Abstract: A computer-implemented method, and a computer system are provided for implementing dynamic and automatic altering a user profile based on machine learning and cognitive analysis to improve user performance. The user profile is dynamically altered based upon live data from multiple external data sources using machine learning and cognitive application programming interfaces (APIs) without explicit input from the user. The altered user profile is automatically stored for the user. The stored user profile is deployed for multiple selected user applications enabling enhanced performance for the user.

Abstract: Techniques are disclosed for performing dump collection on a computing system. One technique includes detecting an error event on the computing system. After detecting the error event, a subset of hardware registers associated with the error event are determined. One or more hardware units within the computing system to capture data from are determined from a set of rules that specify an association between the one or more hardware units and the subset of hardware registers associated with the error event. Data is captured from each of the one or more hardware units.

Abstract: Techniques are disclosed for performing dump collection on a computing system. One technique includes detecting an error event on the computing system. After detecting the error event, a subset of hardware registers associated with the error event are determined. One or more hardware units within the computing system to capture data from are determined from a set of rules that specify an association between the one or more hardware units and the subset of hardware registers associated with the error event. Data is captured from each of the one or more hardware units.

Abstract: A computer-implemented method, and a computer system are provided for implementing dynamic and automatic altering a user profile based on machine learning and cognitive analysis to improve user performance. The user profile is dynamically altered based upon live data from multiple external data sources using machine learning and cognitive application programming interfaces (APIs) without explicit input from the user. The altered user profile is automatically stored for the user. The stored user profile is deployed for multiple selected user applications enabling enhanced performance for the user.

Abstract: A computer-implemented method, and a computer system are provided for implementing dynamic and automatic altering a user profile based on machine learning and cognitive analysis to improve user performance. The user profile is dynamically altered based upon live data from multiple external data sources using machine learning and cognitive application programming interfaces (APIs) without explicit input from the user. The altered user profile is automatically stored for the user. The stored user profile is deployed for multiple selected user applications enabling enhanced performance for the user.

Abstract: Methods and arrangements to collect data related to the state or conditions of a system are described herein. Embodiments may comprise a data identifier to identify data to collect in response to an event and a data collector to collect the identified data. The data collector may comprise firmware, code in ROM, a state machine, and/or other logic, and the data identifier may also comprise firmware, code in ROM, a state machine, and/or other logic that may access information and/or code in a file or other data storage to identify the data to collect. The data storage may comprise information and/or code to identify the location of data to collect and, in some embodiments, the sequence with which to collect the data. For example, such a file may comprise an address or address range within memory of a specific component of the system such as a memory controller.

Abstract: Methods and arrangements to collect data related to the state or conditions of a system are described herein. Embodiments may comprise a data identifier to identify data to collect in response to an event and a data collector to collect the identified data. The data collector may comprise firmware, code in ROM, a state machine, and/or other logic, and the data identifier may also comprise firmware, code in ROM, a state machine, and/or other logic that may access information and/or code in a file or other data storage to identify the data to collect. The data storage may comprise information and/or code to identify the location of data to collect and, in some embodiments, the sequence with which to collect the data. For example, such a file may comprise an address or address range within memory of a specific component of the system such as a memory controller.

Abstract: Embodiments may comprise a data identifier to identify data to collect in response to an event and a data collector to collect the identified data. The data collector may comprise firmware, code in ROM, a state machine, and/or other logic, and the data identifier may also comprise firmware, code in ROM, a state machine, and/or other logic that may access information and/or code in a file or other data storage to identify the data to collect. The data storage may comprise information and/or code to identify the location of data to collect and, in some embodiments, the sequence with which to collect the data.

Abstract: A method of processing data is proposed. In response to determining that a reconfiguration of a data processing system has occurred, one or more system items are surveyed to identify a change to the data processing system. One or more requests for status instructions for the one or more system items are generated, and the status instructions are compiled into a data structure. In response to determining that a status instruction is present in the data structure for which no status data has been collected, a method of collection for the instruction is determined, the collection is performed according to the method to obtain the status data, and the status data is compiled in a dump data structure.

Abstract: A modular computing housing includes a housing structure having a plurality of component slots that each can receive one of a plurality of components, where at least one of the components includes a processor having an operating frequency. A cooling system provides airflow through each of the component slots. A thermal control system can be communicably connected to each of the component slots and each of the received component processors. The thermal control system receives configuration data from each of the component slots, retrieves throttle data corresponding to the configuration data, and directs at least one received component processors to reduce its operating frequency in accordance with the throttle data.

Abstract: A method for recovering from software and/or hardware failures occurred in a data processing system is disclosed. A current version of boot code and an updated version of boot code are stored in a first memory region and a second memory region, respectively, of a non-volatile memory of the data processing system. The updated version of boot code is periodically replaced by a latest version of boot code downloaded from a support center. After an occurrence of a system crash, a determination is made if the system crash was caused by a known problem that can be remedied by the updated version of boot code. If so, the data processing system is rebooted using the updated version of boot code. Otherwise, data related to the system crash is collected, and the data processing system is rebooted using the current version of boot code.

Abstract: A method for recovering from software and/or hardware failures occurred in a data processing system is disclosed. A current version of boot code and an updated version of boot code are stored in a first memory region and a second memory region, respectively, of a non-volatile memory of the data processing system. The updated version of boot code is periodically replaced by a latest version of boot code downloaded from a support center. After an occurrence of a system crash, a determination is made if the system crash was caused by a known problem that can be remedied by the updated version of boot code. If so, the data processing system is rebooted using the updated version of boot code. Otherwise, data related to the system crash is collected, and the data processing system is rebooted using the current version of boot code.

Abstract: A modular computing housing includes a housing structure having a plurality of component slots that each can receive one of a plurality of components, where at least one of the components includes a processor having an operating frequency. A cooling system provides airflow through each of said component slots. A thermal control system can be communicably connected to each of the component slots and each of the received component processors. When the thermal control system receives configuration data from each of the component slots, retrieves throttle data corresponding to the configuration data and directs at least one received component processors to reduce its operating frequency in accordance with the throttle data.

Abstract: A method of processing data is proposed. In response to determining that a reconfiguration of a data processing system has occurred, one or more system items are surveyed to identify a change to the data processing system. One or more requests for status instructions for the one or more system items are generated, and the status instructions are compiled into a data structure. In response to determining that a status instruction is present in the data structure for which no status data has been collected, a method of collection for the instruction is determined, the collection is performed according to the method to obtain the status data, and the status data is compiled in a dump data structure.

Abstract: A method of processing data is proposed. In response to determining that a reconfiguration of a data processing system has occurred, one or more system items are surveyed to identify a change to the data processing system. One or more requests for status instructions for the one or more system items are generated, and the status instructions are compiled into a data structure. In response to determining that a status instruction is present in the data structure for which no status data has been collected, a method of collection for the instruction is determined, the collection is performed according to the method to obtain the status data, and the status data is compiled in a dump data structure.

Abstract: Methods and arrangements to collect data related to the state or conditions of a system are described herein. Embodiments may comprise a data identifier to identify data to collect in response to an event and a data collector to collect the identified data. The data collector may comprise firmware, code in ROM, a state machine, and/or other logic, and the data identifier may also comprise firmware, code in ROM, a state machine, and/or other logic that may access information and/or code in a file or other data storage to identify the data to collect. The data storage may comprise information and/or code to identify the location of data to collect and, in some embodiments, the sequence with which to collect the data. For example, such a file may comprise an address or address range within memory of a specific component of the system such as a memory controller.

Abstract: A method of processing data is proposed. In response to determining that a reconfiguration of a data processing system has occurred, one or more system items are surveyed to identify a change to the data processing system. One or more requests for status instructions for the one or more system items are generated, and the status instructions are compiled into a data structure. In response to determining that a status instruction is present in the data structure for which no status data has been collected, a method of collection for the instruction is determined, the collection is performed according to the method to obtain the status data, and the status data is compiled in a dump data structure.