Abstract: Certain disclosed embodiments provide improved systems and methods for processing jobs. The method comprises steps including receiving, from a client device over a network, information representing a job and generating at least two tasks representative of the job. The method further comprises, for each task, assigning, by a processor, a signature to the task representative of whether the task has been processed, determining at least one dataset related to the task, and assigning a signature to the determined at least one dataset. The method further comprises searching, by the processor, a data structure for the task signature, and based on the searching, sending the task over a network to a task executor for processing or locating results associated with the task. The method further comprises sending, over a network, a job result to the client device. Systems and computer-readable media are also provided.

Abstract: A cloud resource control circuitry may provide an automatic, self-managed, and a real-time elasticity in an active cloud stack including a software stack. The cloud resource control circuitry particularly adjusts cloud computing resources allocated to the active cloud stack based on real-time remote monitoring of resource utilization of the software stack. The resource adjustment may be performed in a stepwise fashion, in a pipelined manner as to the various layers of a software stack, and using hierarchical approach as to levels of cloud computing resources (e.g., task/level, server level, virtual machine/cloud level), to provide a more efficient cloud computing environment.

Abstract: According to one embodiment, a method, computer system, and computer program product for memory corruption diagnosis is provided. The present invention may include generating a pattern expression (PE) header file, wherein a plurality of common datatypes associated with a software program are pre-defined. The invention may further include generating a PE for each of the plurality of common datatypes, and generating a PE table by merging the generated PEs for each of the plurality of common datatypes. Upon discovery that memory corruption has occurred, the invention may include transmitting a recorded state of the software program as a core dump file to a server, and using a dump utility to identify overlay content of the core dump file. Lastly, the invention may include identifying a possible source program of the memory corruption by matching the PE tables against the illegally-written overlay content.

Abstract: Examples disclosed herein relate to visualizations of computer program transactions. The examples enable obtaining a transaction record of a computer program. The transaction record may include a call stack of a plurality of procedure calls and a self-time of each procedure call. The examples enable generating a graphical representation of the transaction record having a plurality of two-dimensional shapes aligned with a first axis and a second axis. Each two-dimensional shape represents a procedure call, and a first dimension of each shape represents a call-time of each procedure call while a second dimension of each shape represents the self-time of each procedure call. The shapes are positioned in the graphical representation to reflect relative positions within the call stack.

Abstract: Techniques are described herein for using artificial intelligence to “learn,” statistically, a target programming style that is imposed in and/or evidenced by a code base. Once the target programming style is learned, it can be used for various purposes. In various implementations, one or more generative adversarial networks (“GANs”), each including a generator machine learning model and a discriminator machine learning model, may be trained to facilitate learning and application of target programming style(s). In some implementations, the discriminator(s) and/or generator(s) may operate on graphical input, and may take the form of graph neural networks (“GNNs”), graph attention neural networks (“GANNs”), graph convolutional networks (“GCNs”), etc., although this is not required.

Abstract: A scheduling method of a system on chip including a multi-core processor includes receiving a schedule-requested task, converting a priority assigned to the schedule-requested task into a linear priority weight, selecting a plurality of candidate cores, to which the schedule-requested task will be assigned, from among cores of the multi-core processor, calculating a preemption compare index indicating a current load state of each of the plurality of candidate cores, comparing the linear priority weight with the preemption compare index of the each of the plurality of candidate cores to generate a comparison result, and assigning the schedule-requested task to one candidate core of the plurality of candidate cores depending on the comparison result.

Abstract: Managing an update of software modules of a layered filesystem installed for running a software application on a data processor. The management of an updated module includes: (i) contributing a back layer from a software module that likely has less stability than the updated module; and/or (ii) rebuilding a layer using a software module that likely has more stability than the updated layer.

Abstract: Some embodiments may be associated with a cloud-based computing environment. A multi-tenant master process platform, associated with a RDBMS, may create a logical database for a tenant on a physical instance of the cloud-based computing environment. A connection to the logical database may be received from a client user associated with the tenant, and a process for the connection may be created. A process identification number created for the process may then be captured along with the database identifier for the tenant using an in-kernel virtual machine program. The system may send the process identification number and the database identifier to a user space program. The user space program creates a control group with the name of the database identifier and places the process identification number into the control group. The control group can then be limited with respect to a maximum amount of resources (memory, CPU etc.).

Abstract: A method and an apparatus for processing a resource request are provided. The method includes: classifying, by a computing device, access virtual objects into a plurality of density grades according to a density of interaction virtual objects in a current interactive range of each access virtual object; allocating a resource request quota to each density grade. The method also includes: when a resource request sent by an access virtual object in a first density grade is received within the first preset duration, processing the resource request if the resource request quota corresponding to the density grade is greater than the preset quota threshold, and subtracting a preset value from the resource request quota corresponding to the density grade; and rejecting the resource request if the resource request quota corresponding to the density grade is not greater than the preset quota threshold.

Abstract: An information processing system for a multitenant service is proposed. The system includes memory queues and a processor. Processing requests issued from tenants are received through a network, where the number of the memory queues is smaller than the number of the tenants, and a priority is given to each of the memory queues. A priority of the processing request issued from each of the tenants is specified, based on a rank set with respect to each of the tenants and the amount of a used calculation resource for a predetermined period of time for each of the tenants, and the processing requests are retained in the memory queues according to the priorities. The retained processing requests are extracted from the memory queues in an order specified based on the priorities to execute processing corresponding to the processing requests.

Abstract: A partial order procedure planning device 10 is provided with: a first generation unit 11 which generates a first condition of a removable order relationship under a predetermined restriction among order relationships between operations in a serial procedure in which a plurality of operations, which transit the state of a state element from an initial state to a target state, are arranged in series; a second generation unit 12 which generates a second condition of an order relationship, which is required to satisfy a transient requirement that is required to satisfy the state element while a state among the order relationships is transitioned from the initial state to the target state; and a determination unit 13 which determines, as the order relationship to be deleted from the serial procedure, an order relationship which satisfies the generated first condition, but does not satisfy the generated second condition.

Abstract: A technique for varying firmware for different virtual functions in a virtualized device is provided. The virtualized device includes a hardware accelerator and a microcontroller that executes firmware. The virtualized device is virtualized in that the virtualized device performs work for different virtual functions (with different virtual functions associated with different virtual machines), each function getting a “time-slice” during which work is performed for that function. To vary the firmware, each time the virtualized device switches from performing work for a current virtual function to work for a subsequent virtual function, one or more microcontrollers of the virtualized device examines memory storing addresses for firmware for the subsequent virtual function and begins executing the firmware for that subsequent virtual function. The addresses for the firmware are provided by a corresponding virtual machine at configuration time.

Abstract: A technique is described herein for allocating tasks within a distributed system. The distributed system includes plural computing devices. Each computing device, in turn, provides a bucket manager and at least one application instance. The bucket managers allocate work to the computing devices in units of buckets, in a manner governed by a set of application-specific initialization parameters. The bucket managers also perform their assignment function in cooperation with a separate storage and notification (S&N) system. The S&N system stores data nodes in a hierarchical data structure that reflect the assignment-related state of the distributed system. The S&N system also notifies the bucket managers upon changes in the data nodes. According to one provision, the bucket managers include logic that reduces expensive context changes when computing devices join and leave the distributed system.

Abstract: An apparatus includes multiple processors, a classifier and queue management logic. The classifier is configured to classify tasks, which are received for execution by the processors, into multiple processor queues, each processor queue associated with a single processor or thread, and configured to temporarily store task entries that represent the tasks, and to send the tasks for execution by the associated processors. The queue management logic is configured to set, based on queue-lengths of the queues, an affinity strictness measure that quantifies a strictness with which the tasks of a same classified queue are to be processed by a same processor, and to assign the task entries to the queues while complying with the affinity strictness measure.

Abstract: A method and apparatus are disclosed which relate generally to worker-scheduling technology in a serverless cloud-computing environment, and more particularly, to technology that allocates workers for executing functions on a micro-function platform which provides a function-level micro-service. The method and apparatus process a worker allocation task in a distributed manner as two-step pre-allocation schemes before a worker allocation request occurs, and pre-allocates workers required for a service using a function request period and a function execution time, thus minimizing scheduling costs incurred by worker allocation requests.

Abstract: The disclosure provides an approach for selecting a path to use in transferring a virtual computing instance such as a virtual machine (VM), across data centers. In one embodiment, throughput and throttling information are sampled (e.g., per second) when VMs are transferred from a source data center to a destination data center, and the sampled information is used to construct histograms that provide performance profiles of the VM transfers. Such histogram information across a number of VM transfers can then be mined to determine trends. In turn, trends determined from historical histogram information may be extrapolated into the future to predict performance of a subsequent VM transfer operation and to select a path and/or destination storage and host pair to use for the VM transfer operation.

Abstract: Systems, methods, and computer program products are described herein for proactively allocating resources of a computing infrastructure having a plurality of namespaces. Data having process information for executing an application task on a namespace of the computing infrastructure is received. The process information defines process loads associated with the application task. A number of application servers for executing the application task are determined based on the process loads. Application servers are allocated to the namespace based on the determined number of application servers for execution of the application task. The receiving, the determining, and the allocating occur prior to execution of the application task.

Abstract: A processor may execute an asynchronous operation of the program code, hibernate a process related to the asynchronous operation, and free-up related cloud runtime platform excluding the related system memory. Additionally, the processor may execute the asynchronous operation during the hibernation of the process, intercept an initiated completion function to the process after a completion of the asynchronous operation, inject at least one of additional program code and data into the completion function, un-hibernating the process and reallocate freed-up cloud runtime platform related resources of the process, and execute the completion function returning result data of the asynchronous operation and the at least one of additional program code and data to the process.

Abstract: Providing self-resetting multi-producer multi-consumer semaphores in distributed processor-based systems is disclosed. In one aspect, a synchronization management circuit provides a semaphore including a counting semaphore value indicator, a current wait count indicator, and a target wait count indicator. When a consumer completes a wait operation, the synchronization management circuit adjusts the value of the current wait count indicator towards the value of the target wait count indicator, and compares the value of the current wait count indicator to the value of the target wait count indicator. If the value of the current wait count indicator has reached the value of the target wait count indicator, the synchronization management circuit infers that all consumers have observed the semaphore, and accordingly resets both the counting semaphore value indicator and the current wait count indicator to an initial wait value to place the semaphore in its initial state for reuse.

Abstract: Techniques are disclosed for reallocating host resources in a virtualized computing environment when certain criteria have been met. In some embodiments, a system identifies a host disabling event. In view of the disabling event, the system identifies a resource for reallocation from a first host to a second host. Based on the identification, the computer system disassociates the identified resource's virtual identifier from the first host device and associates the virtual identifier with the second host device. Thus, the techniques disclosed significantly reduce a system's planned and unplanned downtime.