Abstract: An example device includes a connection engine to establish a secure connection with a second device. The device includes a security engine to determine a shared security state for the first device and the second device based on a security state of the first device and a security state of the second device. The security engine is to detect a change in the security state of the first device should occur. The security engine is to change the shared security state at the first device. The security engine is to indicate to the second device the change in the shared security state at the first device.

Abstract: Systems and methods are described herein to estimate or calculate an execution time for a compute cluster to execute a task based on the number of cores the compute cluster has relative to the number of cores present in a heterogeneous compute cluster for which the time to complete the task was previously measured. In some examples, minimum and maximum scaling ratios are calculated for compute clusters having a different number of cores than a compute cluster for which the time to complete the task has been measured.

Abstract: Systems and methods are described herein to orchestrate the execution of an application, such as a machine learning or artificial intelligence application, using distributed compute clusters with heterogeneous compute resources. A discovery subsystem may identify the different compute resources of each compute cluster. The application is divided into a plurality of workloads with each workload associated with resource demands corresponding to the compute resources of one of the compute clusters. Adaptive modeling allows for hyperparameters to be defined for each workload based on the compute resources associated with the compute cluster to which each respective workload is assigned and the associated dataset.

Abstract: A computing device generating an enhanced reality environment may include, in an example, a processor to execute the enhanced reality environment on the computing device and emulate hardware associated with a real-world mobile computing device within the enhanced reality environment; a network adapter to communicatively couple the computing device to the real-world mobile computing device; and an enhanced reality data capture module to capture data defining the enhanced reality environment and deliver the data to the mobile computing device to be processed by an app associated with the real-world mobile computing device.

Abstract: For each of a number of workloads, time intervals within execution performance information that was collected during execution of the workload on a first hardware platform are correlated with corresponding time intervals within execution performance information that was collected during execution of the workload on a second hardware platform. For a workload, the time intervals within the execution performance information on the second hardware platform are correlated to the time intervals within the execution performance information the first hardware platform during which the same parts of the workload were executed. A machine learning model that outputs predicted performance on the second hardware platform relative to known performance on the first hardware platform is trained. The model is trained from the correlated time intervals within the execution performance information for each workload on the hardware platforms.

Abstract: A peripheral device of a computing device may include a processor; a sharing module to, upon execution of the processor, allow the peripheral device to be shared with an external computing device over a network; and a communication module to, upon execution of the processor: provide data from the peripheral device to a peripheral device hub module of a computing device; and provide communication by the peripheral device with the external computing device.

Abstract: A computing device generating an enhanced reality environment may include, in an example, a processor to execute the enhanced reality environment on the computing device and emulate hardware associated with a real-world mobile computing device within the enhanced reality environment; a network adapter to communicatively couple the computing device to the real-world mobile computing device; and an enhanced reality data capture module to capture data defining the enhanced reality environment and deliver the data to the mobile computing device to be processed by an app associated with the real-world mobile computing device.

Abstract: A peripheral device of a computing device may include a processor; a sharing module to, upon execution of the processor, allow the peripheral device to be shared with an external computing device over a network; and a communication module to, upon execution of the processor: provide data from the peripheral device to a peripheral device hub module of a computing device; and provide communication by the peripheral device with the external computing device.

Abstract: A global network routing system may include a proxy server located in a first region and connected to a network. The proxy server may receive a request from a client in the first region requesting access to the region restricted data restricted according to policies of a second region outside the first region and stored in the second region. The request may include a token authorizing access to a data center servicing the second region and having access to the region restricted data. The proxy server may route the request to the data center based upon the token.

Abstract: A non-volatile main memory stores state information of at least one program executing in the system, and metadata indicating whether a system is to be resumed to a prior state on a next start. As part of restarting the system from a mode in which power is removed from the system, the system is resumed to the prior state using the state information stored in the non-volatile main memory, in response to the metadata indicating that the system is to be resumed to the prior state.

Abstract: In one example, a computer having a processor and a byte-addressable non-volatile read-write main memory. The memory is partitioned into plural regions, each region having at least one defined operational property. At least one of the regions is a metadata region to store plural data sets. Each data set specifies a location in memory, and the at least one operational property, of a corresponding one of the regions.

Abstract: Example implementations relate to booting a system comprising a system-on-a-chip (SOC) device. For example, boot code and system code comprising at least one selected from among an operating system and hypervisor code are stored in an on-chip non-volatile memory of a SoC device. By executing the boot code from the on-chip non-volatile memory, the system is booted from a mode in which power is removed from the system, where the booting includes loading the system code in the SoC device from the on-chip non-volatile memory without accessing storage off the SoC device.

Abstract: As part of starting a system including a system-on-a-chip (SoC) device from a mode in which power is removed from the system, the SoC device determines, based on the metadata, whether to resume the system to a prior system state. In response to the metadata indicating that the system is to be resumed to the prior system state, the system is resumed to the prior system state using system state information stored in the on-chip non-volatile memory.

Abstract: Examples include a system comprising a non-volatile memory and a volatile memory. Examples migrate system memory between the volatile memory and the non-volatile memory. After migration, examples translate virtual addresses to physical memory addresses corresponding to the volatile memory and/or non-volatile memory.

Abstract: Examples include a system comprising a non-volatile memory and a volatile memory. Examples resume the system to a prior state using state information stored in the non-volatile memory. After resuming the system, examples migrate a system memory that is stored in the non-volatile memory to the volatile memory.

Abstract: Example implementations relate to booting a system comprising a system-on-a-chip (SOC) device. For example, boot code and system code comprising at least one selected from among an operating system and hypervisor code are stored in an on-chip non-volatile memory of a SoC device. By executing the boot code from the on-chip non-volatile memory, the system is booted from a mode in which power is removed from the system, where the booting includes loading the system code in the SoC device from the on-chip non-volatile memory without accessing storage off the SoC device.

Abstract: As part of starting a system including a system-on-a-chip (SoC) device fro a mode in which power is removed from the system, the SoC device determines, based on the metadata, whether to resume the system to a prior system state. In response to the metadata indicating that the system is to be resumed to the prior system state, the system is resumed to the prior system state using system state information stored in the on-chip non-volatile memory.

Abstract: A non-volatile main memory stores state information of at least one program executing in the system, and metadata indicating whether a system is to be resumed to a prior state on a next start. As part of restarting the system from a mode in which power is removed from the system, the system is resumed to the prior state using the state information stored in the non-volatile main memory, in response to the metadata indicating that the system is to be resumed to the prior state.

Abstract: In one example, a computer having a processor and a byte-addressable non-volatile read-write main memory. The memory is partitioned into plural regions, each region having at least one defined operational property. At least one of the regions is a metadata region to store plural data sets. Each data set specifies a location in memory, and the at least one operational property, of a corresponding one of the regions.