Texture Memory Optimization for Mobile Devices
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Solution Overview
Problem
Current texture compression techniques fail to optimize memory usage effectively in multimedia devices, leading to performance issues due to increased demand for high-resolution textures, resulting in lag and user experience degradation when multiple applications consume excessive RAM.
Innovation Solution
A system and method that employs Dynamic Texture Scaling (DTS), Content Adaptive Compression (CAC), and On Device Texture Compression (ODTC) to optimize texture memory by selecting the appropriate technique based on rendering parameters such as device resolution, available memory, and texture type, reducing memory consumption while maintaining image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If texture resolution is increased to improve image quality, then image quality is improved, but memory consumption increases
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting texture resolution and compression level based on device characteristics, rendering parameters, and memory availability. The system transforms textures from original high resolution to optimized resolutions, and adjusts compression levels to balance image quality with memory consumption, resolving the contradiction between image quality and memory usage.
Solution Approach 2:
The patent implements dynamics by making the texture optimization process adaptive and runtime-adjustable. The system continuously monitors rendering parameters, device resolution, and memory status to dynamically select and apply appropriate optimization techniques (DTS, CAC, ODTC), allowing the texture processing to adapt to changing conditions rather than using static pre-compression approaches.
2Adaptability or versatility
If multiple applications are run simultaneously to improve functionality, then functionality is improved, but memory consumption increases causing performance degradation
Solution Approach 1:
The patent changes the parameter of texture memory allocation dynamically based on system state. When multiple applications are running, the system adjusts texture quality parameters and compression levels to maintain acceptable performance. The Low Memory Killer (LMK) policy is integrated to trigger optimization when memory pressure is detected, allowing the system to maintain functionality of multiple applications while preventing performance degradation through adaptive texture optimization.
3Quantity of substance
If texture compression is applied to reduce memory usage, then memory consumption is reduced, but image quality deteriorates
Solution Approach 1:
The patent applies local quality by using Content Adaptive Compression (CAC) that analyzes different regions of textures and applies compression selectively. Important regions with high visual impact are preserved with higher quality, while less critical regions are compressed more aggressively. This allows the system to reduce overall memory consumption while maintaining acceptable image quality in visually important areas.
Solution Approach 2:
The patent implements partial action by applying different compression levels to different textures based on their importance and usage patterns. Not all textures are compressed to the same degree - the system applies optimization selectively based on rendering parameters and device capabilities, achieving sufficient memory reduction while maintaining quality where necessary.
4Quantity of substance
If Low Memory Killer policy is applied to free cache memory, then cache memory availability is improved, but user experience deteriorates due to application killing
Solution Approach 1:
The patent applies preliminary action by performing texture optimization proactively before memory pressure becomes critical. The system monitors memory usage trends and applies DTS, CAC, or ODTC techniques in advance to free up cache memory, preventing the need to kill applications. This anticipatory approach ensures cache memory availability is maintained while preserving user experience by avoiding application termination.
Solution Approach 2:
The patent implements feedback mechanisms that continuously monitor cache memory usage, device resolution, and rendering parameters. When memory usage approaches thresholds, the system automatically triggers optimization techniques and adjusts texture processing parameters. This closed-loop feedback system maintains cache memory availability dynamically without requiring aggressive application killing, thereby preserving user experience.
Data Source
AI summary
The embodiments herein provide a mobile device comprising a display, and a processor configured to receiving a texture to be rendered on the display, checking at least one rendering parameter for the received texture wherein the rendering parameter comprises at least one of a device resolution, available memory, rendering path, and texture type, selecting at least one memory optimization technique based on the at least one rendering parameter, wherein the memory optimization technique is at least one of Dynamic Texture Scaling (DTS), Content Adaptive Compression (CAC), and On Device Texture Compression (ODTC) and performing the selected texture optimization technique on the received texture.