Abstract: A method, computer readable medium, and system are disclosed for overlaying a cell onto a polygon meshlet. The polygon meshlet may include a grouping of multiple geometric shapes such as triangles, and the cell may include a square-shaped boundary. Additionally, every polygon (e.g., a triangle or other geometric shape) within the polygon meshlet that has at least one edge fully inside the cell is removed to create an intermediate meshlet. A selected vertex is determined from all vertices (e.g., line intersections) of the intermediate meshlet that are located within the cell, based on one or more criteria, and all the vertices of the intermediate meshlet that are located within the cell are replaced with the selected vertex to create a modified meshlet. The modified meshlet is then rendered (e.g., as part of a process to generate a scene to be viewed).

Abstract: A transceiver configured to communicate a burst of data bits and meta-data bits for the data bits includes data channels, auxiliary data channels, and at least one error correction channel. The transceiver includes an encoder that applies 11b7s encoding to a first number of the data bits to generate first PAM-3 symbols on some or all of the communication channels, and that applies 3b2s encoding to a second number of the data bits to generate second PAM-3 symbols on at least some of the communication channels.

Abstract: In an embodiment, an augmented reality display is provided that incorporates a prescription lens for the wearer. In an embodiment, an image is generated from a display and directed into the edge of the prescription lens, and the lens acts as a waveguide. The image is internally reflected within the prescription lens, and is directed to the wearer by an image combiner embedded within the prescription lens. In an embodiment, the augmented reality display can be adjusted for many common vision problems including myopia, hyperopia, astigmatism, and presbyopia.

Abstract: A network device serving as a local VXLAN) Tunnel Endpoint (VTEP) includes a communication interface, a first processor and a packet processor. The communication interface communicates between the local VTEP and remote VTEPs, each VTEP has a respective VXLAN Identifier (VNI). The first processor imports a Downstream-VNI (D-VNI) to be used in forwarding packets from the local VTEP to a remote VTEP, creates a unique egress Routing Interface (RIF) that is translatable into the imported D-VNI, and associates the unique egress RIF with one or more route entries in the local VTEP. The packet processor receives a packet destined to the remote VTEP, looks up the packet in the route entries in the local VTEP to retrieve the unique egress RIF, translates the unique egress RIF into the imported D-VNI, encapsulates the packet with the imported D-VNI, and forwards the encapsulated packet in accordance with the unique egress RIF.

Abstract: To mitigate pulse shape degradation along a signal route, the signal is driven from two ends. One end of the route is loaded and the other is relatively unloaded. The loaded route and unloaded route may traverse two different metal layers on a printed circuit board. The two routes may thus be related such that the unloaded route has less RC distortion effects on the signal than does the loaded route.

Abstract: In various examples, systems and methods are disclosed that accurately identify driver and passenger in-cabin activities that may indicate a biomechanical distraction that prevents a driver from being fully engaged in driving a vehicle. In particular, image data representative of an image of an occupant of a vehicle may be applied to one or more deep neural networks (DNNs). Using the DNNs, data indicative of key point locations corresponding to the occupant may be computed, a shape and/or a volume corresponding to the occupant may be reconstructed, a position and size of the occupant may be estimated, hand gesture activities may be classified, and/or body postures or poses may be classified. These determinations may be used to determine operations or settings for the vehicle to increase not only the safety of the occupants, but also of surrounding motorists, bicyclists, and pedestrians.

Abstract: One embodiment of a computer-implemented method for compiling a material graph into a set of instructions for execution within an execution unit includes receiving a first material graph having a plurality of nodes, wherein each node included in the plurality of nodes represents a different surface property of a material; parsing the material graph to generate an expression tree that includes one or more expressions for each node included in the plurality of nodes; and generating a set of byte code instructions corresponding to the material graph based on the expression tree, wherein the byte code instructions are executable by a plurality of processing cores included within the execution unit.

Abstract: Apparatuses, systems, and techniques for isolating the performance of a quality-of-service (QoS) policy for improved data streaming systems and applications. In at least one embodiment, a metric is determined for a QoS policy used to provide an application session based on a value of at least one characteristic of the application session that reflects an impact of one or more external conditions beyond the control of the QoS policy.

Abstract: In various examples, a sequential deep neural network (DNN) may be trained using ground truth data generated by correlating (e.g., by cross-sensor fusion) sensor data with image data representative of a sequences of images. In deployment, the sequential DNN may leverage the sensor correlation to compute various predictions using image data alone. The predictions may include velocities, in world space, of objects in fields of view of an ego-vehicle, current and future locations of the objects in image space, and/or a time-to-collision (TTC) between the objects and the ego-vehicle. These predictions may be used as part of a perception system for understanding and reacting to a current physical environment of the ego-vehicle.

Abstract: In various examples, systems and methods are disclosed that accurately identify driver and passenger in-cabin activities that may indicate a biomechanical distraction that prevents a driver from being fully engaged in driving a vehicle. In particular, image data representative of an image of an occupant of a vehicle may be applied to one or more deep neural networks (DNNs). Using the DNNs, data indicative of key point locations corresponding to the occupant may be computed, a shape and/or a volume corresponding to the occupant may be reconstructed, a position and size of the occupant may be estimated, hand gesture activities may be classified, and/or body postures or poses may be classified. These determinations may be used to determine operations or settings for the vehicle to increase not only the safety of the occupants, but also of surrounding motorists, bicyclists, and pedestrians.

Abstract: Techniques are disclosed for improving the throughput of ray intersection or visibility queries performed by a ray tracing hardware accelerator. Throughput is improved, for example, by releasing allocated resources before ray visibility query results are reported by the hardware accelerator. The allocated resources are released when the ray visibility query results can be stored in a compressed format outside of the allocated resources. When reporting the ray visibility query results, the results are reconstructed based on the results stored in the compressed format. The compressed format storage can be used for ray visibility queries that return no intersections or terminate on any hit ray visibility query. One or more individual components of allocated resources can also be independently deallocated based on the type of data to be returned and/or results of the ray visibility query.

Abstract: Layout techniques for circuits on substrates are disclosed that address the multivariate problem of minimizing routing distances for high-speed I/O pins between circuits while simultaneously providing for the rapid provision of transient power demands to the circuits. The layout techniques may also enable improved thermal management for the circuits.

Abstract: A ray (e.g., a traced path of light, etc.) is generated from an originating pixel within a scene being rendered. Additionally, one or more shadow map lookups are performed for the originating pixel to estimate an intersection of the ray with alpha-tested geometry within the scene. A shadow map stores the distance of geometry as seen from the point of view of the light, and alpha-tested geometry includes objects within the scene being rendered that have a determined texture and opacity. Further, the one or more shadow map lookups are performed to determine a visibility value for the pixel (e.g., that identifies whether the originating pixel is in a shadow) and a distance value for the pixel (e.g., that identifies how far the pixel is from the light). Further still, the visibility value and the distance value for the pixel are passed to a denoiser.

Abstract: A method, computer program product, and system perform computations using a processor. A first instruction including a first index vector operand and a second index vector operand is received and the first index vector operand is decoded to produce first coordinate sets for a first array, each first coordinate set including at least a first coordinate and a second coordinate of a position of a non-zero element in the first array. The second index vector operand is decoded to produce second coordinate sets for a second array, each second coordinate set including at least a third coordinate and a fourth coordinate of a position of a non-zero element in the second array. The first coordinate sets are summed with the second coordinate sets to produce output coordinate sets and the output coordinate sets are converted into a set of linear indices.

Abstract: Apparatuses, systems, and techniques to train a generative model based at least in part on a private dataset. In at least one embodiment, the generative model is trained based at least in part on a differentially private Sinkhorn algorithm, for example, using backpropagation with gradient descent to determine a gradient of a set of parameters of the generative models and modifying the set of parameters based at least in part on the gradient.

Abstract: Convergence of threads executing common code sections is facilitated using instructions inserted at strategic locations in computer code sections. The inserted instructions enable the threads in a warp or other group to cooperate with a thread scheduler to promote thread convergence.

Abstract: Apparatuses, systems, and techniques are presented to reduce temporal lag when a dynamic event is occurring in computer generated video. In one embodiment, a first averaging algorithm is utilized to determine a display value for a pixel based at least in part on previous pixel values. Once a dynamic event is detected, a set of the previous pixel values is averaged using a second averaging algorithm. The pixel value is updated based on the first averaging of the pixel values and the second averaging of the pixel values to determine a current pixel value.

Abstract: Machine learning systems and methods that learn glare, and thus determine gaze direction in a manner more resilient to the effects of glare on input images. The machine learning systems have an isolated representation of glare, e.g., information on the locations of glare points in an image, as an explicit input, in addition to the image itself. In this manner, the machine learning systems explicitly consider glare while making a determination of gaze direction, thus producing more accurate results for images containing glare.

Abstract: In training a deep neural network using reduced precision, gradient computation operates on larger values without affecting the rest of the training procedure. One technique trains the deep neural network to develop loss, scales the loss, computes gradients at a reduced precision, and reduces the magnitude of the computed gradients to compensate for scaling of the loss. In one example non-limiting arrangement, the training forward pass scales a loss value by some factor S and the weight update reduces the weight gradient contribution by 1/S. Several techniques can be used for selecting scaling factor S and adjusting the weight update.

Abstract: A neural network is trained to focus on a domain of interest. For example, in a pre-training phase, the neural network in trained using synthetic training data, which is configured to omit or limit content less relevant to the domain of interest, by updating parameters of the neural network to improve the accuracy of predictions. In a subsequent training phase, the pre-trained neural network is trained using real-world training data by updating only a first subset of the parameters associated with feature extraction, while a second subset of the parameters more associated with policies remains fixed.