Abstract: In the embodiment a determination is made, for one or more applications being executed by the computing system, of an amount of the first or second memory being used by the one or more applications. Based on the determination, a portion of the memory resources of the third memory are configured to function with the first or second memory when it is determined that the amount of the first or second memory being used by the one or more applications is not sufficient for the memory needs of the one or more applications and a portion of the memory resources of the third memory are removed from functioning with the first or second memory when it is determined that the amount of the first or second memory being used by the one or more applications is more than is needed for the memory needs of the one or more applications.

Abstract: In the embodiment a determination is made, for one or more applications being executed by the computing system, of an amount of the first or second memory being used by the one or more applications. Based on the determination, a portion of the memory resources of the third memory are configured to function with the first or second memory when it is determined that the amount of the first or second memory being used by the one or more applications is not sufficient for the memory needs of the one or more applications and a portion of the memory resources of the third memory are removed from functioning with the first or second memory when it is determined that the amount of the first or second memory being used by the one or more applications is more than is needed for the memory needs of the one or more applications.

Abstract: Described herein, are methods and systems for locating a leak in a water distribution network. According to an implementation, a leak situation in the water distribution network is detected based on a flow difference value between an actual flow value and a predicted flow value of an inlet flow meter of the water distribution network at at least one time interval. Leak signature values of demand nodes in the water distribution network at the at least one time interval are determined. A leak signature value of a respective demand node at a respective time interval is determined based on centrality metrics, the predicted flow value at the respective time interval, and static physical properties related to the water distribution network. At least one possible leak node is identified based on the flow difference value and the leak signature values of the demand nodes at the at least one time interval.

Abstract: Aspects extend to methods, systems, and computer program products for predicting solid state drive reliability. Aspects of the invention can be used to predict and/or to configure a data center to minimize one or more of: SSD capacity degradation (how much storage an SSD has left), SSD performance degradation (reduced read/write latency/throughput), and SSD failure. Models and data center considerations can be based on device level SSD related operations, such as, for example, read, write, erase. Operations decisions can be made for a data center based on SSD specific features, such as, for example, remaining capacity, write amplification factor, etc. Dependence and/or causality of various different data center factors can be leveraged. The impact of the various data center factors on different SSD failure modes and capacity/performance degradation can be quantified to drive SSD design, SSD provisioning, and SSD operations.

Abstract: Aspects extend to methods, systems, and computer program products for predicting solid state drive reliability. Aspects of the invention can be used to predict and/or to configure a data center to minimize one or more of: SSD capacity degradation (how much storage an SSD has left), SSD performance degradation (reduced read/write latency/throughput), and SSD failure. Models and data center considerations can be based on device level SSD related operations, such as, for example, read, write, erase. Operations decisions can be made for a data center based on SSD specific features, such as, for example, remaining capacity, write amplification factor, etc. Dependence and/or causality of various different data center factors can be leveraged. The impact of the various data center factors on different SSD failure modes and capacity/performance degradation can be quantified to drive SSD design, SSD provisioning, and SSD operations.

Abstract: Described herein, are methods and systems for locating a leak in a water distribution network. According to an implementation, a leak situation in the water distribution network is detected based on a flow difference value between an actual flow value and a predicted flow value of an inlet flow meter of the water distribution network at at least one time interval. Leak signature values of demand nodes in the water distribution network at the at least one time interval are determined. A leak signature value of a respective demand node at a respective time interval is determined based on centrality metrics, the predicted flow value at the respective time interval, and static physical properties related to the water distribution network. At least one possible leak node is identified based on the flow difference value and the leak signature values of the demand nodes at the at least one time interval.