CGR Rendering Task Offloading Across Distributed Compute Nodes
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Delivering a great computer-generated reality (CGR) experience requires significant hardware and software resources, which often operate within limited constraints, leading to issues like jitter and latency, making it difficult for users to interact seamlessly within immersive environments.
Innovation Solution
A display device dynamically discovers and offloads tasks to available computing devices, considering factors such as compute resources, energy budgets, network bandwidth, and security to enhance the user experience by leveraging nearby tablets, laptops, and cloud-based services for additional processing power.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If more hardware and software resources are allocated to deliver high-quality CGR experience, then user experience quality improves, but system complexity and resource constraints worsen
Solution Approach 1:
The patent segments the CGR processing workload into multiple independent tasks that can be distributed across different computing devices. The display device divides rendering tasks, physics calculations, and other computationally intensive operations into separate units that can be executed by different nodes in the network, thereby improving overall system reliability without requiring a single complex device to handle everything
Solution Approach 2:
The patent creates a universal computing architecture where multiple devices (display device, compute devices, cloud services) can perform multiple functions. Each device in the network can serve as both a consumer and provider of computing resources, allowing the system to adapt to different scenarios and reducing the need for specialized hardware for each function
2Speed
If computing tasks are processed locally on the display device, then response time is faster, but available processing power is limited
Solution Approach 1:
The patent transitions from a single-device processing model to a multi-dimensional distributed computing architecture. By adding the network dimension, the system can leverage computing power from multiple devices simultaneously while maintaining fast response times through intelligent task routing and local execution of time-critical operations
Solution Approach 2:
The patent introduces a task distribution mechanism that acts as an intermediary between the display device and remote compute devices. This intermediary intelligently routes tasks based on their urgency and resource requirements, ensuring that time-critical tasks are processed locally while less urgent tasks are offloaded to remote devices with greater processing power
3Power
If tasks are offloaded to remote compute devices, then processing power increases, but network bandwidth requirements increase
Solution Approach 1:
The patent implements partial offloading of tasks rather than complete remote processing. By keeping critical path operations and time-sensitive tasks on the display device while offloading only non-critical computationally intensive operations to remote devices, the system gains access to additional processing power without requiring excessive network bandwidth for data transmission
Data Source
AI summary
Techniques are disclosed relating to display devices. In some embodiments, a display device includes a display system configured to display three-dimensional content to a user. The display device is configured to discover, via a network interface, one or more compute nodes operable to facilitate rendering the three-dimensional content and receive information identifying abilities of the one or more compute nodes to facilitate the rendering. Based on the received information, the display device evaluates a set of tasks to identify one or more of the tasks to offload to the one or more compute nodes for facilitating the rendering and distributes, via the network interface, the identified one or more tasks to the one or more compute nodes for processing by the one or more compute nodes.