News from AMD GPUOpen

Our generative AI research leverages diffusion-based techniques to generate indirect illumination effects for the new era of neural rendering.

This article is a quick how-to guide for using the WMMA intrinsics with our new AMD RDNA™ 4 architecture GPUs.

Join Alexander Cann, Lead Developer at Schola, and Mehdi Saeedi, AI Lead at Schola, as they take you through the fascinating world of reinforcement learning (RL) and its transformative impact on gaming. They’ll be joined by Gabor Sines, Sr. Fellow Engineer at AMD, as moderator.

With version 1.5 of AMD Radeon™ GPU Detective (RGD) you can now use the debug information that is produced by the Microsoft DirectX® Shader Compiler.

We've released an updated AMD Radeon™ Developer Tool Suite, including enhanced versions of tools such as the Radeon GPU Detective, Profiler, Raytracing Analyzer, Memory Visualizer, GPU Analyzer, and Developer Panel, now with expanded GPU support.

Explore how Neural Intersection Functions (NIF) and the enhanced LSNIF are poised to reshape ray tracing by replacing traditional BVH traversal with efficient, GPU-friendly neural networks for accelerated performance and high-fidelity imagery.

Discover a high-performance, memory-efficient extension to Onesweep radix sort on GPUs, featuring circular buffers and advanced optimization techniques that reduce global memory access and improve sorting throughput.

A new algebraic method for hardware-accelerated bilinear interpolation on convex quadrilaterals is presented, using the Barycentric coordinate feature of modern GPUs.

Optimize CPU performance by manually writing x64 assembly code, offering a detailed comparison with compiler-generated instructions and achieving improved performance through streamlined instruction sets.

We look at optimizing CPU performance by reducing the number of instructions, and highlights methods to enhance instruction efficiency and algorithm throughput.