Image Warping Memory Bank Segmentation for SDRAM Efficiency
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Solution Overview
Problem
Existing video processing technologies face inefficiencies due to the need for sequential row access in SDRAM, which leads to long data processing times and intensive resource usage, particularly in image warping applications where random row access is required.
Innovation Solution
An apparatus and method that divide the source image into pixel blocks comprising neighboring horizontal and vertical pixels, allowing for efficient storage and retrieval of these blocks in sequential memory locations, reducing SDRAM access and enabling faster processing through interleaving banks and using a warp engine to map output coordinates to warped coordinates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If sequential row access is used in SDRAM for video processing, then memory access simplicity is improved, but processing time increases significantly
Solution Approach 1:
The patent divides the image data into multiple banks (e.g., 4 banks) within the SDRAM structure. Each bank can be accessed independently and simultaneously, allowing parallel processing of different portions of the image data. This segmentation transforms a single sequential access operation into multiple parallel access operations, dramatically reducing processing time while maintaining the simplicity of row-based access within each bank.
Solution Approach 2:
The patent introduces a bank dimension to the traditional row-column memory address structure. Instead of accessing memory in a single dimensional sequence (row by row), the system now accesses memory across multiple dimensions by simultaneously accessing different banks. This adds a spatial parallelism dimension that enables concurrent access to multiple data blocks without increasing the complexity of individual access operations.
2Device complexity
If sequential row access is used in SDRAM, then memory structure simplicity is improved, but resource usage intensity increases
Solution Approach 1:
The memory system is segmented into multiple independent banks, each capable of autonomous operation. This allows the system to distribute processing load across multiple banks rather than concentrating all access operations on a single memory structure. The segmentation enables parallel execution of memory access operations, reducing the overall energy consumption per operation while maintaining simple row-based access within each bank.
Solution Approach 2:
The patent combines multiple simple memory banks into a unified memory system that operates in parallel. By merging several independent but identical memory structures, the system achieves both simplicity (each bank remains simple) and efficiency (collective operation reduces resource usage intensity through parallelism and load distribution).
3Productivity
If pixel blocks are stored in sequential memory locations, then memory access efficiency is improved, but storage organization complexity increases
Solution Approach 1:
The patent segments the storage organization into fixed-size pixel blocks that are systematically arranged in sequential memory locations. Each block contains a defined number of pixels (e.g., 16x16 or 32x32), and blocks are stored contiguously in memory. This segmentation creates a regular, predictable storage pattern that optimizes cache utilization and memory access efficiency while keeping the organization rule simple: store block n at memory location n.
Data Source
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AI summary
Incoming video data is processed. According to an example embodiment, video data as presented in rows of pixels is stored in terms of blocks of pixels of corresponding images making up the video. When a particular pixel is read from memory, the block of pixels is retrieved (e.g., with a single read), facilitating (simultaneous) access to pixels in adjacent rows or columns, without necessarily accessing entire rows and columns to do so.