Disclosed is a ray clustering learning method based on weakly-supervised learning for denoising using ray tracing. The ray clustering learning method is for learning a denoising model for removing noise from a rendered image through ray tracing, and includes extracting a feature of a simulated ray through the ray tracing and clustering the ray through contrastive learning for the feature.

Disclosed is a ray clustering learning method based on weakly-supervised learning for denoising using ray tracing. The ray clustering learning method is for learning a denoising model for removing noise from a rendered image through ray tracing, and includes extracting a feature of a simulated ray through the ray tracing and clustering the ray through contrastive learning for the feature.

A method for visualizing two-dimensional data with three-dimensional volume enables the end user to easily view abnormalities in sequential data. The two-dimensional data can be in the form of a tiled texture with the images in a set row and column, a media file with the images displayed at certain images in time, or any other way to depict a set of two-dimensional images. The disclosed method takes in each pixel of the images and evaluates the density, usually represented by color, of the pixel. The disclosed method evaluates and renders the opacity and color of each of the pixels within the volume. The disclosed method also calculates and creates dynamic shadows within the volume in real time. This evaluation allows the user to set threshold values and return exact representations of the data presented.

A method for visualizing two-dimensional data with three-dimensional volume enables the end user to easily view abnormalities in sequential data. The two-dimensional data can be in the form of a tiled texture with the images in a set row and column, a media file with the images displayed at certain images in time, or any other way to depict a set of two-dimensional images. The disclosed method takes in each pixel of the images and evaluates the density, usually represented by color, of the pixel. The disclosed method evaluates and renders the opacity and color of each of the pixels within the volume. The disclosed method also calculates and creates dynamic shadows within the volume in real time. This evaluation allows the user to set threshold values and return exact representations of the data presented.

Systems and methods and computer program products for processing three-dimensional (3D) graphics are provided. A method includes receiving 3D geometry data for a shape to be rendered to a display that comprises an array of hogels, the shape defined in a model space. The method can further include reducing downstream processing of the 3D geometry data to render the shape to the display, comprising identifying a subset of hogels in a hogel plane that have hogel bowtie frustums that intersect the shape.

Systems and methods and computer program products for processing three-dimensional (3D) graphics are provided. A method includes receiving 3D geometry data for a shape to be rendered to a display that comprises an array of hogels, the shape defined in a model space. The method can further include reducing downstream processing of the 3D geometry data to render the shape to the display, comprising identifying a subset of hogels in a hogel plane that have hogel bowtie frustums that intersect the shape.

Aspects presented herein relate to methods and devices for graphics processing including an apparatus, e.g., a GPU. The apparatus may configure a BVH structure including a plurality of levels and a plurality of nodes, the BVH structure being associated with geometry data for a plurality of primitives in a scene. The apparatus may also identify an amount of storage in a GMEM that is available for storing at least some of the plurality of nodes in the BVH structure. Further, the apparatus may allocate the BVH structure into a first BVH section including a plurality of first nodes and a second BVH section including a plurality of second nodes. The apparatus may also store first data associated with the plurality of first nodes in the GMEM and second data associated with the plurality of first nodes and the plurality of second nodes in a system memory.

Aspects presented herein relate to methods and devices for graphics processing including an apparatus, e.g., a GPU. The apparatus may configure a BVH structure including a plurality of levels and a plurality of nodes, the BVH structure being associated with geometry data for a plurality of primitives in a scene. The apparatus may also identify an amount of storage in a GMEM that is available for storing at least some of the plurality of nodes in the BVH structure. Further, the apparatus may allocate the BVH structure into a first BVH section including a plurality of first nodes and a second BVH section including a plurality of second nodes. The apparatus may also store first data associated with the plurality of first nodes in the GMEM and second data associated with the plurality of first nodes and the plurality of second nodes in a system memory.

Systems and methods for evaluating ND are described herein. An example method can include constructing a non-sequential (NSC) ray-tracing model of an eye with an ophthalmic lens, and modelling a light source and a detector. The detector can be configured to mimic a retina of the eye. The method can also include computing irradiance data using the light source, the NSC ray-tracing model, and the detector. Irradiance data can be computed for each of a plurality of pupil sizes. The method can further include evaluating ND by analyzing the respective irradiance data for each of the pupil sizes. Also described herein are methods for designing an ophthalmic lens edge that reduces the incidence of ND for a given ophthalmic lens by adjusting the edge thickness and/or the scatter.

Systems and methods for evaluating ND are described herein. An example method can include constructing a non-sequential (NSC) ray-tracing model of an eye with an ophthalmic lens, and modelling a light source and a detector. The detector can be configured to mimic a retina of the eye. The method can also include computing irradiance data using the light source, the NSC ray-tracing model, and the detector. Irradiance data can be computed for each of a plurality of pupil sizes. The method can further include evaluating ND by analyzing the respective irradiance data for each of the pupil sizes. Also described herein are methods for designing an ophthalmic lens edge that reduces the incidence of ND for a given ophthalmic lens by adjusting the edge thickness and/or the scatter.