source alternatives. Users of affected forks will need to find alternative C/C++ extensions or switch to the official Microsoft build to regain the lost functionality.
Hacker News users discuss the implications of Microsoft's decision to restrict the C/C++ extension in VS Code forks, primarily focusing on the potential impact on open-source projects like VSCodium. Some commenters express concern about Microsoft's motivations, viewing it as an anti-competitive move to push users towards the official Microsoft build. Others believe it's a reasonable measure to protect Microsoft's investment and control the quality of the extension's distribution. The technical aspects of how Microsoft enforces this restriction are also discussed, with some suggesting workarounds like manually installing the extension or using alternative extensions. A few users point out that the core VS Code editor remains open-source and the real issue lies in the proprietary extensions being closed off. The discussion also touches upon the broader topic of open-source sustainability and the challenges faced by projects reliant on large companies.
TacOS is a hobby operating system kernel written from scratch in C and Assembly, designed with the specific goal of running DOOM. It features a custom bootloader, memory management, keyboard driver, and a VGA driver supporting a 320x200 resolution. The kernel interfaces with a custom DOOM port, allowing the game to run directly on the bare metal without relying on any underlying operating system like DOS. This project demonstrates a minimal but functional OS capable of running a complex application, showcasing the core components required for basic system functionality.
HN commenters generally express interest in the TacOS project, praising the author's initiative and the educational value of writing a kernel from scratch. Some commend the clean code and documentation, while others offer suggestions for improvement, such as exploring different memory management strategies or implementing a proper filesystem. A few users express skepticism about the "from scratch" claim, pointing out the use of existing libraries like GRUB and the inherent reliance on hardware specifications. Overall, the comments are positive and encouraging, acknowledging the difficulty of the project and the author's accomplishment. Some users engage in deeper technical discussion about specific implementation details and offer alternative approaches.
This blog post explores different strategies for memory allocation within WebAssembly modules, particularly focusing on the trade-offs between using the built-in malloc (provided by wasm-libc) and implementing a custom allocator. It highlights the performance overhead of wasm-libc's malloc due to its generality and thread safety features. The author presents a leaner, custom bump allocator as a more performant alternative for single-threaded scenarios, showcasing its implementation and integration with a linear memory. Finally, it discusses the option of delegating allocation to JavaScript and the potential complexities involved in managing memory across the WebAssembly/JavaScript boundary.
Hacker News users discussed the implications of WebAssembly's lack of built-in allocator, focusing on the challenges and opportunities it presents. Several commenters highlighted the performance benefits of using a custom allocator tailored to the specific application, rather than relying on a general-purpose one. The discussion touched on various allocation strategies, including linear allocation, arena allocation, and using allocators from the host environment. Some users expressed concern about the added complexity for developers, while others saw it as a positive feature allowing for greater control and optimization. The possibility of standardizing certain allocator interfaces within WebAssembly was also brought up, though acknowledged as a complex undertaking. Some commenters shared their experiences with custom allocators in WebAssembly, mentioning reduced binary sizes and improved performance as key advantages.
"Less Slow C++" offers practical advice for improving C++ build and execution speed. It covers techniques ranging from precompiled headers and unity builds (combining source files) to link-time optimization (LTO) and profile-guided optimization (PGO). It also explores build system optimizations like using Ninja and parallelizing builds, and coding practices that minimize recompilation such as avoiding unnecessary header inclusions and using forward declarations. Finally, the guide touches upon utilizing tools like compiler caches (ccache) and build analysis utilities to pinpoint bottlenecks and further accelerate the development process. The focus is on readily applicable methods that can significantly improve C++ project turnaround times.
Hacker News users discussed the practicality and potential benefits of the "less_slow.cpp" guidelines. Some questioned the emphasis on micro-optimizations, arguing that focusing on algorithmic efficiency and proper data structures is generally more impactful. Others pointed out that the advice seemed tailored for very specific scenarios, like competitive programming or high-frequency trading, where every ounce of performance matters. A few commenters appreciated the compilation of optimization techniques, finding them valuable for niche situations, while some expressed concern that blindly applying these suggestions could lead to less readable and maintainable code. Several users also debated the validity of certain recommendations, like avoiding virtual functions or minimizing branching, citing potential trade-offs with code design and flexibility.
Guy Steele's "Growing a Language" advocates for designing programming languages with extensibility in mind, enabling them to evolve gracefully over time. He argues against striving for a "perfect" initial design, instead favoring a core language with powerful mechanisms for growth, akin to biological evolution. These mechanisms include higher-order functions, allowing users to effectively extend the language themselves, and a flexible syntax capable of accommodating new constructs. Steele emphasizes the importance of "bottom-up" growth, where new features emerge from practical usage and are integrated into the language organically, rather than being imposed top-down by designers. This allows the language to adapt to unforeseen needs and remain relevant as the programming landscape changes.
Hacker News users discuss Guy Steele's "Growing a Language" lecture, focusing on its relevance even decades later. Several commenters praise Steele's insights into language design, particularly his emphasis on evolving languages organically rather than rigidly adhering to initial specifications. The concept of "worse is better" is highlighted, along with a discussion of how seemingly inferior initial designs can sometimes win out due to their adaptability and ease of implementation. The challenge of backward compatibility in evolving languages is also a key theme, with commenters noting the tension between maintaining existing code and incorporating new features. Steele's humor and engaging presentation style are also appreciated. One commenter links to a video of the lecture, while others lament that more modern programming languages haven't fully embraced the principles Steele advocates.
UTL::profiler is a single-header, easy-to-use C++17 profiler that measures the execution time of code blocks. It supports nested profiling, multi-threaded applications, and custom output formats. Simply include the header, wrap the code you want to profile with UTL_PROFILE macros, and link against a high-resolution timer if needed. The profiler automatically generates a report with hierarchical timings, making it straightforward to identify performance bottlenecks. It also provides the option to programmatically access profiling data for custom analysis.
HN users generally praised the profiler's simplicity and ease of integration, particularly appreciating the single-header design. Some questioned its performance overhead compared to established profilers like Tracy, while others suggested improvements such as adding timestamp support and better documentation for multi-threaded profiling. One user highlighted its usefulness for quick profiling in situations where integrating a larger library would be impractical. There was also discussion about the potential for false sharing in multi-threaded scenarios due to the shared atomic counter, and the author responded with clarifications and potential mitigation strategies.
The blog post details the author's experience using the -fsanitize=undefined compiler flag with Picolibc, a small C library. While initially encountering numerous undefined behavior issues, particularly related to signed integer overflow and misaligned memory access, the author systematically addressed them through careful code review and debugging. This process highlighted the value of undefined behavior sanitizers in catching subtle bugs that might otherwise go unnoticed, ultimately leading to a more robust and reliable Picolibc implementation. The author demonstrates how even seemingly simple C code can harbor hidden undefined behaviors, emphasizing the importance of rigorous testing and the utility of tools like -fsanitize=undefined in ensuring code correctness.
HN users discuss the blog post's exploration of undefined behavior sanitizers. Several commend the author's clear explanation of the intricacies of undefined behavior and the utility of sanitizers like UBSan. Some users share their own experiences and tips regarding sanitizers, including the importance of using them during development and the potential performance overhead they can introduce. One commenter highlights the surprising behavior of signed integer overflow and the challenges it presents for developers. Others point out the value of sanitizers, particularly in embedded and safety-critical systems. The small size and portability of Picolibc are also noted favorably in the context of using sanitizers. A few users express a general appreciation for the blog post's educational value and the author's engaging writing style.
GCC 15 introduces several usability enhancements. Improved diagnostics offer more concise and helpful error messages, including location information within macros and clearer explanations for common mistakes. The new -fanalyzer option provides static analysis capabilities to detect potential issues like double-free errors and use-after-free vulnerabilities. Link-time optimization (LTO) is more robust with improved diagnostics, and the compiler can now generate more efficient code for specific targets like Arm and x86. Additionally, improved support for C++20 and C2x features simplifies development with modern language standards. Finally, built-in functions for common mathematical operations have been optimized, potentially improving performance without requiring code changes.
Hacker News users generally expressed appreciation for the continued usability improvements in GCC. Several commenters highlighted the value of the improved diagnostics, particularly the location information and suggestions, making debugging significantly easier. Some discussed the importance of such advancements for both novice and experienced programmers. One commenter noted the surprisingly rapid adoption of these improvements in Fedora's GCC packages. Others touched on broader topics like the challenges of maintaining large codebases and the benefits of static analysis tools. A few users shared personal anecdotes of wrestling with confusing GCC error messages in the past, emphasizing the positive impact of these changes.
The Haiku-OS.org post "Learning to Program with Haiku" provides a comprehensive starting point for aspiring Haiku developers. It highlights the simplicity and power of the Haiku API for creating GUI applications, using the native C++ framework and readily available examples. The guide emphasizes practical learning through modifying existing code and exploring the extensive documentation and example projects provided within the Haiku source code. It also points to resources like the Be Book (covering the BeOS API, which Haiku largely inherits), mailing lists, and the IRC channel for community support. The post ultimately encourages exploration and experimentation as the most effective way to learn Haiku development, positioning it as an accessible and rewarding platform for both beginners and experienced programmers.
Commenters on Hacker News largely expressed nostalgia and fondness for Haiku OS, praising its clean design and the tutorial's approachable nature for beginners. Some recalled their positive experiences with BeOS and appreciated Haiku's continuation of its legacy. Several users highlighted Haiku's suitability for older hardware and embedded systems. A few comments delved into technical aspects, discussing the merits of Haiku's API and its potential as a development platform. One commenter noted the tutorial's focus on GUI programming as a smart move to showcase Haiku's strengths. The overall sentiment was positive, with many expressing interest in revisiting or trying Haiku based on the tutorial.
This project introduces "SHORTY," a C++ utility that aims to make lambdas more concise. It achieves this by providing a macro-based system that replaces standard lambda syntax with a shorter, more symbolic representation. Essentially, SHORTY allows developers to define and use lambdas with fewer characters, potentially improving code readability in some cases by reducing boilerplate. However, this comes at the cost of relying on macros and introducing a new syntax that deviates from standard C++. The project documentation argues that the benefits in brevity outweigh the costs for certain use cases.
HN users largely discussed the potential downsides of Shorty, a C++ library for terser lambdas. Concerns included readability and maintainability suffering due to excessive brevity, especially for those unfamiliar with the library. Some argued against introducing more cryptic syntax to C++, preferring explicitness over extreme conciseness. Others questioned the practical benefits, suggesting existing lambda syntax is sufficient and the library's complexity outweighs its advantages. A few commenters expressed mild interest, acknowledging the potential for niche use cases but emphasizing the importance of careful consideration before widespread adoption. Several also debated the library's naming conventions and overall design choices.
PlanetScale's Vitess project, which uses a Go-based MySQL interpreter, historically lagged behind C++ in performance. Through focused optimization efforts targeting function call overhead, memory allocation, and string conversion, they significantly improved Vitess's speed. By leveraging Go's built-in profiling tools and making targeted changes like using custom map implementations and byte buffers, they achieved performance comparable to, and in some cases exceeding, a similar C++ interpreter. These improvements demonstrate that with careful optimization, Go can be a competitive choice for performance-sensitive applications like database interpreters.
Hacker News users discussed the benchmarks presented in the PlanetScale blog post, expressing skepticism about their real-world applicability. Several commenters pointed out that the microbenchmarks might not reflect typical database workload performance, and questioned the choice of C++ implementation used for comparison. Some suggested that the Go interpreter's performance improvements, while impressive, might not translate to significant gains in a production environment. Others highlighted the importance of considering factors beyond raw execution speed, such as memory usage and garbage collection overhead. The lack of details about the specific benchmarks and the C++ implementation used made it difficult for some to fully assess the validity of the claims. A few commenters praised the progress Go has made, but emphasized the need for more comprehensive and realistic benchmarks to accurately compare interpreter performance.
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https://news.ycombinator.com/item?id=44142472
Hacker News users discussed potential downsides of using
-ffast-math, even beyond the documented changes to IEEE compliance. One commenter highlighted the risk of silent changes in code behavior across compiler versions or optimization levels, making debugging difficult. Another pointed out that using-ffast-mathcan lead to unexpected issues with code that relies on specific floating-point behavior, such as comparisons or NaN handling. Some suggested that the performance gains are often small and not worth the risks, especially given the potential for subtle, hard-to-track bugs. The consensus seemed to be that-ffast-mathshould be used cautiously and only when its impact is thoroughly understood and tested, with a preference for more targeted optimizations where possible. A few users mentioned specific instances where-ffast-mathcaused problems in real-world projects, further reinforcing the need for careful consideration.The Hacker News post "Beware of Fast-Math" (https://news.ycombinator.com/item?id=44142472) has generated a robust discussion around the trade-offs between speed and accuracy when using the "-ffast-math" compiler optimization flag. Several commenters delve into the nuances of when this optimization is acceptable and when it's dangerous.
One of the most compelling threads starts with a commenter highlighting the importance of understanding the specific mathematical properties being relied upon in a given piece of code. They emphasize that "-ffast-math" can break assumptions about associativity and distributivity, leading to unexpected results. This leads to a discussion about the importance of careful testing and profiling to ensure that the optimization doesn't introduce subtle bugs. Another commenter chimes in to suggest that using stricter floating-point settings during development and then selectively enabling "-ffast-math" in performance-critical sections after thorough testing can be a good strategy.
Another noteworthy comment chain focuses on the implications for different fields. One commenter mentions that in game development, where performance is often paramount and small inaccuracies in physics calculations are generally acceptable, "-ffast-math" can be a valuable tool. However, another commenter counters this by pointing out that even in games, seemingly minor errors can accumulate and lead to noticeable glitches or exploits. They suggest that developers should carefully consider the potential consequences before enabling the optimization.
Several commenters share personal anecdotes about encountering issues related to "-ffast-math." One recounts a debugging nightmare caused by the optimization silently changing the behavior of their code. This reinforces the general sentiment that while the performance gains can be tempting, the potential for hidden bugs makes it crucial to proceed with caution.
The discussion also touches on alternatives to "-ffast-math." Some commenters suggest exploring other optimization techniques, such as using SIMD instructions or writing optimized code for specific hardware, before resorting to a compiler flag that can have such unpredictable side effects.
Finally, a few commenters highlight the importance of compiler-specific documentation. They point out that the exact behavior of "-ffast-math" can vary between compilers, further emphasizing the need for careful testing and understanding the specific implications for the chosen compiler.
In summary, the comments on the Hacker News post paint a nuanced picture of the "-ffast-math" optimization. While acknowledging the potential for performance improvements, the overall consensus is that it should be used judiciously and with a thorough understanding of its potential pitfalls. The commenters emphasize the importance of testing, profiling, and considering alternative optimization strategies before enabling this potentially problematic flag.