Abstract: A process to ameliorate scoreboard aliasing in multi-threaded data processors whereby, in response to executing at least one long-latency instruction in a first thread, a shared hardware scoreboard is incremented. A shared software register is incremented and the shared software register is spilled to a first per-thread register, and execution is switched to a second thread. After execution switches back to the first thread, execution of the first thread is suspended until the shared hardware scoreboard reaches a value at or below a difference between a value in the shared software register and the value spilled into the first per-thread register.

Abstract: In various examples, systems and methods are disclosed relating to error concealment by replacing a lost video frame region with a chronological predecessor. Network packets including data corresponding to an encoded bitstream of a frame of a video stream can be received. In response to determining that at least one packet of the video stream has been lost, a region of the video frame corresponding to the lost network packet can be replaced with the same region of a previous frame of the video stream.

Abstract: In various examples, systems and methods are disclosed relating to improving perceived video quality through temporal redistribution of network packet payloads that may carry error mitigation data. A subset of network packets for an encoded video stream is identified from a sequence of network packets as corresponding to a region of a video frame of the encoded video stream. A transmission order for the sequence of network packets is determined based at least on the subset of network packets and one or more error correction packets corresponding to the sequence of network packets. The sequence of network packets is transmitted to a receiver client device according to the transmission order.

Abstract: systems, computer program products, and methods are described for an endpoint device configured for secure data transmission within a network. An example endpoint device may include a network interface configured to receive a communication request from a peer endpoint device, and an access control unit configured to determine whether a peer endpoint device is IDE qualified based on the communication request. If the peer endpoint device is IDE qualified, the access control unit authorizes the communication request, allowing secure communication between the devices. If the peer endpoint device is not IDE qualified, the access control unit transmits the communication request to a root port for further authorization, verifying that only IDE-qualified devices are permitted to communicate directly.

Abstract: Systems and methods for cooling a datacenter are disclosed. In at least one embodiment, multiple parallel refrigerant paths are associated with one or more flow controllers to cool multiple computing devices associated therewith, so that one or more flow controllers can distribute equal measures of a liquid phase of refrigerant, relative to a vapor phase of a refrigerant, to such parallel refrigerant paths based in part on a cooling requirement from at least one of such multiple computing devices.

Abstract: A machine-learning control system is trained to perform a task using a simulation. The simulation is governed by parameters that, in various embodiments, are not precisely known. In an embodiment, the parameters are specified with an initial value and expected range. After training on the simulation, the machine-learning control system attempts to perform the task in the real world. In an embodiment, the results of the attempt are compared to the expected results of the simulation, and the parameters that govern the simulation are adjusted so that the simulated result matches the real-world attempt. In an embodiment, the machine-learning control system is retrained on the updated simulation. In an embodiment, as additional real-world attempts are made, the simulation parameters are refined and the control system is retrained until the simulation is accurate and the control system is able to successfully perform the task in the real world.

Abstract: Traditionally, a software application is developed, tested, and then published for use by end users. Any subsequent update made to the software application is generally in the form of a human programmed modification made to the code in the software application itself, and further only becomes usable once tested, published, and installed by end users having the previous version of the software application. This typical software application lifecycle causes delays in not only generating improvements to software applications, but also to those improvements being made accessible to end users. To help avoid these delays and improve performance of software applications, deep learning models may be made accessible to the software applications for use in providing inferenced data to the software applications, which the software applications may then use as desired. These deep learning models can furthermore be improved independently of the software applications using manual and/or automated processes.

Abstract: A system can include a memory and a processing device, operatively coupled to the memory, to perform operations including receiving a header block of an ordered set of blocks. The header block includes a header block payload and a first digest. The operations further include authenticating, based on the header block payload, the header block, and receiving a first data block of the ordered set of blocks. The first data block includes a first data block payload and a second digest. The operations further include authenticating, based on the first digest, the first data block, and processing the first data block payload.

Abstract: To ensure proper operation (e.g., speed and/or function) of standard cells fabricated within an integrated circuit a minimum potential difference between the high and low power supply rails needs to be maintained. IR drop refers to a reduction in the potential difference between the power supply rails and is caused when the switching activity of cells that share a power supply rail is greater than can be provided at a particular time. Before fabrication, placement of the cells is reorganized within bounding box regions. Power density across the power rails within each bounding box is normalized based on spatial and temporal power density characteristics of each cell. The reorganization is IR aware and has minimal impact on timing and IR drop is mitigated because distributing current consumption between the supply rails reduces current spikes and IR drops.

Abstract: Systems, computer program products, and methods are described for secure data transmission. An example system includes a first end-point device, an intermediate device, and a second-end point device. The first end-point device determines the format requirements of the communication link between the first end-point device and the intermediate device, and the communication link intermediate device and the second end-point device. Based on the format requirements, the first end-point device configures the data packet for transmission, such that the data packet, when received at the intermediate device, is re-configured and routed to the second end-point device. When the second end-point device receives the data packet, it verifies the data packet to confirm that the packet has maintained its integrity throughout transit.

Abstract: In various examples, an end-to-end perception evaluation system for autonomous and semi-autonomous machine applications may be implemented to evaluate how the accuracy or precision of outputs of machine learning models—such as deep neural networks (DNNs)—impact downstream performance of the machine when relied upon. For example, decisions computed by the system using ground truth output types may be compared to decisions computed by the system using the perception outputs. As a result, discrepancies in downstream decision making of the system between the ground truth information and the perception information may be evaluated to either aid in updating or retraining of the machine learning model or aid in generating more accurate or precise ground truth information.

Abstract: In various examples, motifs, watermarks, and/or signature inputs are applied to a deep neural network (DNN) to detect faults in underlying hardware and/or software executing the DNN. Information corresponding to the motifs, watermarks, and/or signatures may be compared to the outputs of the DNN generated using the motifs, watermarks and/or signatures. When a the accuracy of the predictions are below a threshold, or do not correspond to the expected predictions of the DNN, the hardware and/or software may be determined to have a fault—such as a transient, an intermittent, or a permanent fault. Where a fault is determined, portions of the system that rely on the computations of the DNN may be shut down, or redundant systems may be used in place of the primary system. Where no fault is determined, the computations of the DNN may be relied upon by the system.

Abstract: Approaches in accordance with various illustrative embodiments provide for the management of active connections in a network environment. In particular, various embodiments implement keep alive functionality in components such as network processing units (NPUs) of network devices such as routers and switches, instead of host processors for those devices. When a status message is received, such as a hello message, the NPU can set or refresh a hit bit in a table entry for a given connection with a peer device. If a subsequent status message is not received within a keep alive interval of the last received status message, then the NPU can determine that the connection with the peer device is stale and can inform the host processor that the connection is no longer available for routing network traffic. The status messages are terminated in the NPU and prevented from being received and processed by the host processor.

Abstract: Various embodiments include a parallel processing computer system that enables parallel instances of a program to synchronize at disparate addresses in memory. When the parallel program instances need to exchange data, the program instances synchronize based on a mask that identifies the program instances that are synchronizing. As each program instance reaches the point of synchronization, the program instance blocks and waits for all other program instances to reach the point of synchronization. When all program instances have reached the point of synchronization, at least one program instance executes a synchronous operation to exchange data. The program instances then continue execution at respective and disparate return addresses.

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: Apparatuses, systems, and techniques to perform effective tone management for image data. In an embodiment, a set of contrast gain curves are generated corresponding to a set of tonal ranges of an input image. An output image may then be generated by at least applying corresponding contrast gain curves to tonal ranges of the input image.

Abstract: A method of compression includes compressing a captured image from a first bit-depth at which it was captured to a second bit-depth that is less than the first bit-depth. The compression comprises applying, according to a power curve, a first compression amount to a first region of the captured image having a first pixel value; and applying, according to the power curve, a second compression amount to a second part of the captured image having a higher second pixel value, wherein the first compression amount is lower than the second compression amount.

Abstract: Embodiments of the present disclosure relate to parallel mask rule checking on evolving mask shapes in optical proximity correction (OPC) flows for integrated circuit designs. Systems and methods are disclosed that perform mask (manufacturing) rule checks (MRC) in parallel, sharing information to maintain symmetry when violations are corrected. In an embodiment the shared information is also used to minimize changes to the geometric area of proposed mask shapes resulting from the OPC. In contrast to conventional systems, MRC is performed for multiple edges in parallel, sharing information between the different edges to encourage symmetry. In an embodiment, all edges may be adjusted in parallel to reduce mask-edge traversal bias.

Abstract: Approaches presented herein provide for semantic data matching, as may be useful for selecting data from a large unlabeled dataset to train a neural network. For an object detection use case, such a process can identify images within an unlabeled set even when an object of interest represents a relatively small portion of an image or there are many other objects in the image. A query image can be processed to extract image features or feature maps from only one or more regions of interest in that image, as may correspond to objects of interest. These features are compared with images in an unlabeled dataset, with similarity scores being calculated between the features of the region(s) of interest and individual images in the unlabeled set. One or more highest scored images can be selected as training images showing objects that are semantically similar to the object in the query image.

Abstract: Apparatuses, systems, and techniques to perform signal processing operations in a fifth generation (“5G”) radio signal. In at least one embodiment, one or more processors equalize, in parallel, one or more 5G radio signals.