Wavefront Sorting Control for SIMD Divergence Reduction
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Solution Overview
Problem
Divergent control flow in parallel processors such as SIMD and SIMT processors leads to underutilization of hardware resources and increased execution time due to sequential execution of instructions, which is common in applications like graphics processing, scientific computing, and machine learning.
Innovation Solution
A technique is employed to reduce divergence by sorting work-items into bins based on a sort parameter, pausing wavefront execution when divergence occurs, and querying the status of the sorting operation to determine subsequent actions, including waiting for sorted work-items or triggering a flush operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If work-items are executed in parallel wavefronts on SIMD/SIMT processors, then computational throughput is improved, but divergent control flow causes sequential execution that reduces hardware utilization efficiency
Solution Approach 1:
The patent segments wavefronts into multiple sorted wavefronts based on control flow divergence characteristics. Work-items with similar control flow paths are grouped together in separate sorted wavefronts, allowing each sorted wavefront to execute efficiently in parallel without divergence-induced sequentialization. This segmentation resolves the contradiction by maintaining parallel execution efficiency while accommodating divergent control flow patterns.
Solution Approach 2:
The patent dynamically sorts and reorganizes wavefronts at runtime based on actual control flow divergence patterns observed during execution. The sorting mechanism adapts to the specific divergence characteristics of each computational region, creating optimized execution schedules that maximize parallel hardware utilization. This dynamic approach allows the system to maintain high productivity while efficiently handling varying degrees of control flow divergence.
2Device complexity
If work-items are sorted into bins based on control flow parameters, then divergence is reduced and hardware utilization improves, but additional sorting operations increase execution time
Solution Approach 1:
The patent performs preliminary sorting of wavefronts at the beginning of computational regions where control flow divergence is anticipated. By pre-organizing work-items into sorted wavefronts before execution, the system eliminates the need for runtime sorting operations that would otherwise cause execution delays. This preliminary action reduces overall execution time while maintaining improved hardware utilization efficiency.
Solution Approach 2:
The patent implements self-sorting mechanisms where wavefronts automatically identify and organize themselves based on control flow characteristics without requiring external sorting operations. The work-items within wavefronts use their own control flow information to determine their sorted position, eliminating the overhead of external sorting while achieving the same divergence-reduction effect.
3Productivity
If sorted wavefronts are used to handle divergent control flow, then execution efficiency improves, but increased control logic complexity is introduced
Solution Approach 1:
The patent introduces a sorting buffer as an intermediary data structure that facilitates the transition from unsorted to sorted wavefronts. This buffer acts as a mediator that organizes work-items based on control flow parameters without requiring complex control logic in the execution paths. The sorting buffer handles the complexity of wavefront reorganization, allowing the execution logic to remain simple while achieving improved execution efficiency.
Solution Approach 2:
The patent changes the parameter organization of wavefronts from unsorted to sorted based on control flow characteristics. By transforming the organizational parameter of wavefronts (from arbitrary ordering to control-flow-based ordering), the system achieves improved execution efficiency without fundamentally changing the control logic. The parameter change approach maintains simple control flow while optimizing the structural organization of executing work-items.
Data Source
AI summary
A technique is disclosed for reducing divergence among a plurality of executing wavefronts. A first wavefront requests that work-items of the first wavefront be sorted based on a sort parameter together with work-items of one or more other wavefronts, and the first wavefront is requested to pause execution. A query is issued for a status of the request, and a query result is provided to the first wavefront. Based on the query result, the first wavefront determines a subsequent action.