AR Eyewear Hardware Accelerator for BRDF Lookup Rendering
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Solution Overview
Problem
Certain augmented and virtual reality head-mounted displays (AR/VR HMDs) face power and compute constraints, preventing them from executing advanced rendering algorithms like BRDF, leading to degraded image quality and user experience.
Innovation Solution
Implementing a hardware accelerator that maps power-intensive compute operations to neural encoder/decoder architectures, trading compute operations for memory lookups, and using neural networks to approximate BRDF algorithms, reducing power and time demands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If advanced rendering algorithms like BRDF are executed on AR/VR HMDs, then image quality is improved, but power consumption and compute requirements exceed device constraints
Solution Approach 1:
The patent introduces a hardware accelerator as an intermediary component between the CPU/GPU and memory systems. This accelerator specifically implements lookup table operations to approximate BRDF calculations, mediating between the need for high-quality rendering and the constraints of mobile power consumption by offloading compute-intensive operations to specialized hardware that uses pre-computed lookup tables instead of real-time mathematical calculations
Solution Approach 2:
The patent uses lookup tables that contain pre-computed BRDF values as copies of the results that would otherwise require intensive real-time calculation. By storing pre-calculated lighting and material interaction data in lookup tables, the system replaces complex compute operations with simple memory access operations, significantly reducing power consumption while maintaining rendering quality
2Manufacturing precision
If advanced rendering algorithms like BRDF are executed on AR/VR HMDs, then image quality is improved, but the device cannot execute these algorithms within time budgets
Solution Approach 1:
The patent applies preliminary action by pre-computing BRDF values and storing them in lookup tables before runtime. This allows the rendering system to access pre-prepared results instead of performing complex calculations during real-time rendering, dramatically reducing rendering time while maintaining image quality
Solution Approach 2:
By creating copies of pre-computed BRDF results in lookup tables, the system replaces time-consuming real-time calculations with instant memory access operations, solving the time budget constraint for rendering frames
3Use of energy by moving object
If hardware accelerators use lookup tables to approximate neural compute, then power consumption is reduced, but compute precision may be affected
Solution Approach 1:
The patent changes the operational parameters of the rendering system by switching from continuous mathematical computation to discrete lookup table access. This parameter change involves transforming the BRDF calculation from a continuous function evaluation to a discrete sampling approach, where pre-computed values at specific parameter points are used to approximate continuous lighting behavior, reducing power while maintaining acceptable precision
Data Source
AI summary
An eyewear device comprising (1) an eyewear frame dimensioned to be worn by a user, (2) circuitry coupled to the eyewear frame, the circuitry comprising a hardware accelerator configured to (A) identify an input that indicates one or more features of an instance of graphical imagery and (B) perform, based at least in part on the input, one or more lookup operations via one or more arrays to obtain an output used to approximate computation of a rendering of the instance of graphical imagery, and (3) a display coupled to the eyewear frame and configured to present the rendering of the instance of graphical imagery to the user. Various other apparatuses, systems, and methods are also disclosed.