Abstract: An architecture to perform resource management among multiple network nodes and associated resources is disclosed. Example resource management techniques include those relating to: proactive reservation of edge computing resources; deadline-driven resource allocation; speculative edge QoS pre-allocation; and automatic QoS migration across edge computing nodes.

Abstract: Examples described herein relate to circuitry to utilize a proportional, derivative, integral neural network (PIDNN) controller to adjust one or more parameters allocated to a first group of one or more workloads based on one or more target parameters for a second group of one or more workloads. In some examples, the second group of one or more workloads are a same, lower, or higher priority level than that of the first group of one or more workloads.

Abstract: There is disclosed in one example a computing apparatus, including: a processor; a multilevel cache including a plurality of cache levels; a peripheral device configured to write data directly to a selected cache level; and a cache monitoring circuit, including a cache counter to track cache lines evicted from the selected cache level without being processed; and logic to provide a direct write policy according to the cache counter.

Abstract: Embodiments of apparatuses, methods, and systems for resource control based on software priority are described. In embodiments, an apparatus includes resource sharing hardware and multiple cores. The resource sharing hardware is to share the shared resource among the cores. A first core includes first execution circuitry to execute multiple threads. The first core also includes registers programmable by software. A first register is to store a first identifier of a first thread and a first priority tag to indicate a first priority of the first thread relative to a second priority of a second thread. A second register to store a second identifier of the second thread and a second priority tag to indicate the second priority of the second thread relative to the first priority of the first thread. The resource sharing hardware is to use the first priority and the second priority to control access to the shared resource by the first thread and the second thread.

Abstract: Embodiments of apparatuses and methods for memory bandwidth monitoring extensible counters are described. In embodiments, an apparatus includes memory bandwidth monitoring hardware to monitor an event, a shared cache to be shared by multiple cores. At least one of the cores is to execute multiple threads and includes at least three registers. The first register is programmable by software to store a thread identifier of one of threads and an event identifier of the event during execution of the thread. At least one value of the event identifier corresponds to a shared cache miss. The second register is to provide to the software a second value corresponding to a number of bits available to represent the count. The third register is to provide to the software a count of occurrences of the event and an indicator to indicate whether the count reached a maximum count representable by the number of bits.

Abstract: Devices and techniques for out-of-band platform tuning and configuration are described herein. A device can include a telemetry interface to a telemetry collection system and a network interface to network adapter hardware. The device can receive platform telemetry metrics from the telemetry collection system, and network adapter silicon hardware statistics over the network interface, to gather collected statistics. The device can apply a heuristic algorithm using the collected statistics to determine processing core workloads generated by operation of a plurality of software systems communicatively coupled to the device. The device can provide a reconfiguration message to instruct at least one software system to switch operations to a different processing core, responsive to detecting an overload state on at least one processing core, based on the processing core workloads. Other embodiments are also described.

Abstract: Technologies for analyzing and optimizing workloads (e.g., virtual network functions) executing on edge resources are disclosed. According to one embodiment disclosed herein, a compute device launches a virtualized system including a virtual network function and a performance manager, the performance manager to monitor a current resource usage of the virtual network function as a function of a performance profile. The compute device determines, in response to a determination that one or more quality-of-service (QoS) requirements is not satisfied, whether one or more resources from the platform are available for satisfying the QoS requirements. The compute device receives, in response to a determination that the one or more resources are available for satisfying the QoS requirements, the one or more resources and updates the performance profile as a function of the received resources.

Abstract: Technologies for managing telemetry and sensor data on an edge networking platform are disclosed. According to one embodiment disclosed herein, a device monitors telemetry data associated with multiple services provided in the edge networking platform. The device identifies, for each of the services and as a function of the associated telemetry data, one or more service telemetry patterns. The device generates a profile including the identified service telemetry patterns.

Abstract: In some examples, for process-to-process communication, such as in function linking, a virtual channel can be provisioned to provide virtual machine to virtual machine communications. In response to a transmit request from a source virtual machine, the virtual channel can cause a data copy from a source buffer associated with the source virtual machine without decryption or encryption. The virtual channel provisions a key identifier for the copied data. The destination virtual machine can receive an indication data is available and can cause the data to be decrypted using a key accessed using the key identifier and source address of the copied data. In addition, the data can be encrypted using a second, different key for storage in a destination buffer associated with the destination virtual machine. In some examples, the key identifier and source address is managed by the virtual channel and is not visible to virtual machine or hypervisor.

Abstract: Method and system for performing data movement operations is described herein. One embodiment of a method includes: storing data for a first memory address in a cache line of a memory of a first processing unit, the cache line associated with a coherency state indicating that the memory has sole ownership of the cache line; decoding an instruction for execution by a second processing unit, the instruction comprising a source data operand specifying the first memory address and a destination operand specifying a memory location in the second processing unit; and responsive to executing the decoded instruction, copying data from the cache line of the memory of the first processing unit as identified by the first memory address, to the memory location of the second processing unit, wherein responsive to the copy, the cache line is to remain in the memory and the coherency state is to remain unchanged.

Abstract: Devices and techniques for out-of-band platform tuning and configuration are described herein. A device can include a telemetry interface to a telemetry collection system and a network interface to network adapter hardware. The device can receive platform telemetry metrics from the telemetry collection system, and network adapter silicon hardware statistics over the network interface, to gather collected statistics. The device can apply a heuristic algorithm using the collected statistics to determine processing core workloads generated by operation of a plurality of software systems communicatively coupled to the device. The device can provide a reconfiguration message to instruct at least one software system to switch operations to a different processing core, responsive to detecting an overload state on at least one processing core, based on the processing core workloads. Other embodiments are also described.

Abstract: A device of a service coordinating entity includes communications circuitry to communicate with a plurality of access networks via a corresponding plurality of network function virtualization (NFV) instances, processing circuitry, and a memory device. The processing circuitry is to perform operations to monitor stored performance metrics for the plurality of NFV instances. Each of the NFV instances is instantiated by a corresponding scheduler of a plurality of schedulers on a virtualization infrastructure of the service coordinating entity. A plurality of stored threshold metrics is retrieved, indicating a desired level for each of the plurality of performance metrics. A threshold condition is detected for at least one of the performance metrics for an NF V instance of the plurality of NFV instances, based on the retrieved plurality of threshold metrics. A hardware resource used by the NFV instance to communicate with an access network is adjusted based on the detected threshold condition.

Abstract: In accordance with some embodiments, a cloud service provider may operate a data center in a way that dynamically reallocates resources across nodes within the data center based on both utilization and service level agreements. In other words, the allocation of resources may be adjusted dynamically based on current conditions. The current conditions in the data center may be a function of the nature of all the current workloads. Instead of simply managing the workloads in a way to increase overall execution efficiency, the data center instead may manage the workload to achieve quality of service requirements for particular workloads according to service level agreements.

Abstract: An apparatus and method for dynamic resource allocation with mile/performance markers.

Abstract: Technologies for analyzing and optimizing workloads (e.g., virtual network functions) executing on edge resources are disclosed. According to one embodiment disclosed herein, a compute device launches a virtualized system including a virtual network function and a performance manager, the performance manager to monitor a current resource usage of the virtual network function as a function of a performance profile. The compute device determines, in response to a determination that one or more quality-of-service (QoS) requirements is not satisfied, whether one or more resources from the platform are available for satisfying the QoS requirements. The compute device receives, in response to a determination that the one or more resources are available for satisfying the QoS requirements, the one or more resources and updates the performance profile as a function of the received resources.

Abstract: Generally discussed herein are systems, devices, and methods for network security monitoring (NSM). A hardware queue manager (HQM) may include an input interface to receive first data from at least a first worker thread, queue duplication circuitry to generate a copy of at least a portion of the first data to create first copied data, and an output interface to (a) provide the first copied data to a second worker thread, and/or (b) provide at least a portion of the first data to a third worker thread.

Abstract: A device of a service coordinating entity includes communications circuitry to communicate with a plurality of access networks via a corresponding plurality of network function virtualization (NFV) instances, processing circuitry, and a memory device. The processing circuitry is to perform operations to monitor stored performance metrics for the plurality of NFV instances. Each of the NFV instances is instantiated by a corresponding scheduler of a plurality of schedulers on a virtualization infrastructure of the service coordinating entity. A plurality of stored threshold metrics is retrieved, indicating a desired level for each of the plurality of performance metrics. A threshold condition is detected for at least one of the performance metrics for an NFV instance of the plurality of NFV instances, based on the retrieved plurality of threshold metrics. A hardware resource used by the NFV instance to communicate with an access network is adjusted based on the detected threshold condition.

Abstract: Embodiments of systems, apparatuses and methods provide enhanced function as a service (FaaS) to users, e.g., computer developers and cloud service providers (CSPs). A computing system configured to provide such enhanced FaaS service include one or more controls architectural subsystems, software and orchestration subsystems, network and storage subsystems, and security subsystems. The computing system executes functions in response to events triggered by the users in an execution environment provided by the architectural subsystems, which represent an abstraction of execution management and shield the users from the burden of managing the execution. The software and orchestration subsystems allocate computing resources for the function execution by intelligently spinning up and down containers for function code with decreased instantiation latency and increased execution scalability while maintaining secured execution.

Abstract: Technologies for managing telemetry and sensor data on an edge networking platform are disclosed. According to one embodiment disclosed herein, a device monitors telemetry data associated with multiple services provided in the edge networking platform. The device identifies, for each of the services and as a function of the associated telemetry data, one or more service telemetry patterns. The device generates a profile including the identified service telemetry patterns.

Abstract: Examples may include techniques to live migrate a virtual machine (VM) using disaggregated computing resources including compute and memory resources. Examples include copying data between allocated memory resources that serve as near or far memory for compute resources supporting the VM at a source or destination server in order to initiate and complete the live migration of the VM.