Graphics Processing Optimization for Large Data Visualization

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Existing systems face difficulties in efficiently processing and displaying large datasets due to insufficient computing power, where massive datasets overwhelm processors, leading to slow rendering and inability to handle user-selected subsets efficiently, especially with heterogeneous data containing missing or corrupted points.

Innovation Solution

A Graphics Processing and Optimization (GPO) computing device is employed, which includes a memory device, user interface, and display device, configured to select and render data points using enhancement algorithms, convert data into renderable graphics components, and dynamically manage processing resources to display subsets of data efficiently, utilizing worker processes and image transformations to reduce computational intensity.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If the entire dataset is processed and rendered at all times, then complete data is available for display, but processor power is starved and rendering speed decreases

Engineering Contradiction:

Improvedata completenessVSAvoidrendering speed

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The dataset is divided into multiple tiles that can be independently processed and rendered. Each tile represents a portion of the overall data space, allowing the system to process only the necessary tiles for the current view rather than the entire dataset, thus improving rendering speed while maintaining data completeness for the visible portion.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system processes only the necessary subset of data tiles required for the current display view rather than the entire dataset. This partial processing approach provides sufficient data for the current rendering needs without the overhead of processing all data, resolving the contradiction between data completeness and rendering speed.

Inventive Principle:

Principle #16Partial or excessive action

2Manufacturing precision

If every pixel is processed and rendered, then complete visual representation is achieved, but processing power is wasted on non-data point pixels

Engineering Contradiction:

Improvevisual accuracyVSAvoidprocessing power consumption

Core Design Contradiction:

Manufacturing precisionVSUse of energy by moving object

Solution Approach 1:

The system extracts only the essential data point information needed for rendering and represents it using efficient graphical primitives. By taking out only the necessary visual elements and representing them with simple geometric shapes rather than processing every individual pixel, the system achieves visual accuracy while dramatically reducing processing power consumption.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The system replaces traditional pixel-by-pixel rendering with a vector-based approach using graphical primitives. Instead of mechanically processing each pixel in the framebuffer, the system uses mathematical descriptions of geometric shapes that can be rendered more efficiently, substituting the mechanical pixel processing system with a more efficient graphical primitive rendering system.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Productivity

If complex parallel processing techniques are used to distribute data across multiple processors, then processing capacity increases, but system complexity and coordination overhead increase

Engineering Contradiction:

Improveprocessing capacityVSAvoidsystem complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The data space is segmented into independent tiles that can be processed in parallel by multiple worker processes. Each worker process handles specific tiles independently, eliminating the need for complex coordination between processors. This segmentation approach increases processing capacity while keeping system complexity manageable through simple task distribution.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

Each worker process independently processes its assigned tiles without requiring complex coordination or synchronization with other workers. The system uses a simple task queue where workers pick up and process tiles autonomously, allowing parallel processing to scale without proportionally increasing system complexity. The independence of tile processing enables self-service operation.

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS9978114B2Systems and methods for optimizing graphics processing for rapid large data visualization

Publication Date: 2018.05.22 GENERAL ELECTRIC CO

AI summary

A system for optimizing processing and display of large datasets is provided. The system includes a graphics processing and optimization (GPO) computing device. The GPO computing device is configured to store a dataset including a data point in a memory device, select the data point to display on a display device based on a first display request signal received via a user interface, and accelerate graphical processing of the dataset using optimization algorithms, wherein the GPO computing device is configured to assign a worker process to execute on the data point, The GPO computing device is also configured to convert the data point into a renderable graphics component, and generate a least-compute intensive representation of the data point, and cause the user interface to display a graphical representation of a first subset of the data including the renderable graphics component at a first display resolution.