A system, method and program product for handling potentially problematic events in an enterprise computing platform. A method is disclosed that includes receiving a request to process an event from a client, wherein the event specifies a feature to be performed on an enterprise resource within the enterprise platform. The method further includes retrieving a processing threshold for the feature from a set of stored configuration settings and obtaining metadata associated with the enterprise resource, wherein the metadata indicates an attribute of the enterprise resource. The method then determines whether the attribute of the enterprise resource exceeds the processing threshold, and if so, does not process the event.

The present invention provides a system for observing power or energy availability for a gateway device and the power or energy consumption of each component or device within or connected to the gateway device. The gateway device of the present invention can then learn the usage patterns of the software modules and devices and then predict the power utilization based on various usage plans. The gateway device can then plan or build an energy consumption schema and implement the energy consumption schema to control power utilization by the gateway device and its related peripheral devices. The gateway device can also communicate with other gateway devices to share power plant data, utilization schemas, or to off load or on board data tasks. The gateway device can dynamically self-optimize to restrict or permit power plant usage based on forecasts derived from past behavior and predicted future behavior and demand predictions triggered by application usage.

The technology includes methods, processes, and systems for virtualizing graphics processing unit (GPU) memory. Example embodiments of the technology include managing an amount of GPU memory used by one or more processes, such as Application Programming Interfaces (APIs), that directly or indirectly impact one or more other processes running on the same GPU. Managing and/or virtualizing the amount of GPU memory may ensure that an end user does not receive a GPU out-of-memory error because the API request is impacted by the processing of other API requests. A virtual machine with access to a GPU may be organized with one or more job slots that are configured to specify the number of processes that are able to run concurrently on a specific virtual machine. A process may be configured on each virtual machine running a software program or API and is used to schedule work based on GPU memory requirements.

Systems and methods for allocating resources are disclosed. Resources such as streams are allocated using a stream credit system. Credits are issued to the clients in a manner that ensure the system is operating in a safe allocation state. The credits can be used not only to allocate resources but also to throttle clients where necessary. Credits can be granted fully, partially, and in a number greater than a request. Zero or negative credits can also be issued to throttle clients.

A method by a cloud orchestrator to provide subscription-based throttling of virtual applications in a cloud. The method includes determining that a physical resource in the cloud is being overutilized, identifying a virtual application running in the cloud that utilizes the physical resource, determining that the virtual application is to be throttled based on a determination that the virtual application is subscribed to a throttling subscription registry, where the throttling subscription registry specifies a throttling mechanism by which to throttle the virtual application, and executing the throttling mechanism to throttle the virtual application in response to a determination that the virtual application is to be throttled.

Methods, apparatus, systems and articles of manufacture (e.g., physical storage media) to implement and manage software defined silicon products are disclosed. Example semiconductor devices disclosed herein include circuitry configurable to provide one or more features. Disclosed example semiconductor devices also include a license processor to activate or deactivate at least one of the one or more features based on a license received via a network from a first remote enterprise system. Disclosed example semiconductor devices further include an analytics engine to report telemetry data associated with operation of the semiconductor device to at least one of the first remote enterprise system or a second remote enterprise system, the analytics engine to report the telemetry data in response to activation or deactivation of the at least one of the one or more features based on the license.

The present disclosure involves systems, software, and computer implemented methods for resource allocation and management. One example method includes receiving a request, including a first application priority, to run a task for an application. At least one second application priority is identified. A maximum number of parallel tasks per application priority is determined. Application priority weights are assigned to the first application priority and the second application priorities. Application priority divisors are determined, for the first application priority and the second application priorities, based on a respective application priority weight and a number of currently running applications of a respective application priority. A number of parallel tasks for the first application and other applications are determined based on the maximum number of allowable parallel tasks per application, an overall divisor, and a respective application priority weight. A number of parallel tasks are assigned to the first application.

Systems and methods for computer memory management by a memory coordinator and a plurality of memory consumers. An urgency and memory quota of each memory consumer is initialized by the memory coordinator, which then adjusts the memory quota of each memory consumer such that the sum of the memory quota of each memory consumer does not exceed a finite amount of computer memory. Each memory consumer adjusts its memory usage in response to the quota input and urgency input from the memory coordinator.

The present disclosure relates to computer-implemented methods, software, and systems for dynamic rate limiting of execution of operation. A request from a user account for execution of an operation by an application service is. A total number of operations registered at an operations registry is determined. In response to determining that all of registered operations exceeds a first threshold value, a number of registered operations associated with a group account of the user account is determined. If it is determined that (i) the total number of registered operations exceeds a first threshold value and that the number of registered operations associated with the group account does not exceed a second threshold value or (ii) if it is determined that the total number of registered operations does not exceed the first threshold value, the operation is registered at the operations registry. An instruction to execute the registered operation is sent.

Resource access control modules that are part of an operating system kernel and data structures visible in both user space and kernel space provide for user space-based configuration of computing system resource limits, accounting of resource usage, and enforcement of resource usage limits. Computing system resource limits can be set on an application, customer, or other basis, and usage limits can be placed on various system resources, such as files, ports, I/O devices, memory, and processing unit bandwidth. Resource usage accounting and resource limit enforcement can be implemented without the use of in-kernel control groups. The resource access control modules can be extended Berkeley Program Format (eBPF) Linux Security Module (LSM) programs linked to LSM hooks in the Linux operation system kernel.