FFmpeg developers have implemented a handwritten AVX-512 assembly code path, resulting in a significant performance boost of up to 94 times for specific functions within the multimedia processing library.
This optimisation leverages the parallel processing capabilities of AVX-512, enabling faster processing of large chunks of data, particularly beneficial for video and image processing.
While this development is advantageous for users with AVX-512-capable hardware, it's worth noting that Intel has disabled AVX-512 support on its recent Core processors.
Fortunately, the AMD users are in luck. AMD's Ryzen 9000-series CPUs feature a fully enabled AVX-512 FPU, allowing these users to benefit from the FFmpeg improvement.
This achievement shows the potential of hand-optimized assembly code for enhancing performance, especially in performance-critical applications.
Handwritten Assembly Code Delivers Huge Performance Boost for FFmpeg
FFmpeg developers have achieved a remarkable performance improvement of up to 94x by implementing handwritten AVX-512 assembly code.
While high-level programming languages and compilers simplify software development, they sometimes fail to fully exploit modern hardware capabilities. The FFmpeg developers tackled this issue by directly utilizing the AVX-512 instruction set, a feature often overlooked even by seasoned programmers.
AVX-512 allows for parallel processing of large data chunks using 512-bit registers. This makes it particularly well-suited for computationally demanding tasks like video and image processing. The results of their efforts were astounding, with the new code path outperforming standard implementations by a factor of 3 to 94.
This optimization is especially beneficial for users with AVX-512-capable hardware, such as AMD's Ryzen 9000-series CPUs. Unfortunately, Intel has disabled AVX-512 support in its recent Core processor generations.
However, the complexity of AVX-512 means that such optimizations are generally limited to specific applications and require specialized knowledge of low-level programming.
