A method for performing stutter of dynamic random access memory (DRAM) where a system on a chip (SOC) initiates bursts of requests to the DRAM to fill buffers to allow the DRAM to self-refresh is disclosed. The method includes issuing, by a system management unit (SMU), a ForceZQCal command to the memory controller to initiate the stutter procedure in response to receiving a timeout request, such as an SMU ZQCal timeout request, periodically issuing a power platform threshold (PPT) request, by the SMU, to the memory controller, and sending a ForceZQCal command prior to a PPT request to ensure re-training occurs after ZQ Calibration. The ForceZQCal command issued prior to PPT request may reduce the latency of the stutter. The method may further include issuing a ForceZQCal command prior to each periodic re-training.

A basic input/output system provides an interface for a core aggregation layout that identifies a grouping of processor cores into core aggregations, wherein each of the core aggregations is associated with a maximum allowable C-state. A processor may monitor an information handling system during operation of an application to gather data associated with latency sensitivity of the application, update the core aggregation layout based on the data gathered during the operation of the application, and pin a thread for execution to one of the processor cores based on the latency sensitivity of the application and the maximum allowable C-state.

A hierarchical representation of entities relate to development of at least one product. A portion of a document is selected. For the selected portion of the document, an indication associated with at least one of the entities in the hierarchical representation is received. Based on the received indication, a link is created between the selected portion of the document and the at least one of the entities in the hierarchical representation.

A process for service chain instance pool sizing includes receiving service requests, communicated in a 5G network, into a buffer of a request handler of the 5G network. The service requests are for processing by a service function chain. The request handler is configured to relay received service requests to a pool of service chain instances of the service function chain. The process determines an average number of service requests to be processed by the service function chain, determines a number of service chain instances to exist in the pool as a composite of (i) service chain instances to process service requests making an initial relay through the service function chain and (ii) service chain instances to process service requests that were re-introduced into the buffer after having previously arrived, and indicates this composite number to a broker component that controls the number of service chain instances in the pool.

An information handling system includes a general storage for storing application data of applications hosted by the information handling system. The information handling system also includes a management storage for storing management data used to manage operation of the information handling system. The information handling system further includes a management storage manager that obtains data for storage in the management storage; encrypts the data to obtain encrypted data and authentication data for the encrypted data; generates error correction code data for the encrypted data and the authentication data; and stores, as a new record, the encrypted data, the authentication data, and the error correction code data in the management storage.

A method comprising: obtaining a first instruction for a first service, the first instruction being associated with a routing preference; generating a second instruction for the first service based on the first instruction; associating the second instruction with the routing preference; and providing the second instruction to the first service, wherein associating the second instruction with the routing preference includes at least one of inserting an indication of the routing preference in the second instruction.

In general, embodiments disclosed herein relate to using high bandwidth memory (HBM) in a booting process. In embodiments disclosed herein, a region of the HBM is set aside as an additional memory pool (also referred to as a pool) for drivers and/or other memory heap requests in the booting process. One or more embodiments maintain the existing memory pool below four GB, but provide an additional resource for drivers and heap requests.

A method, system and apparatus for protecting from out of bounds memory references, including establishing a threshold number of active objects for examination for an out of bounds memory reference, determining whether a number of active objects for an application exceeds the threshold, and when the number of active objects exceeds the threshold, storing at least part of information about the active objects in an overflow table in a memory.

The disclosed systems and methods provide a cloud-based framework for the creation and/or enhancement of high quality media content for dissemination over a computerized network. The disclosed framework is configured to operate in accordance with at least one of a content creation, content enhancement and/or rendering template. Such templates can function as rules engines that call specific types of ML or AI algorithms or routines that modify the input data according to the type of template being used. Thus, the disclosed framework can be utilized for creating new high-quality media, improving upon existing media and/or reformatting media for rendering upon dissemination.

A closed-loop service, referred to as an Adaptive Data Analytics Service (ADAS), characterizes the performance of a system or systems by providing information describing how users or agents are operating the system, how the system components interact, and how these respond to external influences and factors. The ADAS then builds models and/or defines relationships that can be used to optimize performance and/or to predict the results of changes made to the system(s). Subsequently, this learning provides the basis for administering, maintaining, and/or adjusting the system(s) under study. Measurement can be ongoing, even after the operating parameters or controls of a system under the administration or monitoring of the ADAS have been adjusted, so that the impact of such adjustments can be determined. This recursive process of observation, analysis, and adjustment provides a closed-loop system that affords adaptability to changing operating conditions and facilitates self-regulation and self-adjustment of systems.