Shader Engine Bandwidth Compression for Frame Buffer Memory
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Solution Overview
Problem
Graphics processing units (GPUs) face memory bandwidth limitations due to the high number of threads executing simultaneously, leading to unprocessed read/write requests accumulating at the frame buffer interface, which substantially limits memory-related performance.
Innovation Solution
A method for compressing data for thread group STORE operations by determining if thread group data is compressible and reducing it into fewer subpackets, allowing it to be written to the frame buffer memory in one clock cycle, thereby reducing data written and read from the memory.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple threads execute simultaneously in a thread group, then processing throughput increases, but memory bandwidth requirements exceed available bandwidth
Solution Approach 1:
The patent merges the memory operations of multiple threads into a single compressed transaction. Instead of each thread separately accessing memory (which would require 32x the bandwidth), the system combines all thread operations into one compressed memory transaction that can be processed simultaneously, achieving both high throughput and efficient bandwidth utilization.
Solution Approach 2:
The system changes the parameter of data representation from uncompressed individual thread data to compressed merged data. By transforming the data structure and compression state, the system reduces the effective bandwidth requirement from 128B to 16B per clock cycle while maintaining the processing capabilities of all 32 threads.
2Reliability
If uncompressed thread group data is written to frame buffer memory, then all thread operations are preserved, but multiple clock cycles are required increasing latency
Solution Approach 1:
The system segments the memory transaction into a compressed representation that encapsulates all individual thread operations. This segmented compressed transaction can be written in a single clock cycle while preserving the complete data integrity of all 32 threads, eliminating the need for multiple sequential clock cycles.
Solution Approach 2:
The compression process performs preliminary action by pre-processing and organizing thread data into a compressed format before memory writing. This preliminary compression step enables the entire thread group data to be written in one clock cycle, significantly reducing access time while maintaining data integrity.
3Quantity of substance
If data is compressed into fewer subpackets, then bandwidth utilization improves, but data decompression complexity increases
Solution Approach 1:
The system implements self-service by embedding compression metadata directly within the compressed data structure itself. This allows the decompression process to automatically identify and apply the correct decomposition without requiring external control signals or complex coordination, simplifying the overall system architecture despite the compression transformation.
Data Source
AI summary
Embodiments of the present invention set forth systems and methods for compressing thread group data written to frame buffer memory to increase overall memory performance. A compression/decompression engine within the frame buffer memory interface includes logic configured to identify situations where the threads of a thread group are writing similar scalar values to memory. Upon recognizing such a situation, the engine is configured to compress the scalar data into a form that allows all of the scalar data to be written to or read from the frame buffer memory in fewer clock cycles than would be required to transmit the data in uncompressed form to or from memory. Consequently, the disclosed systems and methods are able to effectively increase memory performance when executing thread group STORE and LOAD operations.