Compute Unit Sorting for Reduced SIMD Control Flow Divergence
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Solution Overview
Problem
Single-instruction multiple-data (SIMD) processors experience a slowdown due to divergent control flow, where different execution paths are serialized, leading to inefficiencies in parallel processing.
Innovation Solution
Reorganize execution items across wavefronts or within a wavefront by identifying control flow targets and sorting execution items based on these targets, reducing divergence through techniques such as inter-wavefront and intra-wavefront reorganization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If execution items are processed in parallel using SIMD architecture, then processing throughput is improved, but control flow divergence causes serialization and reduces efficiency
Solution Approach 1:
The patent applies preliminary action by sorting execution items before they reach the divergent control flow point. The sorting operation is performed in advance based on control flow targets, so that when execution items encounter the branch, they are already grouped by their destination. This preliminary organization prevents the need for runtime serialization, allowing all execution items to proceed through the divergent path simultaneously without losing parallelism.
Solution Approach 2:
The patent segments execution items into different groups based on their control flow targets. By dividing the execution items into segments that correspond to different branch destinations, the system can process each segment independently through the appropriate control flow path. This segmentation allows the SIMD processor to maintain parallel execution within each segment while handling multiple control flow paths, thereby reducing the serialization overhead that would occur if all items were processed sequentially through the divergence point.
2Productivity
If execution items with different control flow targets are grouped together in a wavefront, then wavefront utilization is improved, but control flow divergence increases and reduces parallel processing efficiency
Solution Approach 1:
The patent applies local quality by creating heterogeneous wavefronts where execution items are selectively grouped based on their control flow targets rather than using uniform grouping. Each wavefront is tailored with a specific composition of execution items that share common control flow characteristics, allowing the system to optimize for both wavefront utilization and reduced divergence. This local customization of wavefront composition enables better parallel processing efficiency while managing control flow complexity through targeted grouping strategies.
Data Source
AI summary
Described herein are techniques for reducing divergence of control flow in a single-instruction-multiple-data processor. The method includes, at a point of divergent control flow, identifying control flow targets for different execution items, sorting the execution items based on the control flow targets, reorganizing the execution items based on the sorting, and executing after the point of divergent control flow, with the reorganized execution items.