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.
Hexi is a new, header-only C++ library for network binary serialization. It focuses on modern C++ features, aiming for ease of use, safety, and performance. Hexi supports user-defined types, standard containers, and common data structures out-of-the-box, minimizing boilerplate. It leverages compile-time reflection and constexpr processing to achieve efficiency comparable to hand-written serialization code, while providing a more concise and maintainable solution.
HN commenters generally praised Hexi for its simplicity and ease of use, particularly its header-only nature and intuitive syntax. Some compared it favorably to other serialization libraries like Protobuf and Cap'n Proto, highlighting its potential for better performance in certain scenarios due to its zero-copy deserialization. Concerns were raised about potential compile-time impact due to the header-only design and the lack of documentation beyond basic examples. One commenter suggested incorporating compile-time reflection to further enhance the library's capabilities and reduce boilerplate. Others questioned the long-term viability of the project, expressing a desire to see more real-world use cases and benchmarking data. The lack of support for optional fields was also mentioned as a potential drawback.
cute_headers is a curated collection of single-header C/C++ libraries, specifically geared towards game development. These libraries are designed to be easily integrated, requiring no external dependencies or build systems. They cover a range of functionalities often needed in games, including linear algebra, collision detection, graphics, input handling, and more. The project aims to provide a convenient and lightweight way to access commonly used tools without the overhead of complex library management. This makes them particularly suitable for small projects, rapid prototyping, or learning purposes.
Hacker News users generally praised the simplicity and utility of Randy Gaul's single-file libraries. Several commenters highlighted the educational value of the code, particularly for understanding fundamental game development concepts and data structures. Some discussed the trade-offs of using such minimal libraries versus larger, more feature-rich alternatives, acknowledging the benefits of these smaller libraries for learning and small projects while recognizing potential limitations for complex endeavors. A few commenters also mentioned specific libraries they found particularly interesting or useful, including the string library and the JSON parser. There was a short thread discussing licensing, ultimately confirming that the MIT license allows for commercial use.
TinyZero is a lightweight, header-only C++ reinforcement learning (RL) library designed for ease of use and educational purposes. It focuses on implementing core RL algorithms like Proximal Policy Optimization (PPO), Deep Q-Network (DQN), and Advantage Actor-Critic (A2C), prioritizing clarity and simplicity over extensive features. The library leverages Eigen for linear algebra and aims to provide a readily understandable implementation for those learning about or experimenting with RL algorithms. It supports both CPU and GPU execution via optional CUDA integration and includes example environments like CartPole and Pong.
Hacker News users discussed TinyZero's impressive training speed and small model size, praising its accessibility for hobbyists and researchers with limited resources. Some questioned the benchmark comparisons, wanting more details on hardware and training methodology to ensure a fair assessment against AlphaZero. Others expressed interest in potential applications beyond Go, such as chess or shogi, and the possibility of integrating techniques from other strong Go AIs like KataGo. The project's clear code and documentation were also commended, making it easy to understand and experiment with. Several commenters shared their own experiences running TinyZero, highlighting its surprisingly good performance despite its simplicity.
Summary of Comments ( 3 )
https://news.ycombinator.com/item?id=43680477
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 Hacker News post titled "Show HN: Single-Header Profiler for C++17" has generated several comments discussing the linked single-header profiler. Here's a summary:
Ease of Use and Integration: Many commenters praised the simplicity and ease of integration of the profiler, emphasizing the advantage of it being a single header file. This makes it easy to drop into existing projects without complex build system modifications. Some appreciated the minimal setup required, contrasting it with more complex profiling tools.
Chrome Tracing Support: The integration with Chrome's tracing tools was a highlight for several users. They saw the ability to visualize the profiling data in Chrome's trace viewer as a significant benefit, offering a familiar and powerful interface for analysis.
Overhead Concerns: A few commenters raised concerns about the potential performance overhead introduced by the profiler. While acknowledging its usefulness for quick profiling, they cautioned against using it in performance-sensitive production code. One commenter specifically asked about the overhead, but there wasn't a definitive answer provided in the thread.
Comparison with Existing Profilers: The profiler was compared to other existing profiling tools like Tracy and Instruments. Some users expressed a preference for the simplicity of this single-header solution over more complex alternatives, while others highlighted the advanced features offered by established profilers. One commenter specifically mentioned finding Tracy superior.
Specific Feature Requests and Suggestions: There were specific suggestions for improvements, such as adding support for custom allocators and the ability to disable instrumentation for certain functions or scopes. Another commenter requested more documentation and examples.
Appreciation for the Project: Overall, the comments expressed appreciation for the project, recognizing its value as a quick and easy-to-use profiling tool. Several users indicated their intention to try it out in their own projects.
Lack of Extensive Discussion on Accuracy: While performance overhead was discussed, there wasn't a significant discussion about the accuracy of the profiler's measurements.
In summary, the comments on Hacker News generally viewed the single-header profiler positively, praising its simplicity and ease of use, particularly the Chrome tracing integration. However, some concerns were raised regarding potential overhead and comparisons were made to other existing profiling solutions. The thread also contained specific requests for features and improvements.