Hybrid Client-Server Visualization System for Dynamic Rendering Allocation
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Solution Overview
Problem
Existing visualization methods for 3D and 4D image data, such as those used in medical imaging, are computationally intensive and often require specialized hardware, leading to long rendering times and limitations in interactive data exploration.
Innovation Solution
A client-server visualization system with hybrid data processing, where client computers and a render server collaborate to render images, with the client performing local processing for dynamic aspects and the server handling more compute-intensive tasks, allowing for dynamic allocation of rendering tasks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If standard visualization methods (volume rendering) are used to process large 3D and 4D image datasets, then comprehensive image processing capability is achieved, but rendering time becomes excessively long and interactivity is lost
Solution Approach 1:
The rendering task is segmented into two distinct parts: (1) server-side processing that handles compute-intensive operations such as volume rendering, ray casting, and data processing; (2) client-side processing that handles display, user interaction, and simple graphics composition. This segmentation allows the heavy computational burden to be offloaded to the server while the client maintains responsiveness for user interactions.
Solution Approach 2:
A network connection serves as the intermediary between the server and client. The server renders images and transmits them through the network to the client for display. This intermediary approach enables the client to access powerful rendering capabilities without requiring local hardware acceleration, resolving the contradiction between rendering speed and client hardware requirements.
2Productivity
If specialized rendering hardware is deployed locally at the client to achieve fast rendering, then rendering speed improves, but device complexity and hardware cost increase
Solution Approach 1:
Instead of requiring each client to possess expensive specialized rendering hardware, the system creates a virtual copy of the rendering capability through remote server access. The server maintains the specialized hardware resources, and clients access these resources remotely, effectively copying the high-performance rendering function without requiring physical duplication at each client location.
Solution Approach 2:
The server provides universal rendering capabilities that can be accessed by multiple clients simultaneously. A single server instance with specialized hardware can serve multiple users, making the expensive rendering infrastructure shared and multi-functional rather than requiring each client to maintain its own specialized hardware.
3Device complexity
If all rendering operations are performed on the server, then client hardware requirements are reduced, but network bandwidth consumption increases and rendering responsiveness decreases
Solution Approach 1:
The system applies partial action by having the client perform simple graphics composition and display operations locally while the server handles only the essential compute-intensive rendering tasks. This partial offloading approach reduces network bandwidth consumption compared to complete server processing, while still maintaining low hardware requirements at the client end.
Solution Approach 2:
The system dynamically adjusts the division of rendering tasks between server and client based on real-time conditions. The client can request different levels of processing detail, and the system can adaptively allocate computational tasks, allowing clients to balance between network bandwidth usage and rendering quality based on their specific needs and network conditions.
Data Source
AI summary
The invention comprises a system of client-server visualization with hybrid data processing, having a server digital data processor, that allows for server side rendering and processing image data, and client digital data processors simultaneously connected to the server, which receives messages from the clients, creates rendered images of data sets or other data processing results and sends those rendered images and results to the clients for display or further processing. Performing certain image rendering operations on either the server or the client according to which is better suited for the tasks requested by the user at any point in time, and possibly adjusting this division of work dynamically, improves rendering speed and application responsiveness on the clients.