Abstract: Disclosed techniques relate to orchestrating power consumption reductions across a number of hosts. A number of response levels may be utilized, each having an association to a corresponding set of reduction actions. The impact to customers, hosts, and/or workloads can be computed at run time based on current and/or predicted conditions and workloads, and a particular response level can be selected based on the computed impact. These techniques enable a sufficient, but least impactful response to be employed.

Abstract: Disclosed techniques relate to orchestrating power consumption reductions across a number of hosts. A number of response levels may be utilized, each having an association to a corresponding set of reduction actions. The impact to customers, hosts, and/or workloads can be computed at run time based on current and/or predicted conditions and workloads, and a particular response level can be selected based on the computed impact. These techniques enable a sufficient, but least impactful response to be employed.

Abstract: Disclosed techniques relate to orchestrating power consumption reductions across a number of hosts. A number of response levels may be utilized, each having an association to a corresponding set of reduction actions. The impact to customers, hosts, and/or workloads can be computed at run time based on current and/or predicted conditions and workloads, and a particular response level can be selected based on the computed impact. These techniques enable a sufficient, but least impactful response to be employed.

Abstract: Disclosed techniques relate to managing power within a power distribution system. Power consumption corresponding to devices (e.g., servers) that receive power from an upstream device (e.g., a bus bar) may be monitored (e.g., by a service) to determine when power consumption corresponding to those devices has breached or will likely breach a budgeted threshold corresponding to an amount of power allocated to the upstream device. If the budgeted threshold is breached, or is likely to be breached, the service may initiate operations to distribute power caps for the devices and to initiate a timer. Although distributed, the power caps may be ignored by the devices until they are instructed to enforce the power caps (e.g., upon expiration of the timer). This allows the power consumption of the devices to exceed the budgeted power assigned to the upstream device at least until expiration of the timer while avoiding power outage events.

Abstract: Disclosed techniques relate to managing power within a power distribution system. Power consumption corresponding to devices (e.g., servers) that receive power from an upstream device (e.g., a bus bar) may be monitored (e.g., by a service) to determine when power consumption corresponding to those devices breaches (or approaches) a budget threshold corresponding to an amount of power allocated to the upstream device. If the budget threshold is breached, or is likely to be breached, the service may initiate operations to distribute power caps for the devices and to initiate a timer. Although distributed, the power caps may be ignored by the devices until they are instructed to enforce the power caps (e.g., upon expiration of the timer). This allows the power consumption of the devices to exceed the budgeted power associated with the upstream device at least until expiration of the timer while avoiding power outage events.

Abstract: Disclosed techniques relate to orchestrating power consumption reductions across a number of hosts. A current value for an aggregate power threshold of a plurality of hosts may be identified. During a first time period, an aggregate power consumption of the plurality of hosts may be managed using the current value for the aggregate power threshold. A triggering event indicating a modification to the aggregate power threshold is needed may be detected. A new value for the aggregate power threshold may be determined based on the triggering event. During a second time period, the aggregate power consumption of the plurality of hosts may be managed using the new value for the aggregate power threshold.

Abstract: Disclosed techniques relate to orchestrating power consumption reductions across a number of hosts. A number of response levels may be utilized, each having an association to a corresponding set of reduction actions. The impact to customers, hosts, and/or workloads can be computed at run time based on current and/or predicted conditions and workloads, and a particular response level can be selected based on the computed impact. These techniques enable a sufficient, but least impactful response to be employed.

Abstract: Disclosed techniques relate to orchestrating power consumption reductions across a number of hosts. Power consumption of power-drawing devices (e.g., hosts, servers, etc.) may be monitored with respect to a power threshold. When the current power consumption corresponding to those devices breaches the power threshold, or at any suitable time, the system may identify a set of reduction actions configured to reduce aggregate power consumption. The power threshold may be updated dynamically based on the operational status of related systems and environmental factors. A number of response levels may be utilized, each having an association to a corresponding set of reduction actions. The impact to customers, hosts, and/or workloads can be computed at run time based on current conditions and workloads, and a particular response level can be selected based on the computed impact. These techniques enable a sufficient, but least impactful response to be employed.

Abstract: Disclosed techniques relate to managing power within a power distribution system. Power consumption corresponding to devices (e.g., servers) that receive power from an upstream device (e.g., a bus bar) may be monitored (e.g., by a service) to determine when power consumption corresponding to those devices breaches (or approaches) a budget threshold corresponding to an amount of power allocated to the upstream device. If the budget threshold is breached, or is likely to be breached, the service may initiate operations to distribute power caps for the devices and to initiate a timer. Although distributed, the power caps may be ignored by the devices until they are instructed to enforce the power caps (e.g., upon expiration of the timer). This allows the power consumption of the devices to exceed the budgeted power associated with the upstream device at least until expiration of the timer while avoiding power outage events.

Abstract: In some aspects, techniques may include monitoring a primary load of a datacenter and a reserve load of the datacenter. The primary load and reserve load can be monitored by a computing device. The primary load of the datacenter can be configured to be powered by one or more primary generator blocks having a primary capacity, and the reserve load of the datacenter can be configured to be powered by one or more reserve generator blocks having a reserve capacity. Also, the techniques may include detecting that the primary load of the datacenter exceeds the primary capacity. In addition, the techniques may include connecting the reserve generator blocks to at least one of the primary generator blocks and the primary load using a computing device switch.

Abstract: In some aspects, techniques may include monitoring a primary load of a datacenter and a reserve load of the datacenter. The primary load and reserve load can be monitored by a computing device. The primary load of the datacenter can be configured to be powered by one or more primary generator blocks having a primary capacity, and the reserve load of the datacenter can be configured to be powered by one or more reserve generator blocks having a reserve capacity. Also, the techniques may include detecting that the primary load of the datacenter exceeds the primary capacity. In addition, the techniques may include connecting the reserve generator blocks to at least one of the primary generator blocks and the primary load using a computing device switch.

Abstract: In some aspects, techniques may include monitoring a primary load of a datacenter and a reserve load of the datacenter. The primary load and reserve load can be monitored by a computing device. The primary load of the datacenter can be configured to be powered by one or more primary generator blocks having a primary capacity, and the reserve load of the datacenter can be configured to be powered by one or more reserve generator blocks having a reserve capacity. Also, the techniques may include detecting that the primary load of the datacenter exceeds the primary capacity. In addition, the techniques may include connecting the reserve generator blocks to at least one of the primary generator blocks and the primary load using a computing device switch.

Abstract: A system includes operation of a trained neural network to output a first signal indicative of one or more characteristics of a power signal based on an input plurality of power-related conditions data, determination of a first power supply mode based on the first signal, and control of a power supply to operate in the first power supply mode.

Abstract: A system includes operation of a trained neural network to output a first signal indicative of one or more characteristics of a power signal based on an input plurality of power-related conditions data, determination of a first power supply mode based on the first signal, and control of a power supply to operate in the first power supply mode.

Abstract: A method and system for correcting errors in a memory subsystem in a computer system. Occurrence of correctable memory errors are monitored and a determination is made whether the risk of an occurrence of an uncorrectable memory error is less than a tolerable risk. If the risk of an occurrence of an uncorrectable memory error is not less than the tolerable risk, at least one system level parameter is adjusted to decrease the occurrence of correctable memory errors.

Abstract: One embodiment is a method of dynamically adjusting a rate at which a dynamic random access memory (“DRAM”) module is refreshed in a computer system. The method comprises monitoring a plurality of system conditions; detecting a change in at least one of the monitored system conditions; responsive to the detection, determining an optimum refresh rate for a current state of the computer system; and setting the refresh rate to the determined optimum refresh rate.

Abstract: Embodiments include apparatus, methods, and systems providing a heatsink for electronic heat generating components. In one embodiment, the heatsink includes a metal base having a plurality of grooves, and a plurality of graphite fins connected to the base. The fins thermally dissipate heat from the base and into a surrounding environment. The fins are secured within the grooves with an interference fit produced by thermally expanding the base.