The Blend2D project developed a new high-performance PNG decoder, significantly outperforming existing libraries like libpng, stb_image, and lodepng. This achievement stems from a focus on low-level optimizations, including SIMD vectorization, optimized Huffman decoding, prefetching, and careful memory management. These improvements were integrated directly into Blend2D's image pipeline, further boosting performance by eliminating intermediate copies and format conversions when loading PNGs for rendering. The decoder is designed to be robust, handling invalid inputs gracefully, and emphasizes correctness and standard compliance alongside speed.
Driven by a desire to understand how Photoshop worked under the hood, the author embarked on a personal project to recreate core functionalities in C++. Focusing on fundamental image manipulation like layers, blending modes, filters (blur, sharpen), and transformations, they built a simplified version without aiming for feature parity. This exercise provided valuable insights into image processing algorithms and the complexities of software development, highlighting the importance of optimization for performance, especially when dealing with large images and complex operations. The project, while not a full Photoshop replacement, served as a profound learning experience.
Hacker News users generally praised the author's project, "Recreating Photoshop in C++," for its ambition and educational value. Some questioned the practical use of such an undertaking, given the existence of Photoshop and other mature image editors. Several commenters pointed out the difficulty in replicating Photoshop's full feature set, particularly the more advanced tools. Others discussed the choice of C++ and suggested alternative languages or libraries that might be more suitable for certain aspects of image processing. The author's focus on performance optimization and leveraging SIMD instructions also sparked discussion around efficient image manipulation techniques. A few comments highlighted the importance of UI/UX design, often overlooked in such projects, for a truly "Photoshop-like" experience. A recurring theme was the project's value as a learning exercise, even if it wouldn't replace existing professional tools.
Dithering is a technique used to create the illusion of more colors and smoother gradients in images with a limited color palette. The post "Dithering in Colour" explores various dithering algorithms, focusing on how they function with color images. It explains ordered dithering using matrices like the Bayer matrix, and error-diffusion dithering methods such as Floyd-Steinberg, which distribute quantization errors to neighboring pixels. The post visually demonstrates the effects of these algorithms with examples, highlighting the trade-offs between different methods in terms of perceived noise and color accuracy. It concludes by mentioning how dithering remains relevant today for stylistic effects and performance optimization, even with modern displays capable of displaying millions of colors.
HN users generally praised the article for its clear explanation of dithering, particularly its interactive visualizations. Several commenters shared their experiences with dithering, including its use in older games and demos. Some discussed the subtle differences between various dithering algorithms, while others highlighted the continued relevance of these techniques in resource-constrained environments or for stylistic effect. One commenter pointed out a typo in the article, which the author promptly corrected. A few users mentioned alternative resources on the topic, including a related blog post and a book.
This post introduces rotors as a practical alternative to quaternions and matrices for 3D rotations. It explains that rotors, like quaternions, represent rotations as a single action around an arbitrary axis, but offer a simpler, more intuitive geometric interpretation based on the concept of "geometric algebra." The author argues that rotors are easier to understand and implement, visually demonstrating their geometric meaning and providing clear code examples in Python. The post covers basic rotor operations like creating rotations from an axis and angle, composing rotations, and applying rotations to vectors, highlighting rotors' computational efficiency and stability.
Hacker News users discussed the practicality and intuitiveness of using rotors for 3D rotations. Some found the rotor approach more elegant and easier to grasp than quaternions, especially appreciating the clear geometric interpretation and connection to bivectors. Others questioned the claimed advantages, arguing that quaternions remain the superior choice for performance and established library support. The potential benefits of rotors in areas like interpolation and avoiding gimbal lock were acknowledged, but some commenters felt the article didn't fully demonstrate these advantages convincingly. A few requested more comparative benchmarks or examples showcasing rotors' practical superiority in specific scenarios. The lack of widespread adoption and existing tooling for rotors was also raised as a barrier to entry.
Using mix() with step() to simulate conditional assignments in shaders is often less efficient than directly using branch instructions. While seemingly branchless, this mix()/step() approach can introduce extra computations and potentially disrupt hardware optimizations related to predication. Modern GPUs are adept at handling branches efficiently, especially when they are predictable, so relying on them is often faster and simpler than employing arithmetic workarounds. Therefore, default to standard branching unless profiling reveals a specific performance bottleneck that can be demonstrably addressed by a mix()/step() alternative.
HN users generally agreed that the article's advice is sound, particularly for modern GPUs. Several pointed out that mix() and step() can be more efficient than branching, especially when dealing with SIMD architectures where branching can lead to thread divergence. Some emphasized that profiling is crucial, as the optimal approach can vary depending on the specific GPU and shader complexity. One commenter noted that while branching might be faster in simple cases, mix() offers more predictable performance as shader complexity increases. Another cautioned against premature optimization and recommended focusing on algorithmic improvements first. A few users shared alternative techniques like using lookup textures or bitwise operations for certain conditional scenarios. Finally, there was discussion about the evolution of GPU architecture and how older advice regarding branching might no longer apply.
This blog post details a method for realistically simulating shallow water flow over terrain. The author utilizes a heightmap to represent the terrain and employs a simplified shallow water equations model to govern water movement. This model calculates water height and velocity, accounting for factors like terrain slope and gravity. The simulation iteratively updates the water's state using numerical integration, allowing for dynamic changes in water distribution and flow patterns based on the underlying terrain. Visualization is achieved through a simple rendering technique that adjusts terrain color based on water depth, creating a visually convincing representation of shallow water flowing over varied terrain.
Commenters on Hacker News largely praised the clarity and educational value of the blog post on simulating water over terrain. Several appreciated the author's focus on intuitive explanation and avoidance of overly complex mathematics, making the topic accessible to a wider audience. Some pointed out the limitations of the shallow water equations used, particularly regarding their inability to model breaking waves, while others suggested alternative approaches or resources for further exploration, such as smoothed-particle hydrodynamics (SPH) and the book "Fluid Simulation for Computer Graphics." A few commenters also shared their own experiences and projects related to fluid simulation. Overall, the discussion was positive and focused on the technical aspects of the simulation.
The Graphics Codex is a comprehensive, free online resource for learning about computer graphics. It covers a broad range of topics, from fundamental concepts like color and light to advanced rendering techniques like ray tracing and path tracing. Emphasizing a practical, math-heavy approach, the Codex provides detailed explanations, interactive diagrams, and code examples to facilitate a deep understanding of the underlying principles. It's designed to be accessible to students and professionals alike, offering a structured learning path from beginner to expert levels. The resource continues to evolve and expand, aiming to become a definitive and up-to-date guide to the field of computer graphics.
Hacker News users largely praised the Graphics Codex, calling it a "fantastic resource" and a "great intro to graphics". Many appreciated its practical, hands-on approach and clear explanations of fundamental concepts, contrasting it favorably with overly theoretical or outdated textbooks. Several commenters highlighted the value of its accompanying code examples and the author's focus on modern graphics techniques. Some discussion revolved around the choice of GLSL over other shading languages, with some preferring a more platform-agnostic approach, but acknowledging the educational benefits of GLSL's explicit nature. The overall sentiment was highly positive, with many expressing excitement about using the resource themselves or recommending it to others.
This blog post breaks down the "Tiny Clouds" Shadertoy by iq, explaining its surprisingly simple yet effective cloud rendering technique. The shader uses raymarching through a 3D noise function, but instead of directly visualizing density, it calculates the amount of light scattered backwards towards the viewer. This is achieved by accumulating the density along the ray and weighting it based on the distance traveled, effectively simulating how light scatters more in denser areas. The post further analyzes the specific noise function used, which combines several octaves of Simplex noise for detail, and discusses how the scattering calculations create a sense of depth and illumination. Finally, it offers variations and potential improvements, such as adding lighting controls and exploring different noise functions.
Commenters on Hacker News largely praised the "Tiny Clouds" shader's elegance and efficiency, admiring the author's ability to create such a visually appealing effect with minimal code. Several discussed the clever use of trigonometric functions and noise to generate the cloud shapes, and some delved into the specifics of raymarching and signed distance fields. A few users shared their own experiences experimenting with similar techniques, and offered suggestions for further exploration, like adding lighting variations or animation. One commenter linked to a related Shadertoy example showcasing a different approach to cloud rendering, prompting a brief comparison of the two methods. Overall, the discussion highlighted the technical ingenuity behind the shader and fostered a sense of appreciation for its concise yet powerful implementation.
Someone has rendered the entirety of the original Doom (1993) game, including all levels, enemies, items, and even the intermission screens, as individual images within a 460MB PDF file. This allows for a static, non-interactive experience of browsing through the game's visuals like a digital museum exhibit. The PDF acts as a unique form of archiving and presenting the game's assets, essentially turning the classic FPS into a flipbook.
Hacker News users generally expressed amusement and appreciation for the novelty of rendering Doom as a PDF. Several commenters questioned the practicality, but acknowledged the technical achievement. Some discussed the technical aspects, wondering how it was accomplished and speculating about the use of vector graphics and custom fonts. Others shared similar projects, like rendering Quake in HTML. A few users pointed out potential issues, such as the large file size and the lack of interactivity, while others jokingly suggested printing it out. Overall, the sentiment was positive, with commenters finding the project a fun and interesting hack.
Summary of Comments ( 4 )
https://news.ycombinator.com/item?id=43451187
HN commenters generally praise Blend2D's PNG decoder for its speed and clean implementation. Some appreciate the detailed blog post explaining its design and optimization strategies, highlighting the clever use of SIMD intrinsics and the decision to avoid complex dependencies. One commenter notes the impressive performance compared to LodePNG, particularly for large images. Others discuss potential further optimizations, such as using pre-calculated tables for faster filtering, and the challenges of achieving peak performance with varying image characteristics and hardware platforms. A few users also share their experiences integrating or considering Blend2D in their projects.
The Hacker News post titled "High-Performance PNG Decoding" discussing the blog post about Blend2D's new PNG codec has a moderate number of comments, sparking a discussion around performance, specific implementation details, and comparisons to other libraries.
Several commenters express admiration for the author's deep dive into optimization and the impressive performance results achieved. One commenter notes the impressive speeds, especially for the palette and grayscale formats, questioning whether further optimization is even possible or necessary. Another commends the author's dedication to thoroughly explaining their optimization process and the challenges they encountered. The detailed explanations are appreciated by other commenters as well, as they provide insight into the complexities of image decoding and the nuances of performance tuning.
A thread emerges around the use of SIMD instructions and the potential for further optimization using AVX-512. Commenters discuss the trade-offs involved in using these advanced instruction sets, considering factors like CPU compatibility and potential power consumption increases. The author of the Blend2D library chimes in to explain their reasoning for not fully utilizing AVX-512 yet, citing compilation complexities and limited practical benefits in their current implementation.
Comparisons to other popular image decoding libraries like libpng and stb_image are also made. Commenters discuss the performance differences, highlighting Blend2D's competitive edge in certain scenarios. The simplicity and ease of integration of stb_image are acknowledged, while Blend2D is praised for its focus on performance.
Finally, some comments delve into specific technical details, such as the use of premultiplied alpha and the handling of different bit depths. These comments demonstrate a deeper understanding of the technical aspects of image processing and offer specific suggestions or raise questions about the implementation choices made in Blend2D. One commenter questions the usage of premultiplied alpha by default.
Overall, the comments section reveals a general appreciation for the author's work and the performance achieved by Blend2D. The discussion offers valuable insights into the technical challenges and trade-offs involved in optimizing image decoding libraries, along with comparisons to existing solutions.