GPU 3D Data Decompression via Segmented Parallel Processing
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Solution Overview
Problem
The existing methods for decompressing 3D object data lead to a bottleneck between the CPU and GPU, resulting in increased processing time and reduced transmission rates, which hampers the efficient output of 3D object data.
Innovation Solution
A GPU is designed to decompress compressed 3D object data by extracting segment information from the data header and using parallel threads to decompress segments, with memory allocation for storing the compressed and decompressed data, allowing for efficient parallel processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the CPU decompresses the compressed 3D object data, then the decompression process can be completed, but the transmission rate between the CPU and GPU reduces and processing time increases
Solution Approach 1:
The patent divides the compressed 3D object data into multiple segments, each with its own header containing decompression parameters. This segmentation allows the GPU to independently decompress multiple segments simultaneously using parallel threads, significantly reducing the overall decompression time compared to sequential CPU decompression.
Solution Approach 2:
The patent introduces a bit stream format with structured headers that contain segment information and decompression parameters. This intermediary data structure enables the GPU to efficiently extract and process segment information without requiring complex CPU intervention, facilitating fast parallel decompression while maintaining data integrity.
2Ease of operation
If the CPU decompresses the compressed 3D object data before transmission to the GPU, then the GPU receives ready-to-use data, but a bottleneck situation between the CPU and GPU occurs
Solution Approach 1:
The patent segments the compressed data into multiple independent units with self-contained headers. This allows the GPU to receive and process multiple segments in parallel immediately upon reception, eliminating the sequential bottleneck that would occur with traditional CPU-decompressed data transmission.
Solution Approach 2:
The patent performs preliminary organization of the compressed data into a structured bit stream format with embedded segment information and headers before transmission. This preliminary structuring enables the GPU to directly extract and process segments without requiring additional CPU preprocessing, improving transmission efficiency and reducing bottlenecks.
3Quantity of substance
If the capacity of the 3D object data increases, then more detailed 3D objects can be represented, but the transmission rate between the CPU and GPU reduces
Solution Approach 1:
The patent divides large-capacity 3D object data into multiple smaller segments that can be transmitted and processed in parallel. This segmentation maintains high transmission rates by allowing the GPU to receive and decompress multiple segments simultaneously, rather than transmitting one large data set sequentially.
Solution Approach 2:
The patent transitions from sequential data transmission to parallel processing by organizing data into segments that can be handled in multiple dimensions simultaneously. The bit stream structure enables the GPU to process segments across multiple parallel threads, effectively increasing transmission throughput for large data capacities.
Data Source
AI summary
A graphic processing unit (GPU) and method for decompressing compressed 3-dimensional (3D) compressed data. The GPU may extract segment information by analyzing a compressed data header and decompress segments included in a bit stream based on the segment information.