Abstract: Methods, apparatus and systems for adaptive fabric allocation for local and remote emerging memories-based prediction schemes. In conjunction with performing memory transfers between a compute host and memory device connected via one or more interconnect segments, memory read and write traffic is monitored for at least one interconnect segment having reconfigurable upstream lanes and downstream lanes. Predictions of expected read and write bandwidths for the at least one interconnect segment are then made. Based on the expected read and write bandwidths, the upstream lanes and downstream lanes are dynamically reconfigured. The interconnect segments include interconnect links such as Compute Exchange Link (CXL) flex buses and memory channels for local memory implementations, and fabric links for remote memory implementations. For local memory, management messages may be used to provide telemetry information containing the expected read and write bandwidths.

Abstract: An apparatus and/or system is described including a memory device including a memory range and a temporal data management unit (TDMU) coupled to the memory device to receive from an interface, the memory range and a temporal range corresponding to validity of data in the memory range, check the temporal range against a time and/or date value provided by a timer or clock to identify the data in the memory range as expired, and invalidate the data that is expired in the memory device. In some embodiments, the TDMU includes hardware logic that resides on a memory module with the memory device and is coupled to invalidate expired data when the memory module is decoupled from the interface. Other embodiments may be disclosed and claimed.

Abstract: Examples described herein relate to allocation of an amount of memory for a time duration based on receipt of a request to allocate an amount of memory for a time duration. The request can include a configuration that requests an allocation of the amount of memory and the configuration specifies a time tier and/or the time duration. The request can specify one or more of: a request identifier, the amount of memory to allocate, or a requested time duration to reserve the amount of memory.

Abstract: Technologies for providing dynamic selection of edge and local accelerator resources includes a device having circuitry to identify a function of an application to be accelerated, determine one or more properties of an accelerator resource available at the edge of a network where the device is located, and determine one or more properties of an accelerator resource available in the device. Additionally, the circuitry is to determine a set of acceleration selection factors associated with the function, wherein the acceleration factors are indicative of one or more objectives to be satisfied in the acceleration of the function. Further, the circuitry is to select, as a function of the one or more properties of the accelerator resource available at the edge, the one or more properties of the accelerator resource available in the device, and the acceleration selection factors, one or more of the accelerator resources to accelerate the function.

Abstract: Methods, apparatus and systems for adaptive fabric allocation for local and remote emerging memories-based prediction schemes. In conjunction with performing memory transfers between a compute host and memory device connected via one or more interconnect segments, memory read and write traffic is monitored for at least one interconnect segment having reconfigurable upstream lanes and downstream lanes. Predictions of expected read and write bandwidths for the at least one interconnect segment are then made. Based on the expected read and write bandwidths, the upstream lanes and downstream lanes are dynamically reconfigured. The interconnect segments include interconnect links such as Compute Exchange Link (CXL) flex buses and memory channels for local memory implementations, and fabric links for remote memory implementations. For local memory, management messages may be used to provide telemetry information containing the expected read and write bandwidths.

Abstract: Methods, apparatus, systems and machine-readable storage media of an edge computing device which is enabled to access and select the use of local or remote acceleration resources for edge computing processing is disclosed. In an example, an edge computing device obtains first telemetry information that indicates availability of local acceleration circuitry to execute a function, and obtains second telemetry that indicates availability of a remote acceleration function to execute the function. An estimated time (and cost or other identifiable or estimateable considerations) to execute the function at the respective location is identified. The use of the local acceleration circuitry or the remote acceleration resource is selected based on the estimated time and other appropriate factors in relation to a service level agreement.

Abstract: Reliability, availability, and serviceability (RAS)-based memory domains can enable applications to store data in memory domains having different degrees of reliability to reduce downtime and data corruption due to memory errors. In one example, memory resources are classified into different RAS-based memory domains based on their expected likelihood of encountering errors. The mapping of memory resources into RAS-based memory domains can be dynamically managed and updated when information indicative of reliability (such as the occurrence of errors or other information) suggests that a memory resource is becoming less reliable. The RAS-based memory domains can be exposed to applications to enable applications to allocate memory in high reliability memory for critical data.

Abstract: In one embodiment, an apparatus comprises a fabric controller of a first computing node. The fabric controller is to receive, from a second computing node via a network fabric that couples the first computing node to the second computing node, a request to execute a kernel on a field-programmable gate array (FPGA) of the first computing node; instruct the FPGA to execute the kernel; and send a result of the execution of the kernel to the second computing node via the network fabric.

Abstract: Embodiments of the invention include a machine-readable medium having stored thereon at least one instruction, which if performed by a machine causes the machine to perform a method that includes decoding, with a node, an invalidate instruction; and executing, with the node, the invalidate instruction for invalidating a memory range specified across a fabric interconnect.

Abstract: Generally discussed herein are systems, devices, and methods for prefetcher in a multi-tiered memory (DSM) system. A node can include a network interface controller (NIC) comprising system address decoder (SAD) circuitry configured to determine a node identification of a node to which a memory request from a processor is homed, and prefetcher circuitry communicatively coupled to the SAD circuitry, the prefetcher circuitry to determine, based on an address in the memory request, one or more addresses from which to prefetch data, the one or more addresses corresponding to respective entries in a memory of a node on a different network than the NIC.

Abstract: Technologies for providing deduplication of data in an edge network includes a compute device having circuitry to obtain a request to write a data set. The circuitry is also to apply, to the data set, an approximation function to produce an approximated data set. Additionally, the circuitry is to determine whether the approximated data set is already present in a shared memory and write, to a translation table and in response to a determination that the approximated data set is already present in the shared memory, an association between a local memory address and a location, in the shared memory, where the approximated data set is already present. Additionally, the circuitry is to increase a reference count associated with the location in the shared memory.

Abstract: Technologies for quality of service based throttling in a fabric architecture include a network node of a plurality of network nodes interconnected across the fabric architecture via an interconnect fabric. The network node includes a host fabric interface (HFI) configured to facilitate the transmission of data to/from the network node, monitor quality of service levels of resources of the network node used to process and transmit the data, and detect a throttling condition based on a result of the monitored quality of service levels. The HFI is further configured to generate and transmit a throttling message to one or more of the interconnected network nodes in response to having detected a throttling condition. The HFI is additionally configured to receive a throttling message from another of the network nodes and perform a throttling action on one or more of the resources based on the received throttling message. Other embodiments are described herein.

Abstract: There is disclosed in one example an application-specific integrated circuit (ASIC), including: an artificial intelligence (AI) circuit; and circuitry to: identify a flow, the flow including traffic diverted from a core cloud service of a network to be serviced by an edge node closer to an edge of the network than to the core of the network; receive telemetry related to the flow, the telemetry including fine-grained and flow-level network monitoring data for the flow; operate the AI circuit to predict, from the telemetry, a future service-level demand for the edge node; and cause a service parameter of the edge node to be tuned according to the prediction.

Abstract: An embodiment of an electronic apparatus may comprise one or more substrates and a controller coupled to the one or more substrates, the controller including circuitry to apply a reliability, availability, and serviceability (RAS) policy for access to a memory in accordance with a first RAS scheme, change the applied RAS policy in accordance with a second RAS scheme at runtime, where the second RAS scheme is different from the first RAS scheme, and access the memory in accordance with the applied RAS policy. Other embodiments are disclosed and claimed.

Abstract: Methods and apparatus for software-assisted sparse memory. A processor including a memory controller is configured to implement one or more portions of the memory space for memory accessed via the memory controller as sparse memory regions. The amount of physical memory used for a sparse memory region is a fraction of the address range for the sparse memory region, where only non-zero data are written to the physical memory. Mechanisms are provided to detect memory access requests for memory in a sparse memory region and perform associated operations, while non-sparse memory access operations are performed when accessing memory that is not in a sparse memory region. Interfaces are provided to enable software to request allocation of a new sparse memory region or allocate sparse memory from an existing sparse memory region. Operations associated with access to sparse memory regions include detecting whether data for read and write request are all zeros.

Abstract: There is disclosed in one example an application-specific integrated circuit (ASIC), including: an artificial intelligence (Al) circuit; and circuitry to: identify a flow, the flow including traffic diverted from a core cloud service of a network to be serviced by an edge node closer to an edge of the network than to the core of the network; receive telemetry related to the flow, the telemetry including fine-grained and flow-level network monitoring data for the flow; operate the Al circuit to predict, from the telemetry, a future service-level demand for the edge node; and cause a service parameter of the edge node to be tuned according to the prediction.

Abstract: Technologies for providing selective offload of execution of an application to the edge include a device that includes circuitry to determine whether a section of an application to be executed by the device is available to be offloaded. Additionally, the circuitry is to determine one or more characteristics of an edge resource available to execute the section. Further, the circuitry is to determine, as a function of the one or more characteristics and a target performance objective associated with the section, whether to offload the section to the edge resource and offload, in response to a determination to offload the section, the section to the edge resource.

Abstract: Technologies for providing efficient data access in an edge infrastructure include a compute device comprising circuitry configured to identify pools of resources that are usable to access data at an edge location. The circuitry is also configured to receive a request to execute a function at an edge location. The request identifies a data access performance target for the function. The circuitry is also configured to map, based on a data access performance of each pool and the data access performance target of the function, the function to a set of the pools to satisfy the data access performance target.

Abstract: Memory controller systems, methods and apparatus for memory access and scheduling are herein disclosed. In some aspects, a memory controller includes a clock, a first interface to be coupled with a first memory device via a common memory channel, and a second interface to be coupled with a second memory device via the common memory channel. The memory controller also includes a register to store data to store data to indicate an access scheme to process access requests to the first memory device according to a first timing scheme and issue access requests to the second memory device according to a second timing scheme. The memory controller further includes logic to cause the access scheme to be implemented in order to issue access requests to the first memory device or to issue access requests to the second memory device via the common memory channel.

Abstract: Technologies for providing dynamic selection of edge and local accelerator resources includes a device having circuitry to identify a function of an application to be accelerated, determine one or more properties of an accelerator resource available at the edge of a network where the device is located, and determine one or more properties of an accelerator resource available in the device. Additionally, the circuitry is to determine a set of acceleration selection factors associated with the function, wherein the acceleration factors are indicative of one or more objectives to be satisfied in the acceleration of the function. Further, the circuitry is to select, as a function of the one or more properties of the accelerator resource available at the edge, the one or more properties of the accelerator resource available in the device, and the acceleration selection factors, one or more of the accelerator resources to accelerate the function.