Technologies for enhancing work scheduling of a big data framework. The technologies can include generating, in a database, configurable namespaces to be used by a work scheduling enhancement application to group together tasks of one or more big data clusters. The namespaces can be hierarchical. The technologies can also include linking in the database, by the application, related tasks with respective namespaces to categorize and group together the related tasks. The technologies can also include configuring, by the application, a display scheme for displaying error handling and root cause analysis of tasks of the one or more big data clusters. The technologies can also include generating or rendering, by the application, a GUI having a navigable hierarchal view for displaying the namespaces. The generation or rendering of the GUI can be based partially on the display scheme.

Apparatus and Method for Fault Handling of an Offload Transaction. For example, one embodiment of a processor comprises: a plurality of cores; an interconnect coupling the plurality of cores; and offload circuitry to transfer work from a first core of the plurality of cores to a second core of the plurality of cores without operating system (OS) intervention, the work comprising a plurality of instructions; the second core comprising first fault management logic to determine an action to take responsive to a fault condition, wherein responsive to detecting a first type of fault condition, the first fault management logic is to cause the first core to be notified of the fault condition, the first core comprising second fault management logic to attempt to resolve the fault condition.

An apparatus and method are provided for managing use of capabilities. The apparatus has processing circuitry to execute instructions, and a plurality of capability storage elements accessible to the processing circuitry and arranged to store capabilities used to constrain operations performed by the processing circuitry when executing instructions. The processing circuitry is operable at a plurality of exception levels, each exception level having different software execution privilege. Further, capability configuration storage is provided to identify capability configuration information for each of the plurality of exception levels. For each exception level, the capability configuration information identifies at least whether the operations performed by the processing circuitry when executing instructions at that exception level are constrained by capabilities. During a switch operation from a source exception level to a target exception level, the capability configuration information in the capability configuration storage pertaining to at least one of the source exception level and the destination exception level is used to determine how execution state of the processing circuitry is managed during the switch operation. This provides a great deal of flexibility in the management of capabilities.

A method for debugging a processor which is executing vertices of a software application is described. Each vertex is assigned to a programming thread of the processor. The processor has debug hardware for raising exceptions in certain break conditions. The method comprises inspecting a vertex identifier, comparing the vertex identifier and raising an instruction exception event for the programming thread if the vertex identifier assigned to the thread matches the vertex break identifier in the debug hardware. Exceptions are raised based on identified vertices, rather than just individual instructions or instruction addresses.

Technologies for enhancing work scheduling of a big data framework. The technologies can include generating, in a database, configurable namespaces to be used by a work scheduling enhancement application to group together tasks of one or more big data clusters. The namespaces can be hierarchical. The technologies can also include linking in the database, by the application, related tasks with respective namespaces to categorize and group together the related tasks. The technologies can also include configuring, by the application, a display scheme for displaying error handling and root cause analysis of tasks of the one or more big data clusters. The technologies can also include generating or rendering, by the application, a GUI having a navigable hierarchal view for displaying the namespaces. The generation or rendering of the GUI can be based partially on the display scheme.

Methods, apparatus, computer program products for handling critical problem exceptions during an execution of an application are provided. The method comprises: detecting, by one or more processing units, an occurrence of a certain type of critical problem exception during an execution of an application, the critical problem exception resulting in a termination of the application; instructing, by one or more processing units, to call a Super Handling Routine (SHR) corresponding to the type of the critical problem exception at a pre-configured address based on a pre-determined context registered by the application, the SHR being configured to handle critical problem exceptions; and handing, by one or more processing units, control to the SHR to handle the type of the critical problem exception.

A software framework for implementation in the performance of automated robotic workflows imparts a hierarchical communications command structure, utilizing an actor-based model to run driver software isolated from scheduling software, by instantiating a message-based abstraction layer that acts as an intermediary between the scheduling software and the third-party driver software. The actor-based model is used within the message-based abstraction layer to isolate the third-party software controlling third party instruments from scheduling software, where such scheduling software and third-party instruments are operating on a common computing platform. This framework prevents scheduling applications from entering an error state, or crashing, where the third-party software component also crashes, and allows the scheduling software to restart the third-party software to continue with the processes controlled by the scheduling software, without interruption to the automated workflow environment.

A method for exchanging data among several enterprise management systems includes receiving and processing data sent by a first system, and recording a task of writing data to a second system in a database of an electronic device, and setting the recorded task as unfinished task. A list of unfinished tasks is acquired from the database in predetermined time period, and a result of query can be generated by searching or interrogating the second system as to the list of unfinished tasks. When the second system has finished the task, the task for writing data in the second system is set as finished.

Embodiments of the present disclosure relate to a method, system, and computer program product for exception handling. In some embodiments, a method is disclosed. According to the method, in response to an application throwing an exception, a target stack frame for handling the exception is detected from a call stack of the application. The call stack comprises a plurality of stack frames. One of the plurality of stack frames corresponds to a function called by the application and supports either a one-phase exception handling mechanism or a two-phase exception handling mechanism. In response to the target stack frame being detected from the call stack, the target stack frame is caused to handle the exception. In other embodiments, a system and a computer program product are disclosed.

Providing exception stack management using stack panic fault exceptions in processor-based devices is disclosed. In this regard, a processor device defines a “stack panic fault exception” that may be raised upon execution of an exception handler store operation attempting to write state data into an exception stack, and provides a dedicated plurality of stack panic fault exception state registers in which stack panic fault exception state data may be saved. Upon detecting a first exception, the processor device transfers program control to an exception handler for the first exception. If a second exception occurs upon execution of a store operation in the exception handler, the processor device determines that the second exception should be handled as a stack panic fault exception, saves the stack panic fault exception state data in the stack panic fault exception state registers, and transfers program control to a stack panic fault exception handler.