Abstract: Various systems and methods for implementing computational storage are described herein.

Abstract: In an example, there is disclosed a demand scaling engine, including: a processor interface to communicatively couple to a processor; a network controller interface to communicatively couple to a network controller and to receive network demand data; a scaleup criterion; a current processor frequency scale datum; and logic, provided at least partly in hardware, to: receive the network demand data; compare the network demand data to the scaleup criterion; determine that the network demand data exceeds the scaleup criterion; and instruct the processor via the processor interface to scaleup processor frequency.

Abstract: In one embodiment, a method comprises determining whether an automation recommendation for a network is to be forwarded to a management system of the network, wherein the automation recommendation specifies an action to take with respect to a plurality of platforms of the network and is received from a recommendation system utilizing artificial intelligence to generate the automation recommendation; responsive to a determination to forward the automation recommendation, assessing an impact of the automation recommendation; and performing an action with respect to the automation recommendation based on the impact.

Abstract: Examples include techniques for core-specific metrics collection. Examples include fetching metrics of a core of a multi-core processor from one or more registers responsive to scheduling of an event. The fetched metrics are pushed to a shared memory space of a memory that is accessible to a user-space application and accessible to other cores of the multi-core processor. The user-space application to access the shared memory space to aggregate core-specific metrics associated with at least the core of the multi-core processor and then publish the aggregated core-specific metrics.

Abstract: Telemetry information in the form of platform telemetry, virtualization layer telemetry, and application telemetry can be used to estimate power consumption of a software entity, such as a virtual machine, container, application, or network slice. A controller can take various actions based on software entity power consumption information. If a power limit of an integrated circuit component is exceeded, the controller can reduce the power consumption of a software entity or move the software entity to another integrated circuit component to reduce the power consumption of the integrated circuit component. The controller can determine a total software entity power consumption for software entities associated with a user entity and take actions to keep the total software entity power consumption within a power budget.

Abstract: Techniques for reassembling fragmented datagrams are disclosed. Packets may be received and classified. Packets of a fragmented datagram may be stored for later reassembly. In the illustrative embodiment, a datagram is reassembled based on an identified class of service associated with the datagram. Additionally or alternatively, in the illustrative embodiment, a replay window of a replay attack detector may be tuned based on hardware performance of a compute device.

Abstract: Technologies for accelerated key caching in an edge hierarchy include multiple edge appliance devices organized in tiers. An edge appliance device receives a request for a key, such as a private key. The edge appliance device determines whether the key is included in a local key cache and, if not, requests the key from an edge appliance device included in an inner tier of the edge hierarchy. The edge appliance device may request the key from an edge appliance device included in a peer tier of the edge hierarchy. The edge appliance device may activate per-tenant accelerated logic to identify one or more keys in the key cache for eviction. The edge appliance device may activate per-tenant accelerated logic to identify one or more keys for pre-fetching. Those functions of the edge appliance device may be performed by an accelerator such as an FPGA. Other embodiments are described and claimed.

Abstract: A processing device includes a plurality of processing cores, a control register, associated with a first processing core of the plurality of processing cores, to store a first base clock frequency value at which the first processing core is to run, and a power management circuit to receive a base clock frequency request comprising a second base clock frequency value, store the second base clock frequency value in the control register to cause the first processing core to run at the second base clock frequency value, and expose the second base clock frequency value on a hardware interface associated with the power management circuit.

Abstract: A system comprising a first processor unit comprising a first register to store a metric for the first processor unit; and circuitry to initiate sharing of the metric with a second processor unit without the use of an inter-processor interrupt.

Abstract: A computing device includes an appliance status table to store at least one of reliability and performance data for one or more network functions virtualization (NFV) appliances and one or more legacy network appliances. The computing device includes a load controller to configure an Internet Protocol (IP) filter rule to select a packet for which processing of the packet is to be migrated from a selected one of the one or more legacy network appliances to a selected one of the one or more NFV appliances, and to update the appliance status table with received at least one of reliability and performance data for the one or more legacy network appliances and the one or more NFV appliances. The computing device includes a packet distributor to receive the packet, to select one of the one or more NFV appliances based at least in part on the appliance status table, and to send the packet to the selected NFV appliance. Other embodiments are described herein.

Abstract: In one embodiment, a system comprising a network interface controller comprising circuitry to determine per-flow analytics information for a plurality of packet flows; and facilitate differential rate processing of a plurality of packet queues for the plurality of packet flows based on the per-flow analytics information.

Abstract: There is disclosed in an example, a computer-implemented method of providing network function virtualization orchestration (NFVO), including: determining that a first virtual network function (VNF) instance, providing a virtual service appliance on a virtual network, is to be migrated; provisioning a second VNF instance of the virtual service appliance; cloning configuration data from the first VNF to the second VNF; starting the second VNF without copying traffic data; and halting the first VNF. There is also disclosed an apparatus for performing the method, and a computer-readable medium having instructions for performing the method.

Abstract: In one embodiment, a system includes a device and a host. The device includes a device stream buffer. The host includes a processor to execute at least a first application and a second application, a host stream buffer, and a host scheduler. The first application is associated with a first transmit streaming channel to stream first data from the first application to the device stream buffer. The first transmit streaming channel has a first allocated amount of buffer space in the device stream buffer. The host scheduler schedules enqueue of the first data from the first application to the first transmit streaming channel based at least in part on availability of space in the first allocated amount of buffer space in the device stream buffer. Other embodiments are described and claimed.

Abstract: A computing apparatus, including: a processor; a pointer to a counter memory location; and a lazy increment counter engine to: receive a stimulus to update the counter; and lazy increment the counter including issuing a weakly-ordered increment directive to the pointer.

Abstract: Techniques for managing workloads in processor cores are disclosed. High priority or mission critical workloads may be assigned to processor cores of a processor. When a power limited throttling condition is met, the processor may throttle some of its cores while not throttling the cores with the high priority or mission critical workloads assigned to it. Such an approach can ensure that mission critical workloads continue even upon throttling of the processor cores.

Abstract: A computing device includes an appliance status table to store at least one of reliability and performance data for one or more network functions virtualization (NFV) appliances and one or more legacy network appliances. The computing device includes a load controller to configure an Internet Protocol (IP) filter rule to select a packet for which processing of the packet is to be migrated from a selected one of the one or more legacy network appliances to a selected one of the one or more NFV appliances, and to update the appliance status table with received at least one of reliability and performance data for the one or more legacy network appliances and the one or more NFV appliances. The computing device includes a packet distributor to receive the packet, to select one of the one or more NFV appliances based at least in part on the appliance status table, and to send the packet to the selected NFV appliance. Other embodiments are described herein.

Abstract: Examples include a method of determining a first traffic overload protection policy for a first service provided by a first virtual network function in a network of virtual network functions in a computing system and determining a second traffic overload protection policy for a second service provided by a second virtual network function in the network of virtual network functions. The method includes applying the first traffic overload protection policy to the first virtual network function and the second traffic overload protection policy to the second virtual network function, wherein the first traffic overload protection policy and the second traffic overload protection policy are different.

Abstract: A network interface device, including: an ingress interface; a host platform interface to communicatively couple to a host platform; and a packet preprocessor including logic to: receive via the ingress interface a data sequence including a plurality of discrete data units; identify the data sequence as data for a parallel processing operation; reorder the discrete data units into a reordered data frame, the reordered data frame configured to order the discrete data units for consumption by the parallel operation; and send the reordered data to the host platform via the host platform interface.

Abstract: A performance monitor provides cache miss stall and memory bandwidth usage metric samples to a resource exhaustion detector. The detector can detect the presence of last-level cache and memory bandwidth exhaustion conditions based on the metric samples. If cache miss stalls and memory bandwidth usage are both trending up, the detector reports a memory bandwidth exhaustion condition to a resource controller. If cache miss stalls are trending up and memory bandwidth usage is trending down, the detector reports a last-level cache exhaustion condition to the resource controller. The resource controller can allocate additional last-level cache or memory bandwidth to the processor unit to remediate the resource exhaustion condition. If bandwidth-related metric samples indicate that a processor unit may be overloaded due to receiving high bandwidth traffic, the resource controller can take a traffic rebalancing remedial action.

Abstract: Examples described herein relate to circuitry to boot a virtualized execution environment (VEE) by use of system resources, wherein the system resources are allocated based on a priority level of the VEE. In some examples, the circuitry to boot a VEE by use of system resources is to access an identification of system resources to use to boot the VEE and priority level of the VEE from stored data. In some examples, the priority level of the VEE is based on a service level agreement (SLA), service level objective (SLO), or class of service (COS) that identifies boot time of the VEE. In some examples, the circuitry is to boot a VEE by use of system resources, wherein the system resources are allocated based on a priority level of the VEE and also based on a number of VEEs that boot concurrently.