GPU Last-Active Thread Selection for Parallel Sub-Wave Operations
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Solution Overview
Problem
Existing graphics processing technologies face inefficiencies in performing sub-wave operations, leading to increased time and power consumption at graphics processing units (GPUs), particularly in handling wave and sub-wave operations in a serial manner.
Innovation Solution
A mechanism is introduced to identify and select a representative thread from each sub-wave, allowing parallel execution of wave and sub-wave operations, thereby reducing the load on GPUs by activating only the last active thread and performing atomic operations efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If sub-wave operations are performed in a serial manner, then thread activation is simple, but time consumption and power consumption increase
Solution Approach 1:
The wave is divided into multiple sub-waves, each containing a subset of threads. By segmenting the wave into smaller units, the system can activate threads in parallel across different sub-waves rather than sequentially, reducing total execution time and power consumption while maintaining simplified thread activation logic within each segment.
Solution Approach 2:
The system dynamically activates only the last active thread from each sub-wave after performing operations, rather than activating all threads. This dynamic approach optimizes power consumption by keeping fewer threads active while maintaining the ability to process all sub-wave operations efficiently through parallel execution.
2Productivity
If all threads in a sub-wave are activated, then operations can be performed, but time consumption increases due to serial execution
Solution Approach 1:
By dividing the wave into multiple sub-waves, the system enables parallel execution of operations across different sub-waves. Each sub-wave can be processed independently, allowing simultaneous operation execution that reduces total execution time while maintaining comprehensive thread activation where needed.
Solution Approach 2:
Instead of activating all threads in a wave, the system activates only the necessary last active thread from each sub-wave. This partial activation approach reduces execution time by avoiding redundant thread activation while ensuring all required operations are performed through the coordinated action of activated threads.
3Use of energy by stationary object
If threads are inactivated after operations, then power consumption reduces, but complexity of thread management increases
Solution Approach 1:
The system automatically identifies and activates only the last active thread from each sub-wave without requiring manual thread management. The threading mechanism self-manages activation and inactivation based on operation requirements, reducing power consumption while minimizing management complexity through automated last-thread selection and activation logic.
Data Source
AI summary
Aspects presented herein relate to methods and devices for graphics processing including an apparatus, e.g., a GPU. The apparatus may allocate a wave into a set of sub-waves, where each sub-wave in the set of sub-waves comprises a set of threads. The apparatus may also perform a set of wave operations for each sub-wave in the set of sub-waves. Further, the apparatus may identify, based on the set of wave operations, a last active thread from amongst the set of threads for each sub-wave in the set of sub-waves.