Abstract: In various examples, users may access a tool that automatically generates video montages from video clips of the user's gameplay according to parameterized recipes. As a result, a user may select—or allow the system to select—clips corresponding to gameplay of the user and customize one or more parameters (e.g., transitions, music, audio, graphics, etc.) of a recipe, and a video montage may be generated automatically according to a montage script output using the recipe. As such, a user may have a video montage generated with little user involvement, and without requiring any skill or expertise in video editing software. In addition, even for experienced video editors, automatic video montage generation may be a useful alternative to save the time and effort of manually curating video montages.

Abstract: The disclosure provides a cloud-based renderer and methods of rendering a scene on a computing system using a combination of raytracing and rasterization. In one example, a method of rendering a scene includes: (1) generating at least one raytracing acceleration structure from scene data of the scene, (2) selecting raytracing and rasterization algorithms for rendering the scene based on the scene data, and (3) rendering the scene utilizing a combination of the raytracing algorithms and the rasterization algorithms, wherein the rasterization algorithms utilize primitive cluster data from the raytracing acceleration structures.

Abstract: A communication method between a source device and a target device utilizes speculative connection setup between the source device and the target device, target-device-side packet ordering, and fine-grained ordering to remove packet dependencies.

Abstract: A computing device comprises: a base portion; a display portion that is movably coupled to the base portion and includes a housing having a movable panel and one or more fixed panels; and a mechanical assembly that positions the movable panel away from the one or more fixed panels as the display portion opens away from the base portion.

Abstract: In various examples, game session audio data—e.g., representing speech of users participating in the game—may be monitored and/or analyzed to determine whether inappropriate language is being used. Where inappropriate language is identified, the portions of the audio corresponding to the inappropriate language may be edited or modified such that other users do not hear the inappropriate language. As a result, toxic behavior or language within instances of gameplay may be censored—thereby enhancing the user experience and making online gaming environments safer for more vulnerable populations. In some embodiments, the inappropriate language may be reported—e.g., automatically—to the game developer or game application host in order to suspend, ban, or otherwise manage users of the system that have a proclivity for toxic behavior.

Abstract: A network device configured to perform scalable, in-network computations is described. The network device is configured to process pull requests and/or push requests from a plurality of endpoints connected to the network. A collective communication primitive from a particular endpoint can be received at a network device. The collective communication primitive is associated with a multicast region of a shared global address space and is mapped to a plurality of participating endpoints. The network device is configured to perform an in-network computation based on information received from the participating endpoints before forwarding a response to the collective communication primitive back to one or more of the participating endpoints. The endpoints can inject pull requests (e.g., load commands) and/or push requests (e.g., store commands) into the network. A multicast capability enables tasks, such as a reduction operation, to be offloaded to hardware in the network device.

Abstract: According to an aspect of an embodiment, operations may comprise receiving a search query for points near a query-point, accessing a compressed octree representation of a point cloud comprising 3D points of a region, and traversing the compressed octree representation to identify regions that overlap a search space by, marking a current node as overlapping the search space responsive to determining that the current node is a leaf node, identifying a child node of the current node and performing a nearest neighbor search in the child node responsive to determining that a region represented by the current node overlaps the search space, and identifying a sibling node of the current node and performing the nearest neighbor search in the sibling node responsive to determining that a region represented by the current node does not overlap the search space.

Abstract: A clock data recovery circuit detects illegal decisions for received data, accumulates a phase gradient for the data, determines a number of the illegal decisions in a configured window for receiving the data, and if the number of the illegal decisions exceeds a pre-defined number in the window, applies a sum of the accumulated phase gradient and a phase increment having a sign of the accumulated phase gradient to a clock circuit for the data receiver.

Abstract: Various embodiments include a modulo operation generator associated with a cache memory in a computer-based system. The modulo operation generator generates a first sum by performing an addition and/or a subtraction function on an input address. A first portion of the first sum is applied to a lookup table that generates a correction value. The correction value is then added to a second portion of the first sum to generate a second sum. The second sum is adjusted, as needed, to be less than the divisor. The adjusted second sum forms a residue value that identifies a cache memory slice in which the input data value corresponding to the input address is stored. By generating the residue value in this manner, the cache memory distributes input data values among the slices in a cache memory even when the number of slices is not a power of two.

Abstract: In various examples, a neural network may be trained for use in vehicle re-identification tasks—e.g., matching appearances and classifications of vehicles across frames—in a camera network. The neural network may be trained to learn an embedding space such that embeddings corresponding to vehicles of the same identify are projected closer to one another within the embedding space, as compared to vehicles representing different identities. To accurately and efficiently learn the embedding space, the neural network may be trained using a contrastive loss function or a triplet loss function. In addition, to further improve accuracy and efficiency, a sampling technique—referred to herein as batch sample—may be used to identify embeddings, during training, that are most meaningful for updating parameters of the neural network.

Abstract: In a ray tracer, to prevent any long-running query from hanging the graphics processing unit, a traversal coprocessor provides a preemption mechanism that will allow rays to stop processing or time out early. The example non-limiting implementations described herein provide such a preemption mechanism, including a forward progress guarantee, and additional programmable timeout options that can be time or cycle based. Those programmable options provide a means for quality of service timing guarantees for applications such as virtual reality (VR) that have strict timing requirements.

Abstract: In various examples, an extensible network traffic engineering platform monitors network traffic and application performance to dynamically update network ingress and egress communication paths for increasing performance of the application—such as a cloud gaming application, a cloud virtual reality (VR) application, and/or another high performance application types. Pluggable, distributed, application-centric network monitors, policy engines, and network configurators are implemented at the edge to detect degraded network and application performance and dynamically update network routing to account for the same.

Abstract: A style-based generative network architecture enables scale-specific control of synthesized output data, such as images. During training, the style-based generative neural network (generator neural network) includes a mapping network and a synthesis network. During prediction, the mapping network may be omitted, replicated, or evaluated several times. The synthesis network may be used to generate highly varied, high-quality output data with a wide variety of attributes. For example, when used to generate images of people's faces, the attributes that may vary are age, ethnicity, camera viewpoint, pose, face shape, eyeglasses, colors (eyes, hair, etc.), hair style, lighting, background, etc. Depending on the task, generated output data may include images, audio, video, three-dimensional (3D) objects, text, etc.

Abstract: Candidate grasping models of a deformable object are applied to generate a simulation of a response of the deformable object to the grasping model. From the simulation, grasp performance metrics for stress, deformation controllability, and instability of the response to the grasping model are obtained, and the grasp performance metrics are correlated with robotic grasp features.

Abstract: Enhanced techniques applicable to a ray tracing hardware accelerator for traversing a hierarchical acceleration structure and its underlying primitives are disclosed. For example, traversal speed is improved by grouping processing of primitives sharing at least one feature (e.g., a vertex or an edge) during ray-primitive intersection testing. Grouping the primitives for ray intersection testing can reduce processing (e.g., projections and transformations of primitive vertices and/or determining edge function values) because at least a portion of the processing results related to the shared feature in one primitive can be used in determine whether the ray intersects another primitive(s). Processing triangles sharing an edge can double the culling rate of the triangles in the ray/triangle intersection test without replicating the hardware.

Abstract: Appearance driven automatic three-dimensional (3D) modeling enables optimization of a 3D model comprising the shape and appearance of a particular 3D scene or object. Triangle meshes and shading models may be jointly optimized to match the appearance of a reference 3D model based on reference images of the reference 3D model. Compared with the reference 3D model, the optimized 3D model is a lower resolution 3D model that can be rendered in less time. More specifically, the optimized 3D model may include fewer geometric primitives compared with the reference 3D model. In contrast with the conventional inverse rendering or analysis-by-synthesis modeling tools, the shape and appearance representations of the 3D model are automatically generated that, when rendered, match the reference images.

Abstract: Alternating Current (AC) light sources can cause images captured using a rolling shutter to include alternating darker and brighter regions—known as flicker bands—due to some sensor rows being exposed to different intensities of light than others. Flicker bands may be compensated for by extracting them from images that are captured using exposures that at least partially overlap in time. Due to the overlap, the images may be subtracted from each other so that scene content substantially cancels out, leaving behind flicker bands. The images may be for a same frame captured by at least one sensor, such as different exposures for a frame. For example, the images used to extract flicker bands may be captured using different exposure times that share a common start time, such as using a multi-exposure sensor where light values are read out at different times during light integration.

Abstract: High quality image rendering can be achieved in part by using inverse transform sampling to direct sampling toward regions of greater importance, such as regions with higher brightness values, to reduce noise and improve convergence. Inverse transform sampling can be achieved more efficiently by reformulating as a ray-tracing problem, using tree traversal units that can be accelerated. A geometric mesh can be generated based on a set of cumulative distribution functions (CDFs) for various rows and columns of pixels in a texture, and individual rays can be traced against this mesh, with those rays having a higher probability of intersection at a point with greater importance, such as a higher brightness value. A probability distribution function to be used for importance sampling can be derived by analyzing partial derivatives of the CDF geometry at the intersection location.

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.

Abstract: An automatic standard cell layout generator that generates circuit layouts for an industry standard cell library on an advanced technology node leverages reinforcement learning (RL) to generate device placements in the layouts and also to fix design rule violations during routing. A genetic algorithm is utilized to generate routing candidates to which a reinforcement learning model is applied to correct the design rule constraint violations incrementally. A design rule checker provides feedback on the violations to the reinforcement learning model and the model learns how to fix the violations. A layout device placer based upon a simulated annealing method may also be utilized.