Abstract:
There is disclosed in an example, a fabric interface device, having: a fabric interconnect to communicatively couple to a fabric; service level agreement (SLA) input logic to receive an SLA data structure from a controller, the SLA data structure providing an end-to-end SLA for a resource flow provided by a plurality of resources, and comprising QoS metrics for the resources; and SLA output logic to propagate the QoS metrics out to the resources via the fabric interconnect.
Abstract:
Examples may include techniques to distribute queries in a fabric of nodes configured to process the queries. A load balancing switch coupled to the nodes can receive indications of resource metrics from the nodes and can schedule and distribute the queries based on the resource metrics and network metrics identified by the switch. The switch can include programmable circuitry to receive selected resource metrics and identify selected network metrics and to distribute queries to nodes based on the metrics and distribution logic.
Abstract:
A processor or system may include a memory controller to store, in a pre-allocated portion of bit-addressable, random access persistent memory (PM), a relationship between a group of addresses being stored in the PM according to a set of instructions when executed. The memory controller is further to retrieve the relationship when accessing an address from the groups of addresses.
Abstract:
Technologies for software testing include a computing device having persistent memory that includes a platform simulator and an application or other code module to be tested. The computing device generates a checkpoint for the application at a test location using the platform simulator. The computing device executes the application from the test location to an end location and traces all writes to persistent memory using the platform simulator. The computing device generates permutations of persistent memory writes that are allowed by the hardware specification of the computing device simulated by the platform simulator. The computing device replays each permutation from the checkpoint, simulates a power failure, and then invokes a user-defined test function using the platform simulator. The computing device may test different permutations of memory writes until the application's use of persistent memory is validated. Other embodiments are described and claimed.
Abstract:
System and techniques for power-based adaptive hardware reliability on a device are described herein. A hardware platform is divided into multiple partitions. Here, each partition includes a hardware component with an adjustable reliability feature. The several partitions are placed into one of multiple reliability categories. A workload with a reliability requirement is obtained and executed on a partition in a reliability category that satisfies the reliability requirements. A change in operating parameters for the device is detected and the adjustable reliability feature for the partition is modified based on the change in the operating parameters of the device.
Abstract:
Deployment of resources utilizing improved mixture of experts processing is described. An example of an apparatus includes one or more network ports; one or more direct memory access (DMA) engines; and circuitry for mixture of experts (MoE) processing in the network, wherein the circuitry includes at least circuitry to track routing of tokens in MoE processing, prediction circuitry to generate predictions regarding MoE processing, including predicting future token loads for MoE processing, and routing management circuitry to manage the routing of the tokens in MoE processing based at least in part on the predictions regarding the MoE processing.
Abstract:
An apparatus includes a host interface; a network interface; and a programmable circuitry communicably coupled to the host interface and the network interface, the programmable circuitry comprising one or more processors to implement network interface functionality and to: determine portions of a set of computer vision (CV) processes to be deployed on the programmable circuitry and a host device, wherein the host device to be communicably coupled to the programmable network interface device; access instructions to cause the portions of the set of the CV processes to be deployed on the host device and the programmable network interface device; and wherein a media processing portion of the set of the CV processes is to be deployed to the programmable circuitry, and wherein the programmable circuitry is to utilize media processing hardware circuitry hosted by the apparatus to perform the media processing portion.
Abstract:
Described herein are technique to enable the autonomous generation of configurations for a network environment, including but not limited to an edge network of a datacenter. Additional embodiments include prompt-based generation of network and device configurations and neural network based systems for adaptive network management.
Abstract:
Systems and methods for inter-kernel communication using one or more semiconductor devices. The semi-conductor devices include a kernel. The kernel may be in an inactive state unless performing an operation. One kernel of a first device may monitor data for an event. Once an event has occurred, the kernel sends an indication to a first inter-kernel communication circuitry. The inter-kernel communication circuitry determines an activation function of a plurality of activation functions is to be generated, generates the activation function, and transmits the activation function to a second kernel of a second device to waken and perform a function using a peer-to-peer connection.
Abstract:
Various aspects of methods, systems, and use cases include coordinating actions at an edge device based on power production in a distributed edge computing environment. A method may include identifying a long-term service level agreement (SLA) for a component of an edge device, and determining a list of resources related to the component using the long-term SLA. The method may include scheduling a task for the component based on the long-term SLA, a current battery level at the edge device, a current energy harvest rate at the edge device, or an amount of power required to complete the task. A resource of the list of resources may be used to initiate the task, such as according to the scheduling.