A tracing operation is initiated on a service, wherein the service comprises a plurality of method calls. A span is generated comprising timing information associated with the service, wherein the span comprises a plurality of nested spans associated with the plurality of method calls. A determination is made as to whether one or more method calls of the plurality of method calls are causing the service to underperform in view of the plurality of nested spans. In response to determining that the one or more method calls of the plurality of method calls are causing the service to underperform, a remedial action associated with the one or more method calls is performed.

A system and method of scheduling timer access includes a first physical processor with a first physical timer executing a first guest virtual machine. A hypervisor determines an interrupt time remaining before an interrupt is scheduled and determines the interrupt time is greater than a threshold time. Responsive to determining that the interrupt time is greater than the threshold time, the hypervisor designates a second physical processor as a control processor with a control timer and sends, to the second physical processor, an interval time, which is a specific time duration. The hypervisor grants, to the first guest virtual machine, access to the first physical timer. The second physical processor detects that the interval time expires. Responsive to detecting that the interval time expired, an inter-processor interrupt is sent from the second physical processor to the first physical processor, triggering the first guest virtual machine to exit to the hypervisor.

A non-transitory computer-readable storage medium storing therein a job scheduler test program that causes a computer to execute a process includes: determining whether or not a state of every thread of a test-target job scheduler is a standby state; and changing a time of a system referenced when the thread executes a process to a time that is put forward in a case where the state of every thread is the standby state.

Pre-fetching instructions for tasks of an operating system (OS) is provided by calling a task scheduler that determines a load start time for a set of instructions for a particular task corresponding to a task switch condition. The OS calls, and in response to the load start time, a loader entity module that generates a pre-fetch request that loads the set of instructions for the particular task from a non-volatile memory circuit into a random access memory circuit. The OS calls the task scheduler to switch to the particular task.

A task control circuit maintains, in response to task event information, a task information queue that includes task information for a plurality of tasks. Based upon the task information in the task information queue, a future task switch condition is identified as corresponding to a task switch time for a particular task of the plurality of tasks. A load start time is determined for a set of instructions for the particular task. A pre-fetch request is generated to load the set of instructions for the particular task into the memory circuit. The pre-fetch request is forwarded to a hardware loader circuit. In response to the task switch time, a task event trigger is generated for the particular task. The hardware loader circuit is used to load, in response to the pre-fetch request, the set of instructions from a non-volatile memory into the memory circuit.

Methods and systems are disclosed for automated semantic tagging that include detecting a particular thread executed by a processor and identifying a root process of the particular thread. An object-process link may be by linking an object that executed code that called the particular thread to the root process. A thread list of thread definitions of the object may be identified. A particular thread definition that corresponds to the particular thread can be mapped. Resource types to be consumed upon executing an instance of the thread instantiated from the particular thread definition can be identified and the corresponding values of the resource types can be determined. A process specification can be generated that encapsulates the thread definition, resource types and values so as to reproduce a state of the root process at a point in which the particular thread executed.

The disclosure relates to systems, methods and computer-readable media for using system jobs for performing actions outside the constraints of batch compute jobs submitted to a compute environment such as a cluster or a grid. The method for modifying a compute environment from a system job disclosure associating a system job to a queuable object, triggering the system job based on an event and performing arbitrary actions on resources outside of compute nodes in the compute environment. The queuable objects include objects such as batch compute jobs or job reservations. The events that trigger the system job may be time driven, such as ten minutes prior to completion of the batch compute job, or dependent on other actions associated with other system jobs. The system jobs may be utilized also to perform rolling maintenance on a node by node basis.

Systems and methods for transaction/file-based management of a plurality of processes associated with various jobs are provided. Through the management of discrete applications, a file distribution manager/scheduler orchestrates automated execution of different types of jobs. The processes executed for the various processes can vary based on job type, or other parameters.

Techniques are disclosed that enable automating user interface input by generating a sequence of actions to perform a task utilizing a multi-agent reinforcement learning framework. Various implementations process an intent associated with received user interface input using a holistic reinforcement policy network to select a software reinforcement learning policy network. The sequence of actions can be generated by processing the intent, as well as a sequence of software client state data, using the selected software reinforcement learning policy network. The sequence of actions are utilized to control the software client corresponding to the selected software reinforcement learning policy network.

Computerized RPA methods and systems that increase the flexibility and lower the cost with which RPA systems may be deployed are disclosed herein. In one embodiment, an RPA system and method avoids the need for preinstalled RPA software on a device employed by a user to create and/or execute software robots to perform RPA. In another embodiment, an RPA system and method provides a capability to execute software robots that may have been encoded in one or more programming languages to execute on an operating system different than that employed by a server of the RPA system.