Digital Instrument Cluster Full Sweep Without a GPU
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Solution Overview
Problem
GPU-less digital instrument cluster systems face challenges in rendering dynamic assets efficiently due to the lack of graphical processing units, leading to slow performance and artifacts like jagged edges, and struggle to achieve quick startup times due to the complexity of managing large asset data and decoding compressed files.
Innovation Solution
Implementing a method and apparatus that uses a processor to sequentially retrieve and display dynamic assets at increasing levels of granularity, with a full sweep from minimum to maximum and back, leveraging compressed preprocessed assets stored in memory to simulate GPU graphical effects, and utilizing multiple processors for concurrent execution to accelerate the boot process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If a GPU is used to render digital instrument cluster graphics, then graphical quality and rendering speed are improved, but device complexity and cost increase
Solution Approach 1:
The patent extracts the GPU rendering function and replaces it with a CPU-based rendering engine. The system removes the dedicated graphics processing unit and implements all graphical rendering operations through the central processing unit, thereby reducing device complexity while maintaining rendering capability through software-based graphics processing
Solution Approach 2:
The patent substitutes the hardware-based GPU rendering system with a software-based CPU rendering system. By replacing the dedicated graphics hardware with general-purpose processor-based rendering, the system eliminates the need for complex graphical processing units while achieving acceptable rendering performance through optimized software algorithms
2Quantity of substance
If compressed asset files are decoded and displayed sequentially, then memory usage is reduced, but startup time increases
Solution Approach 1:
The patent applies preliminary action by pre-compressing asset files before storage and by implementing an optimized decoding sequence during startup. Assets are compressed offline and stored in compact form, then decoded in a prioritized sequence during system initialization, allowing critical graphical elements to be rendered first while minimizing overall startup time
Solution Approach 2:
The patent segments the asset decoding process into multiple priority levels and batches. Instead of decoding all assets uniformly, the system divides them into critical and non-critical segments, decoding essential graphical elements first and less important assets subsequently, thereby reducing perceived startup time while maintaining efficient memory usage
3Measurement precision
If all dynamic assets are retrieved with high granularity, then display precision is improved, but data retrieval time and memory usage increase
Solution Approach 1:
The patent applies local quality by retrieving and rendering dynamic assets at different granularity levels based on their importance and visibility. Critical assets that directly impact safety or primary information display are retrieved with high granularity, while less important assets use lower granularity, optimizing the balance between display precision and retrieval efficiency
Solution Approach 2:
The patent implements partial action by retrieving only the necessary portion of dynamic assets at full granularity rather than all assets. The system identifies and prioritizes essential dynamic elements for immediate retrieval, accepting that some less critical assets may be loaded at reduced granularity or deferred, thereby reducing overall data retrieval time and memory consumption
Data Source
AI summary
A method for implementing a full sweep in a digital instrument cluster system without a graphical processing unit (GPU) is disclosed. The method includes displaying a static asset as background for displaying of dynamic assets that point to different position values on the static asset, sequentially retrieving each of a plurality of subsets of dynamic assets such that each subset provides position indicators with a different level of position granularity, wherein an order of retrieving each subset moves from a lowest granularity subset to a highest granularity subset until all of the plurality of subsets of dynamic assets have been retrieved, and performing a full sweep, prior to retrieving of the dynamic assets, by sequentially displaying the dynamic assets from a minimum position to a maximum position of the static asset, and back, the sequentially displaying being based on a highest available granularity of dynamic assets that have been retrieved.