Abstract: A fully-connected neural network may be configured for execution by a processor as a fully-fused neural network by limiting slow global memory accesses to reading and writing inputs to and outputs from the fully-connected neural network. The computational cost of fully-connected neural networks scale quadratically with its width, whereas its memory traffic scales linearly. Modern graphics processing units typically have much greater computational throughput compared with memory bandwidth, so that for narrow, fully-connected neural networks, the linear memory traffic is the bottleneck. The key to improving performance of the fully-connected neural network is to minimize traffic to slow “global” memory (off-chip memory and high-level caches) and to fully utilize fast on-chip memory (low-level caches, “shared” memory, and registers), which is achieved by the fully-fused approach.

Abstract: Disclosed are apparatuses, systems, and techniques to render images with global illumination using efficient ray tracing, light source identification, and reservoir resampling that deploys temporal and spatial reservoirs.

Abstract: A system is provided for monitoring and controlling program flow in an event-triggered system. A program (e.g., application, algorithm, routine, etc.) may be organized into operational units (e.g., nodes executed by one or more processors), each of which tasked with executing one or more respective events (e.g., tasks) within the larger program. At least some of the events of the larger program may be successively executed in a flow, one after another, using triggers sent directly from one node to the next. In addition, the system of the present disclosure may include a manager that may exchange communications with the nodes to monitor or assess a status of the system (e.g., determine when a node has completed an event) or to control or trigger a node to initiate an event.

Abstract: A host may use address translation to convert virtual addresses to physical addresses for endpoints, which may then submit memory access requests for physical addresses. The host may incorporate the physical address and a signature of the physical address generated using a private key into a translated address field of a response to a translation request. An endpoint may treat the combination as a translated address by storing it in an entry of a translation cache, and accessing the entry for inclusion in a memory access request. The host may generate a signature of the translated address from the request using the private key, with the result being compared to the signature from the request. The memory access request may be verified when the compared values match, and the memory access may be performed using the translated address.

Abstract: In various examples, a yield scenario may be identified for a first vehicle. A wait element is received that encodes a first path for the first vehicle to traverse a yield area and a second path for a second vehicle to traverse the yield area. The first path is employed to determine a first trajectory in the yield area for the first vehicle based at least on a first location of the first vehicle at a time and the second path is employed to determine a second trajectory in the yield area for the second vehicle based at least on a second location of the second vehicle at the time. To operate the first vehicle in accordance with a wait state, it may be determined whether there is a conflict between the first trajectory and the second trajectory, where the wait state defines a yielding behavior for the first vehicle.

Abstract: In various examples, sensor data recorded in the real-world may be leveraged to generate transformed, additional, sensor data to test one or more functions of a vehicle—such as a function of an AEB, CMW, LDW, ALC, or ACC system. Sensor data recorded by the sensors may be augmented, transformed, or otherwise updated to represent sensor data corresponding to state information defined by a simulation test profile for testing the vehicle function(s). Once a set of test data has been generated, the test data may be processed by a system of the vehicle to determine the efficacy of the system with respect to any number of test criteria. As a result, a test set including additional or alternative instances of sensor data may be generated from real-world recorded sensor data to test a vehicle in a variety of test scenarios—including those that may be too dangerous to test in the real-world.

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: This application discloses techniques for generating and querying projective hash maps. More specifically, projective hash maps can be used for spatial hashing of data related to N-dimensional points. Each point is projected onto a projection surface to convert the three-dimensional (3D) coordinates for the point to two-dimensional (2D) coordinates associated with the projection surface. Hash values based on the 2D coordinates are then used as an index to store data in the projective hash map. Utilizing the 2D coordinates rather than the 3D coordinates allows for more efficient searches to be performed to locate points in the 3D space. In particular, projective hash maps can be utilized by graphics applications for generating images, and the improved efficiency can, for example, enable a game streaming application on a server to render images transmitted to a user device via a network at faster frame rates.

Abstract: According to an aspect of an embodiment, operations may comprise receiving an approximate geographic location of a vehicle, accessing a map of a region within which the approximate geographic location of the vehicle is located, identifying a first region on the map within a first threshold distance of the approximate geographic location of the vehicle, identifying a second region on the map associated with one or more roads on the map, determining a search space on the map within which the vehicle is likely to be present, the search space representing an intersection of the first region and the second region, and determining a more accurate geographic location of the vehicle by performing a search within the search space.

Abstract: In various examples, live perception from sensors of a vehicle may be leveraged to detect and classify intersection contention areas in an environment of a vehicle in real-time or near real-time. For example, a deep neural network (DNN) may be trained to compute outputs—such as signed distance functions—that may correspond to locations of boundaries delineating intersection contention areas. The signed distance functions may be decoded and/or post-processed to determine instance segmentation masks representing locations and classifications of intersection areas or regions. The locations of the intersections areas or regions may be generated in image-space and converted to world-space coordinates to aid an autonomous or semi-autonomous vehicle in navigating intersections according to rules of the road, traffic priority considerations, and/or the like.

Abstract: Apparatuses, systems, and techniques to animate objects in computer-generated graphics. In at least one embodiment, one or more neural networks are trained to identify one or more forces to be applied to one or more objects based, at least in part, on training data corresponding to two or more aspects of motion of the one or more objects.

Abstract: In various examples, optical flow estimate (OFE) quality is improved when employing a hint-based algorithm in multi-level hierarchical motion estimation by using different scan orders at different resolution levels. A scan of an image performed with a scan order may initially leverage OFEs from a previous scan of the image, where the previous scan was performed using a different scan order. The OFEs leveraged from the previous scan are more likely to be of high accuracy until sufficient spatial hints are available to the hint-based algorithm for the scan to reduce the impact of potentially lower quality OFEs resulting from the different scan order of the previous scan.

Abstract: A weighted average execution time associated with each execution stage of a plurality of execution stages used to process a plurality of frames in parallel is obtained. The processing of each of the plurality of frames is performed at each of the plurality of execution stages in a sequential order, starting with an initial execution stage and continuing with each subsequent execution stage. A first largest weighted average execution time associated with one of the plurality of execution stages is determined. A delay to the initial execution stage prior to processing a first next frame is applied. The delay is determined based on the first largest weighted average execution time.

Abstract: Apparatuses, systems, and techniques to render images. In at least one embodiment, at least one visibility parameter determined for a first image region is reused for a different second image region that neighbors the first image region (e.g., spatially and/or temporally).

Abstract: User interfaces and methods are disclosed. In some embodiments, a plurality of source artifacts is displayed. A selector is operable to indicate a selected set of the source artifacts. An output artifact is displayed having an output attribute that represents a combination of source attributes from the source artifacts in the selected set. An amount of contribution to the first output attribute by respective ones of the source artifacts in the first selected set is based on a coordinate of the selector relative to coordinates of the source attributes in the first selected set.

Abstract: In various embodiments, a finite aperture omni-directional camera is modeled by aligning a finite aperture lens and focal point with the omni-directional part of the projection. For example, each point on an image plane maps to a direction in camera space. For a spherical projection, the lens can be orientated along this direction and the focal point is picked along this direction at focal distance from the lens. For a cylindrical projection, the lens can be oriented along the projected direction on the two dimensional (2D) xz-plane, as the projection is not omni-directional in the y direction. The focal point is picked along the (unprojected) direction so its projection on the xz-plane is at focal distance from the lens. The final outgoing ray can be constructed by sampling of point on this oriented lens and shooting a ray from there through the focal point.

Abstract: In various examples, systems and methods are disclosed that preserve rich spatial information from an input resolution of a machine learning model to regress on lines in an input image. The machine learning model may be trained to predict, in deployment, distances for each pixel of the input image at an input resolution to a line pixel determined to correspond to a line in the input image. The machine learning model may further be trained to predict angles and label classes of the line. An embedding algorithm may be used to train the machine learning model to predict clusters of line pixels that each correspond to a respective line in the input image. In deployment, the predictions of the machine learning model may be used as an aid for understanding the surrounding environment—e.g., for updating a world model—in a variety of autonomous machine applications.

Abstract: While one type of input, either a mouse input or a joystick input, may be preferred for one type of a game, it may not be preferred, or even compatible, for another type of a game. Introduced herein is a game controller that employs a dedicated input, which is capable of the absolute accuracy of a mouse input or trackball input, but is also capable of measuring how far off center the input is (e.g., how far off center it has moved), and can also return to center when released, as is present in a joystick input. The introduced game controller integrates a touch sensing trackball to enjoy the benefits of both the mouse type input and joystick type input, in a single dedicated input, providing a user freedom to play any type of game without worrying about the compatibility of their game controllers.

Abstract: In various examples, information may be received for a 3D model, such as 3D geometry information, lighting information, and material information. A machine learning model may be trained to disentangle the 3D geometry information, the lighting information, and/or material information from input data to provide the information, which may be used to project geometry of the 3D model onto an image plane to generate a mapping between pixels and portions of the 3D model. Rasterization may then use the mapping to determine which pixels are covered and in what manner, by the geometry. The mapping may also be used to compute radiance for points corresponding to the one or more 3D models using light transport simulation. Disclosed approaches may be used in various applications, such as image editing, 3D model editing, synthetic data generation, and/or data set augmentation.

Abstract: The present invention facilitates efficient and effective image processing. A network can comprise: a first system configured to perform a first portion of lighting calculations for an image and combing results of the first portion of lighting calculations for the image with results of a second portion of lighting calculations; and a second system configured to perform the second portion of lighting calculations and forward the results of the second portion of the lighting calculations to the first system. The first and second portion of lighting calculations can be associated with indirect lighting calculations and direct lighting calculations respectively. The first system can be a client in a local location and the second system can be a server in a remote location (e.g., a cloud computing environment). The first system and second system can be in a cloud and a video is transmitted to a local system.