Abstract: An apparatus for memory management a high-speed fabric controller and a memory controller connected between a high-speed memory and a processor. The memory controller is configured to control processor access to the high-speed memory over a memory bus between the processor and the high-speed memory. The apparatus includes a high-speed data connection between the memory controller and the high-speed fabric controller and a data connection between a tier of persistent data storage and the high-speed fabric controller. The high-speed fabric controller is configured to control data transfers between the tier of persistent data storage over and the high-speed memory independent of the processor.

Abstract: An apparatus for memory management a high-speed fabric controller and a memory controller connected between a high-speed memory and a processor. The memory controller is configured to control processor access to the high-speed memory over a memory bus between the processor and the high-speed memory. The apparatus includes a high-speed data connection between the memory controller and the high-speed fabric controller and a data connection between a tier of persistent data storage and the high-speed fabric controller. The high-speed fabric controller is configured to control data transfers between the tier of persistent data storage over and the high-speed memory independent of the processor.

Abstract: One embodiment provides a method for scalable predictive failure analysis. Embodiments of the method may include gathering memory information for memory on a user computer system having at least one processor. Further, the method includes selecting one or more memory-related parameters. Further still, the method includes calculating based on the gathering and the selecting, a single bit error value for the scalable predictive failure analysis through calculations for each of the one or more memory-related parameters that utilize the memory information. Yet further, the method includes setting, based on the calculating, the single bit error value for the user computer system.

Abstract: One embodiment provides a method for scalable predictive failure analysis. Embodiments of the method may include gathering memory information for memory on a user computer system having at least one processor. Further, the method includes selecting one or more memory-related parameters. Further still, the method includes calculating based on the gathering and the selecting, a single bit error value for the scalable predictive failure analysis through calculations for each of the one or more memory-related parameters that utilize the memory information. Yet further, the method includes setting, based on the calculating, the single bit error value for the user computer system.

Abstract: An approach to determine a power-on-hour offset for a memory device that is newly-installed into a computer system is provided, which subtracts a current power-on-hour count of the memory device from a current power-on-hour value of a power supply that supplies operative power to the memory device within the computer system. In response to the computer system powering down, an accumulated power-on-hour for the memory device is determined by subtracting the power-on-hour offset of the memory from a current power-on-hour value of the computer system power supply. The determined power-on-hour offset and accumulated power-on-hour values are saved into one or more designated bytes of a free area of electrically erasable programmable read-only memory of the memory device that are available for data storage by a memory controller, and wherein data stored therein persists after operative power is lost to the memory device, the memory controller or the computer system.

Abstract: An approach to determine a power-on-hour offset for a memory device that is newly-installed into a computer system is provided, which subtracts a current power-on-hour count of the memory device from a current power-on-hour value of a power supply that supplies operative power to the memory device within the computer system. In response to the computer system powering down, an accumulated power-on-hour for the memory device is determined by subtracting the power-on-hour offset of the memory from a current power-on-hour value of the computer system power supply. The determined power-on-hour offset and accumulated power-on-hour values are saved into one or more designated bytes of a free area of electrically erasable programmable read-only memory of the memory device that are available for data storage by a memory controller, and wherein data stored therein persists after operative power is lost to the memory device, the memory controller or the computer system.

Abstract: An approach to determine a power-on-hour offset for a memory device that is newly-installed into a computer system is provided, which subtracts a current power-on-hour count of the memory device from a current power-on-hour value of a power supply that supplies operative power to the memory device within the computer system. In response to the computer system powering down, an accumulated power-on-hour for the memory device is determined by subtracting the power-on-hour offset of the memory from a current power-on-hour value of the computer system power supply. The determined power-on-hour offset and accumulated power-on-hour values are saved into one or more designated bytes of a free area of electrically erasable programmable read-only memory of the memory device that are available for data storage by a memory controller, and wherein data stored therein persists after operative power is lost to the memory device, the memory controller or the computer system.

Abstract: One embodiment provides a method for scalable predictive failure analysis. Embodiments of the method may include gathering memory information for memory on a user computer system having at least one processor. Further, the method includes selecting one or more memory-related parameters. Further still, the method includes calculating based on the gathering and the selecting, a single bit error value for the scalable predictive failure analysis through calculations for each of the one or more memory-related parameters that utilize the memory information. Yet further, the method includes setting, based on the calculating, the single bit error value for the user computer system.

Abstract: One embodiment provides an error detection method wherein single-bit errors in a memory module are detected and identified as being a random error or a repeat error. Each identified random error and each identified repeat error occurring in a time interval is counted. An alert is generated in response to a number of identified random errors reaching a random-error threshold or a number of identified repeat errors reaching a repeat-error threshold during the predefined interval. The repeat-error threshold is set lower than the random-error threshold. A hashing process may be applied to the memory address of each detected error to map the location of the error in the memory system to a corresponding location in an electronic table.

Abstract: One embodiment provides a method for scalable predictive failure analysis. Embodiments of the method may include gathering memory information for memory on a user computer system having at least one processor. Further, the method includes selecting one or more memory-related parameters. Further still, the method includes calculating based on the gathering and the selecting, a single bit error value for the scalable predictive failure analysis through calculations for each of the one or more memory-related parameters that utilize the memory information. Yet further, the method includes setting, based on the calculating, the single bit error value for the user computer system.

Abstract: One embodiment provides an error detection method wherein single-bit errors in a memory module are detected and identified as being a random error or a repeat error. Each identified random error and each identified repeat error occurring in a time interval is counted. An alert is generated in response to a number of identified random errors reaching a random-error threshold or a number of identified repeat errors reaching a repeat-error threshold during the predefined interval. The repeat-error threshold is set lower than the random-error threshold. A hashing process may be applied to the memory address of each detected error to map the location of the error in the memory system to a corresponding location in an electronic table.