Tiled Image Rendering Pipeline with Texture Pyramid Caching
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Solution Overview
Problem
Traditional GPU-based rendering approaches for large images, such as those used in medical imaging, suffer from slow data transfer and unacceptably slow rendering times due to the large amount of data being transferred from CPU memory to the GPU, especially on high-resolution monitors, leading to inhibited smooth rendering and slow access when images are located remotely.
Innovation Solution
A GPU-based rendering pipeline that includes a texture pyramid with toroidal wrapping, where the texture serves as both an image object and a cache, allowing reuse of previously uploaded data without re-uploading, and a client-server architecture for image rendering that optimizes computations and reduces data transmission between CPU and GPU.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If traditional GPU-based rendering approaches are used for large images, then the rendering can be performed on high-resolution monitors, but the data transfer time and rendering time become unacceptably slow
Solution Approach 1:
The patent divides the large image into multiple smaller tiles that can be processed independently. The CPU prepares and transfers only the necessary tiles to the GPU as needed, rather than transferring the entire large image at once. This segmentation reduces the data transfer burden and enables incremental rendering, significantly improving rendering speed while reducing data transfer time.
Solution Approach 2:
The CPU performs preliminary preparation of image tiles before they are needed by the GPU. Tiles are pre-processed, formatted, and staged in CPU memory in advance, so that when the GPU needs them for rendering, they are ready for immediate transfer and processing. This preliminary action optimizes the workflow and reduces idle time, improving overall rendering speed.
2Quantity of substance
If the entire large image is transferred from CPU memory to GPU, then complete image data is available for rendering, but the data transfer amount becomes excessively large
Solution Approach 1:
The patent segments the large image into smaller tile units that are transferred individually from CPU to GPU. Only the tiles currently needed for the visible region and near-future rendering are transferred, rather than the entire image dataset. This reduces the quantity of data transmitted at any given time and decreases the total energy consumption for data transfer.
Solution Approach 2:
The system optimizes data transfer by focusing only on the local region of the image that is currently needed for rendering. The CPU identifies and transfers only the specific tiles corresponding to the visible area and anticipated viewing regions, rather than transferring the entire image. This localized approach reduces data transmission volume and energy usage.
3Productivity
If image tiles are cached in CPU memory, then previously uploaded data can be reused, but the cache management complexity increases
Solution Approach 1:
The patent implements a tile-based caching system where the CPU maintains a cache of image tile data that has been previously processed or is frequently needed. The cache is organized by tile coordinates and can be efficiently queried to determine whether required tiles are already available in CPU memory, enabling reuse without re-transfer and improving productivity.
Solution Approach 2:
The system employs feedback mechanisms to track which tiles are currently cached in CPU memory and which have been transferred to the GPU. This information is used to make intelligent decisions about what data to transfer next, optimizing cache utilization and reducing redundant transfers. The feedback loop improves data reuse efficiency while maintaining manageable cache complexity through systematic tracking.
Data Source
AI summary
Features are disclosed for rendering an image using a GPU and CPU based rendering pipeline. An imaging system may include a GPU and a CPU that each include a portion of an image renderer. A component of the GPU can process the set of image tiles to generate a texture with a wrapped tile coordinate. A component of the GPU can further store the image data as a level of a texture pyramid. As subsequent image data is received, a component of the GPU can access the texture pyramid to determine previously stored image tiles. A component of the GPU can use the previously stored image tiles in rendering the subsequent image data.