Graphics Discard Engine for Memory Bandwidth Optimization
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Solution Overview
Problem
In graphics processing pipelines, there is a challenge in efficiently managing and deallocating attribute data as it is consumed by pixel shaders, leading to potential memory inefficiencies and increased bandwidth usage.
Innovation Solution
A discard engine is introduced to gather deallocation messages from multiple pixel shaders and determine when attribute data is no longer needed, sending discard commands to caches to invalidate the data and prevent writebacks to memory.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If attribute data is kept in cache for extended periods to ensure data availability for pixel shaders, then data access reliability is improved, but memory bandwidth usage increases due to preventable writebacks
Solution Approach 1:
The discard engine implements a feedback mechanism by monitoring the consumption status of attribute data across multiple pixel shaders. When all shaders have consumed the data, the system sends discard commands to invalidate the cache entries, preventing unnecessary writebacks. This feedback loop ensures data is retained only as long as needed, optimizing the balance between reliability and bandwidth usage.
Solution Approach 2:
The system applies the discard and recover principle by systematically invalidating cache entries for attribute data that has been fully consumed by all pixel shaders. The discard engine tracks consumption status and selectively discards completed data blocks, recovering memory bandwidth that would otherwise be wasted on writing back unnecessary data to memory.
2Loss of energy
If a discard engine is implemented to track and invalidate attribute data, then memory bandwidth usage is reduced, but device complexity increases
Solution Approach 1:
The discard engine is designed to handle multiple pixel shaders simultaneously through a unified interface and common tracking mechanism. Rather than implementing separate tracking logic for each shader, the engine provides a universal solution that monitors and manages attribute data consumption across the entire shader group, reducing overall system complexity while achieving bandwidth optimization.
3Quantity of substance
If attribute data is invalidated early to free cache space, then cache utilization is improved, but data access reliability deteriorates due to premature deallocation
Solution Approach 1:
The discard engine uses feedback from pixel shader consumption status to determine the optimal timing for data invalidation. Rather than using fixed or heuristic-based early invalidation, the system waits for explicit feedback that all shaders have finished consuming the attribute data, ensuring that cache space is freed only when safe to do so, thus maintaining data access reliability.
Data Source
AI summary
Systems, apparatuses, and methods for implementing a discard engine in a graphics pipeline are disclosed. A system includes a graphics pipeline with a geometry engine launching shaders that generate attribute data for vertices of each primitive of a set of primitives. The attribute data is consumed by pixel shaders, with each pixel shader generating a deallocation message when the pixel shader no longer needs the attribute data. A discard engine gathers deallocations from multiple pixel shaders and determines when the attribute data is no longer needed. Once a block of attributes has been consumed by all potential pixel shader consumers, the discard engine deallocates the given block of attributes. The discard engine sends a discard command to the caches so that the attribute data can be invalidated and not written back to memory.