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: Systems and methods are disclosed for dynamically smoothing images based on network conditions to adjust a bitrate needed to transmit the images. Content in the images is smoothed to reduce the quantity of bits needed to encode each image. Filtering the images modifies regions including content having a high frequency of pixel variation, reducing the frequency, so the pixel colors in the region appear “smoothed” or homogeneous. In other words, a region of an image showing a grassy lawn has a high frequency of variation from pixel to pixel resulting from the fine detail of separate blades of grass that may be similar in color, but not homogeneous. Encoding the region as a single shade of green (or multi-pixel regions of different shades of green) enables a viewer to recognize it as a grassy lawn while greatly reducing the number of bits needed to represent the region.

Abstract: A circuit mask optimizer utilizes a Convolutional Fourier Neural Operator (CFNO) to efficiently learn layout tile dependencies, enabling stitch-less largescale mask optimization with limited intervention of legacy tools. Litho-guided self training via a trained machine learning model provides non-convex optimization, enabling iterative model and dataset refinements at a substantial performance improvement over conventional solutions.

Abstract: Generation of synthetic speech from an input text sequence may be difficult when durations of individual phonemes forming the input text sequence are unknown. A predominantly parallel process may model speech rhythm as a separate generative distribution such that phoneme duration may be sampled at inference. Additional information such as pitch or energy may also be sampled to provide improved diversity for synthetic speech generation.

Abstract: Disclosed are techniques for compressing data of an image. Intermediate pixels may be determined. Each location of the image may be associated with a block of a plurality of blocks of a first size and a block of a plurality of blocks of a second size. For each block of the first size and of the second size, a first cost for a first mode and a second cost for a second mode may be determined in parallel using the intermediate pixels. A final mode and a final block size may be selected for each location of the image using the first cost and the second cost for each of a respective block of the first size and a respective block of the second size associated with a corresponding location. Final pixels may be determined, and a representation of the image may be obtained based on the final pixels.

Abstract: Techniques for isolating interfaces while testing a semiconductor device include a semiconductor device having a link interface that couples the semiconductor device to a high-speed data transfer link, a clock control unit that transmits one or more clock signals to the link interface; and a protection module. The protection module asserts a clock stop request to the clock control unit and, in response to receiving a clock stop acknowledgement from the clock control unit, asserts a clamp enable to cause the link interface to be isolated from portions of the semiconductor device. After waiting for a first predetermined period of time to expire, the protection module de-asserts the clock stop request.

Abstract: In various embodiments, an unsupervised training application executes a neural network on a first point cloud to generate keys and values. The unsupervised training application generates output vectors based on a first query set, the keys, and the values and then computes spatial features based on the output vectors. The unsupervised training application computes quantized context features based on the output vectors and a first set of codes representing a first set of 3D geometry blocks. The unsupervised training application modifies the first neural network based on a likelihood of reconstructing the first point cloud, the quantized context features, and the spatial features to generate an updated neural network. A trained machine learning model includes the updated neural network, a second query set, and a second set of codes representing a second set of 3D geometry blocks and maps a point cloud to a representation of 3D geometry instances.

Abstract: Systems and methods for efficient lossless compression of captured raw image information are presented. A method can comprise: receiving raw image data from an image capture device, segregating the pixel data into a base layer portion and an enhanced layer portion, reconfiguring the base layer portion expressed in the first color space values from a raw capture format into a pseudo second color space compression mechanism compatible format, and compressing the reconfigured base layer portion of first color space values. The raw image data can include pixel data are expressed in first color space values. The segregation can be based upon various factors, including a compression benefits analysis of a boundary location between the base layer portion and enhanced layer portion. The reconfiguring the base layer portion can include separating the base layer portion based upon multiple components within the raw data; and forming base layer video frames from the multiple components.

Abstract: According to an aspect of an embodiment, operations may comprise accessing a set of vehicle poses of one or more vehicles; for each of the set of vehicle poses, accessing a high definition (HD) map of a geographical region surrounding the vehicle pose, with the HD map comprising a three-dimensional (3D) representation of the geographical region, determining a measure of constrainedness for the vehicle pose, with the measure of constrainedness representing a confidence for performing localization for the vehicle pose based on 3D structures surrounding the vehicle pose, and storing the measure of constrainedness for the vehicle pose; and for each of the geographical regions surrounding each of the set of vehicle poses, determining a measure of constrainedness for the geographical region based on measures of constrainedness of vehicle poses within the geographical region, and storing the measure of constrainedness for the geographical region.

Abstract: A remediation system for threshold leaks in a datacenter liquid cooling system is disclosed. The system includes a fluid controller and a power controller that are adapted to receive input from a learning subsystem that can determine that a threshold leak has occurred even though a computing component is functioning normally, so that a change in power state to reduce reliance on the coolant and so that a change of flow of the coolant may be effected.

Abstract: A neural network-based rendering technique increases temporal stability and image fidelity of low sample count path tracing by optimizing a distribution of samples for rendering each image in a sequence. A sample predictor neural network learns spatio-temporal sampling strategies such as placing more samples in dis-occluded regions and tracking specular highlights. Temporal feedback enables a denoiser neural network to boost the effective input sample count and increases temporal stability. The initial uniform sampling step typically present in adaptive sampling algorithms is not needed. The sample predictor and denoiser operate at interactive rates to achieve significantly improved image quality and temporal stability compared with conventional adaptive sampling techniques.

Abstract: In an embodiment, a modular augmented reality display is provided that incorporates prescription eyewear that can be used separately by the wearer. In an embodiment, an image is generated from a removable display attached to the eyewear and directed into the edge of a prescription lens, which 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 includes a wearable belt pouch that includes a battery and support electronics connected to the eyewear so that the weight on the eyewear is reduced.

Abstract: Systems and methods for evaluating cooling characteristics are disclosed. In at least one embodiment, a thermal test vehicle can be used to simulate a thermal performance of a computing unit.

Abstract: To determine a path through a pose configuration space, trajectories of poses may be evaluated in parallel based at least on translating the trajectories along at least one axis of the pose configuration space (e.g., an orientation axis). A trajectory may include at least a portion of a turn having a fixed turn radius. Turns or turn portions that have the same turn radius and initial orientation can be translatively shifted along and processed in parallel along the orientation axis as they are translated copies of each other, but with different starting points. Trajectories may be evaluated based at least on processing variables used to evaluate reachability as bit vectors with threads effectively performing large vector operations in synchronization. A parallel reduction pattern may be used to account for dependencies that may exist between sections of a trajectory for evaluating reachability, allowing for the sections to be processed in parallel.

Abstract: Apparatuses, systems, and techniques are presented to configure computing resources to perform various tasks. In at least one embodiment, an approach presented herein can be used to verify whether a network of computing nodes is properly configured based, at least in part, on one or more expected data strings generated by the network of computing nodes.

Abstract: Apparatuses, systems, and techniques to process packet data in parallel. In at least one embodiment, packet data is processed by (e.g., one or more algorithms expressed in CUDA code executing on) a Graphics Processing Unit (“GPU”).

Abstract: High performance applications—such as cloud game streaming, cloud virtual reality (VR), remote desktop, and others—are sensitive to various network conditions, such as latency, jitter, and packet loss. Systems of the present disclosure may match network characteristics for a user device with latency requirements for a particular application type, and application sessions may be forwarded or distributed to a suitable data center. To accomplish this, application specific network tests may be executed to determine requirements for executing a high performing application session for a user. The result of these tests, in addition to application specific performance requirements, may be used to find a suitable data center—from a set of available data centers—that is capable of hosting the application session without degradation. As a result, efficient use of distributed infrastructures may be accomplished, while avoiding congestion and hot-spots, and providing an optimized application experience for end users.

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: Various embodiments include a memory device that is capable of transferring both commands and data via a single clock signal input. In order to initialize the memory device to receive commands, a memory controller transmits a synchronization command to the memory device. The synchronization command establishes command start points that identify the beginning clock cycle of a command that is transferred to the memory device over multiple clock cycles. Thereafter, the memory controller transmits subsequent commands to the memory device according to a predetermined command length. The predetermined command length is based on the number of clock cycles needed to transfer each command to the memory device. Adjacent command start points are separated from one another by the predetermined command length. In this manner, the memory device avoids the need for a second lower speed clock signal for transferring commands to the memory device.

Abstract: A method for remotely provisioning resources for running a computer application is described. The method includes: causing, using one or more processing units, an initialization of a user interactive video portion of a computer application, the computer application being executed using a remote server; determining a runtime of a static video portion of the computer application and a time required to complete initialization of the user interactive portion using information provided by the remote server; and delaying a start time of displaying the static video portion when the runtime of the static video portion is shorter than the time required to complete the initialization of the user interactive portion. A device that is capable of performing the above method and a server are also described.