How Does libaom Multi-Threading Work?

The libaom encoder maximizes CPU performance and accelerates the computationally intensive AV1 video encoding process through a multi-tiered parallel execution model. By combining tile-based, row-based, and frame-parallel processing techniques, libaom splits video data into independently manageable chunks that can be computed simultaneously across multiple CPU cores. While AV1 encoding is notoriously heavy due to its deep partition trees and advanced coding tools, understanding how libaom utilizes these distinct multi-threading layers allows developers to efficiently scale hardware usage without significantly compromising compression efficiency.

Tile-Based Parallelism

The foundational layer of multi-threading in libaom relies on video tiles. The AV1 specification allows a single video frame to be divided into a grid of independent rectangular regions called tiles.

• Independent Coding: Each tile contains its own loop-filtering boundaries and entropy coding contexts, meaning a thread can process a tile completely isolated from adjacent regions.
• Hardware Scaling: By configuring parameters such as tile columns and tile rows, users define the maximum number of structural threads that can execute concurrently at the frame level.
• Efficiency Trade-off: While tiles provide excellent multi-threaded scaling, they limit the encoder’s ability to reference pixel data across tile boundaries, which can cause a minor penalty in overall compression efficiency.

Row-Based Multi-Threading (Row-MT)

To overcome the scaling limits and efficiency penalties of relying purely on massive tile grids, libaom features Row-Based Multi-Threading. When activated, Row-MT introduces a wavefront processing mechanism within the tiles or across the frame.

Instead of waiting for an entire tile to finish, a secondary thread can begin encoding the subsequent row of blocks as soon as the leading thread has cleared a specific horizontal offset. This dependency tracking ensures that spatial intra-prediction vectors from the top and top-right blocks are already computed and available. Row-MT significantly improves CPU utilization on high-core-count processors, even when using a low number of tiles.

Frame-Parallel Multi-Threading

At the highest level of its parallel architecture, libaom implements frame-parallel multithreading. This technique enables the encoder to analyze and process multiple video frames in the lookahead buffer and encoding pipeline simultaneously.

Because video frames inherently depend on temporal references (such as golden frames or alternative reference frames), libaom coordinates inter-frame dependencies via internal threading controls. Threads working on non-reference frames or frames within the same hierarchical layer of a Group of Pictures (GOP) can run asynchronously, heavily reducing the total time required to process sequential video streams.