Abstract: In various examples, a virtual light meter may be implemented along with ray tracing techniques in order to determine incident light values—e.g., incoming irradiance, incident radiance, etc.—for adjusting auto exposure values of rendered frames. For example, one or more rays may be used to sample incident light over a sampling pattern—such as a hemispherical sampling pattern—for any position in a virtual game environment. As a result, the incident light values may be sampled near a subject of interest in a scene or frame such that exposure values are consistent or stable regardless of the composition of the rendered frames.

Abstract: Enhanced techniques applicable to a ray tracing hardware accelerator for traversing a hierarchical acceleration structure are disclosed. For example, traversal efficiency is improved by combining programmable traversals based on ray operations with per-node static configurations that modify traversal behavior. The per-node static configurations enable creators of acceleration data structures to optimize for potential traversals without necessarily requiring detailed information about ray characteristics and ray operations used when traversing the acceleration structure. Moreover, by providing for selective exclusion of certain nodes using per-node static configurations, less memory is needed to express an acceleration structure that includes, for example, different geometric levels of details corresponding to a single object.

Abstract: A glitch detection device includes an oscillator to generate multiple local clocks of multiple different phases and a sampling circuit to oversample, using the multiple local clocks, a system clock to generate multiple samples of the system clock. The device further includes a glitch detector to monitor a variation in pulse width of the system clock based on counting the multiple samples and to report a glitch in response to detecting a variation in the pulse width that exceeds a threshold value.

Abstract: Optical systems including an interferometer utilizing a spatial light modulator. A light guide including a first beam splitter and multiple mirrors directs incoherent light through the beam splitter to the interferometer to generate an interference light pattern, and further directs the interference light pattern back to the first beam splitter via the mirrors.

Abstract: A circuit includes a bandgap circuit configured to generate multiple reference voltages. A first voltage glitching detection circuit utilizes a first one of the reference voltages and a first power rail to generate a first reset signal in response to a voltage glitching attack on the first power rail, and a second voltage glitching detection circuit operates independently of the reference voltages to generate a second reset signal in response to the voltage glitching attack on the first power rail.

Abstract: Disclosed are techniques for compressing data of an image using multiple processing cores. The techniques include obtaining, using a first (second, etc.) processing core, a first (second, etc.) plurality of reconstructed blocks approximating source pixels of a first (second, etc.) portion of an image and filtering, using the first processing core, the first plurality of reconstructed blocks. The filtering includes enabling application of one or more filters to a first plurality of regions that include pixels of the first plurality of reconstructed blocks but not pixels of the second plurality of reconstructed blocks. The filtering further includes disabling application of the one or more filters to a second plurality of regions that include pixels of the first plurality of reconstructed blocks and pixels of the second plurality of reconstructed blocks.

Abstract: A cold plate that is configurable and for a datacenter liquid cooling system is disclosed. The cold plate includes a first section, a second section, and an intermediate layer, which is changeable and has first channels to enable flow of a coolant through the intermediate layer, and has second channels or at least one adapted second channel to concentrate the coolant or the flow of the coolant to at least one area within the configurable cold plate corresponding to at least a heat generating feature of an associated computing device.

Abstract: An autoencoder may be trained to predict 3D pose labels using simulation data extracted from a simulated environment, which may be configured to represent an environment in which the 3D pose estimator is to be deployed. Assets may be used to mimic the deployment environment such as 3D models or textures and parameters used to define deployment scenarios and/or conditions that the 3D pose estimator will operate under in the environment. The autoencoder may be trained to predict a segmentation image from an input image that is invariant to occlusions. Further, the autoencoder may be trained to exclude areas of the input image from the object that correspond to one or more appendages of the object. The 3D pose may be adapted to unlabeled real-world data using a GAN, which predicts whether output of the 3D pose estimator was generated from real-world data or simulated data.

Abstract: The disclosure provides a cheating detection strategy for interactive programs, which detects programmatically-generated motion from actual human-generated motion based on a comparison of actual motion data to inferred motion data. The cheating detection strategy uses visual and input information to ensure that the input matches the output to detect and avoid cheating tools positioned in between the input and the output. In one example, the disclosure provide a method of monitoring cheating in interactive programs that includes: (1) receiving actual motion data from a user input device, wherein the actual motion data corresponds to interacting with the interactive program, (2) receiving image data of the interactive program that includes image sequences of the interactive program to display on a screen, (3) comparing the actual motion data to inferred motion data determined from the image sequences, and (4) determining possible cheating based on the comparing.

Abstract: In examples, image data representative of an image of a field of view of at least one sensor may be received. Source areas may be defined that correspond to a region of the image. Areas and/or dimensions of at least some of the source areas may decrease along at least one direction relative to a perspective of the at least one sensor. A downsampled version of the region (e.g., a downsampled image or feature map of a neural network) may be generated from the source areas based at least in part on mapping the source areas to cells of the downsampled version of the region. Resolutions of the region that are captured by the cells may correspond to the areas of the source areas, such that certain portions of the region (e.g., portions at a far distance from the sensor) retain higher resolution than others.

Abstract: In various examples, physical sensor data may be generated by a vehicle in a real-world environment. The physical sensor data may be used to train deep neural networks (DNNs). The DNNs may then be tested in a simulated environment—in some examples using hardware configured for installation in a vehicle to execute an autonomous driving software stack—to control a virtual vehicle in the simulated environment or to otherwise test, verify, or validate the outputs of the DNNs. Prior to use by the DNNs, virtual sensor data generated by virtual sensors within the simulated environment may be encoded to a format consistent with the format of the physical sensor data generated by the vehicle.

Abstract: A trajectory for an autonomous machine may be evaluated for safety based at least on determining whether the autonomous machine would be capable of occupying points of the trajectory in space-time while still being able to avoid a potential future collision with one or more objects in the environment through use of one or more safety procedures. To do so, a point of the trajectory may be evaluated for conflict based at least on a comparison between points in space-time that correspond to the autonomous machine executing the safety procedure(s) from the point and arrival times of the one or more objects to corresponding position(s) in the environment. A trajectory may be sampled and evaluated for conflicts at various points throughout the trajectory. Based on results of one or more evaluations, the trajectory may be scored, eliminated from consideration, or otherwise considered for control of the autonomous machine.

Abstract: Apparatuses, systems, and techniques to use data obtained from an inferred object to determine whether to re-infer the same inferred object. In at least one embodiment, data obtained from inferencing a tracked object among a set of images is used to adjust a set of conditions.

Abstract: Apparatuses, systems, and techniques to identify a shape or camera pose of a three-dimensional object from a two-dimensional image of the object. In at least one embodiment, objects are identified in an image using one or more neural networks that have been trained on objects of a similar category and a three-dimensional mesh template.

Abstract: Recurrent blurring may be used to render frames of a virtual environment, where the radius of a filter for a pixel is based on a number of successfully accumulated frames that correspond to that pixel. To account for rejections of accumulated samples for the pixel, ray-traced samples from a lower resolution version of a ray-traced render may be used to increase the effective sample count for the pixel. Parallax may be used to control the accumulation speed along with an angle between a view vector that corresponds to the pixel. A magnitude of one or more dimensions of a filter applied to the pixel may be based on an angle of a view vector that corresponds to the pixel to cause reflections to elongate along an axis under glancing angles. The dimension(s) may be based on a direction of a reflected specular lobe associated with the pixel.

Abstract: In at least one embodiment, differentiable neural architecture search and reinforcement learning are combined under one framework to discover network architectures with desired properties such as high accuracy, low latency, or both. In at least one embodiment, an objective function for search based on generalization error prevents the selection of architectures prone to overfitting.

Abstract: Optical center is determined on a column-by-column and row-by-row basis by identifying brightest pixels in respective columns and rows. The brightest pixels in each column are identified and a line is fit to those pixels. Similarly, brightest pixels in each row are identified and a second line is fit to those pixels. The intersection of the two lines is the optical center.

Abstract: One embodiment of a method for rendering one or more graphics images includes tracing one or more rays through a graphics scene; storing one or more hit points based on one or more coordinate frames associated with one or more voxels of a grid, where the one or more rays intersect one or more surfaces of geometry in the one or more voxels; and rendering one or more graphics images based on the one or more hit points that are stored.

Abstract: Apparatuses, systems, and techniques to perform non-maximum suppression (NMS) in parallel to remove redundant bounding boxes. In at least one embodiment, two or more parallel circuits to perform two or more portions of a NMS algorithm in parallel to remove one or more redundant bounding boxes corresponding to one or more objects within one or more digital images.

Abstract: In various examples, a 3D surface structure such as the 3D surface structure of a road (3D road surface) may be observed and estimated to generate a 3D point cloud or other representation of the 3D surface structure. Since the estimated representation may be sparse, a deep neural network (DNN) may be used to predict values for a dense representation of the 3D surface structure from the sparse representation. For example, a sparse 3D point cloud may be projected to form a sparse projection image (e.g., a sparse 2D height map), which may be fed into the DNN to predict a dense projection image (e.g., a dense 2D height map). The predicted dense representation of the 3D surface structure may be provided to an autonomous vehicle drive stack to enable safe and comfortable planning and control of the autonomous vehicle.