An user profile may be used to adjust one or more system power management settings of an information handling system. An information handling system may transmit one or more user profile credentials. The information handling system may receive user profile data and may compare the user profile data with one or more system characteristics of the information handling system. Based on the comparison of the user profile data with the system characteristics of the information handling system, the information handling system may adjust one or more power management settings of the information handling system.

A position-measuring device includes a graduation carrier having a measuring graduation, position measurement electronics, a data memory and a power supply. The data memory includes a first memory which is a volatile memory for storing additional data, a second memory which is a writable non-volatile memory, and a memory controller for controlling transfer and storage of additional data from the first into the second memory. The power supply includes an input stage, a first output stage for the position measurement electronics, a second output stage for the data memory, and a voltage monitor which will turn off the first output stage of the power supply in response to a drop below a minimum value and signal the drop to the memory controller by a backup signal. In response to the backup signal, the memory controller will transfer additional data from the first memory into the second memory.

A method for monitoring multiple servers in one or more server clusters includes collecting and recording sensor data (SDR data) and storing the SDR as a predetermined file format into a specified storage area. The SDR stored in the specified storage area is analyzed according to a predetermined analysis rule to determine whether the SDR comprises data indicating abnormal functioning on a moment-by-moment basis SDR. When the SDR indicates an abnormality, SDR warning information corresponding to the abnormality SDR is outputted. A server monitoring device utilizing the method and a non-transitory storage medium are also provided.

In an approach to improve multi-data center environments by minimizing the environmental impact of workloads in multi-data center environments embodiments migrate at least a portion of one or more workloads between one or more data centers automatically to maximize a usage of renewable energy based on a predetermined threshold score of input power and a combination of renewal energy sources. Further, embodiments dictate, by a policy engine, where at least a portion of the one or more workloads can be hosted. Additionally, embodiments control, by a scheduling engine, how, when, and where at least a portion of the one or more workloads will migrate, and perform data replication to migrate data between a plurality of data center locations.

A processor in a system is responsive to a coherent memory request buffer having a plurality of entries to store coherent memory requests from a client module and a non-coherent memory request buffer having a plurality of entries to store non-coherent memory requests from the client module. The client module buffers coherent and non-coherent memory requests and releases the memory requests based on one or more conditions of the processor or one of its caches. The memory requests are released to a central data fabric and into the system based on a first watermark associated with the coherent memory buffer and a second watermark associated with the non-coherent memory buffer.

Techniques for managing energy use of a computing deployment are provided. In one embodiment, a computer system can establish a performance model for one or more components of the computing deployment, where the performance model models a relationship between one or more tunable parameters of the one or more components and an end-to-end performance metric, and where the end-to-end performance metric reflects user-observable performance of a service provided by the computing deployment. The computer system can further execute an algorithm to determine values for the one or more tunable parameters that minimize power consumption of the one or more components, where the algorithm guarantees that the determined values will not cause the end-to-end performance metric, as calculated by the performance model, to cross a predefined threshold. The computer system can then enforce the determined values by applying changes to the one or more components.

In one embodiment, a method for increasing power efficiency for an information handling system includes: monitoring, by a host service, one or more performance metrics associated with a memory device of the information handling system, the memory device including a power controller communicably coupled to a management device via a side-band bus; predicting, by the host service, an energy requirement for the memory device based on the one or more performance metrics; generating, by the host service, a power configuration profile based on the energy requirement, the power configuration profile indicating one or more power controller parameters associated with the power controller; sending, by the host service, the power configuration profile to the management device; receiving, by the management device, the power configuration profile; and modifying, by the management device and via the side-band bus, the one or more power controller parameters based on the power configuration profile.

A system includes a multicore chip configured to perform machine learning (ML) operations. The system also includes a power monitoring module configured to measure power consumption of the multicore chip on a main power rail of the multicore chip. The power monitoring module is further configured to assert a signal in response to the measured power consumption exceeding a first threshold. The power monitoring module is further configured to transmit the asserted signal to a power throttling module to initiate a power throttling for the multicore chip.

A computer implemented method of energy consumption analysis of a multi-operator communication network site. The method is performed by receiving total energy consumption values of a multi-operator communication network site, wherein the site is divided into two or more individually and independently managed equipment sections, and the total energy consumption covers energy consumption of the whole site, detecting a change of a first magnitude in the total energy consumption at a first point of time, obtaining, from an external source, information about maintenance work taking place in a first section of the site at the first point of time, concluding that the first magnitude represents a first estimate of energy consumption of the first section of the site, and outputting the first estimate of energy consumption.

A network (101) is composed of a bus branched at one or more points, and one or more nodes are connected to each branch line. An inspection control unit (220) outputs a base signal. An amplification control unit (210) determines an amplification period and an amplification factor based on a parameter, and amplifies the base signal with the determined amplification factor during the determined amplification period. The inspection control unit (220) accepts, as an inspection signal, the base signal whose waveform has changed as a result of flowing though the bus, and judges whether or not there is a new node connected to the bus based on a waveform of the inspection signal.