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: In an example, there is disclosed a host-fabric interface (HFI), including: an interconnect interface to communicatively couple the HFI to an interconnect; a network interface to communicatively couple the HFI to a network; network interface logic to provide communication between the interconnect and the network; a coprocessor configured to provide an offloaded function for the network; a memory; and a caching agent configured to: designate a region of the memory as a shared memory between the HFI and a core communicatively coupled to the HFI via the interconnect; receive a memory operation directed to the shared memory; and issue a memory instruction to the memory according to the memory operation.

Abstract: Embodiments may be generally directed to techniques to cause communication of a registration request between a first end-point and a second end-point of an end-to-end path, the registration request to establish resource load monitoring for one or more resources of the end-to-end path, receive one or more acknowledgements indicating resource loads for each of the one or more resources of the end-to-end path, at least one of the acknowledgements to indicate a resource of the one or more resources is not meeting a threshold requirement for the end-to-end path, and perform an action for communication traffic utilizing the one or more resources based on the acknowledgement.

Abstract: In an example, there is disclosed a host-fabric interface (HFI), including: an interconnect interface to communicatively couple the HFI to an interconnect; a network interface to communicatively couple the HFI to a network; network interface logic to provide communication between the interconnect and the network; a coprocessor configured to provide an offloaded function for the network; a memory; and a caching agent configured to: designate a region of the memory as a shared memory between the HFI and a core communicatively coupled to the HFI via the interconnect; receive a memory operation directed to the shared memory; and issue a memory instruction to the memory according to the memory operation.

Abstract: Data management for edge architected computing systems extends current storage and memory schemes of edge resources to expose interfaces to allow a device, such as an endpoint or client device, or another edge resource, to specify criteria for managing data originating from the device and stored in an edge resource, and extends the storage and memory controllers to manage data in accordance with the criteria, including removing stored data that no longer satisfies the criteria. The criteria includes a temporal hint to specify a time after which the data can be removed, a physical hint to specify a list of edge resources outside of which the data can be removed, an event-based hint to specify an event after which the data can be removed, and a quality of service condition to modify the time specified in the temporal hint based on a condition, such as memory and storage capacity of the edge resource in which the data is managed.

Abstract: An embodiment of an electronic apparatus may include one or more substrates, and logic coupled to the one or more substrates, the logic to allocate a first memory portion to a first application as a combination of a local memory and remote memory, wherein the remote memory is shared between multiple compute nodes, and manage a first memory balloon associated with the first memory portion based on two or more memory tiers associated with the local memory and the remote memory. Other embodiments are disclosed and claimed.

Abstract: An embodiment of a semiconductor apparatus may include technology to receive data with a unique identifier, and bypass encryption logic of a media controller based on the unique identifier. Other embodiments are disclosed and claimed.

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: An embodiment of an electronic apparatus may include one or more substrates, and logic coupled to the one or more substrates, the logic to allocate a first memory portion to a first application as a combination of a local memory and remote memory, wherein the remote memory is shared between multiple compute nodes, and manage a first memory balloon associated with the first memory portion based on two or more memory tiers associated with the local memory and the remote memory. Other embodiments are disclosed and claimed.

Abstract: In accordance with embodiments disclosed herein, there are provided methods, systems, mechanisms, techniques, and apparatuses for presentation of direct accessed storage under a logical drive model; for implementing a distributed architecture for cooperative NVM Data protection; data mirroring for consistent SSD latency; for boosting a controller’s performance and RAS with DIF support via concurrent RAID processing; for implementing arbitration and resource schemes of a doorbell mechanism, including doorbell arbitration for fairness and prevention of attack congestion; and for implementing multiple interrupt generation using a messaging unit and NTB in a controller through use of an interrupt coalescing scheme.

Abstract: In accordance with embodiments disclosed herein, there are provided methods, systems, mechanisms, techniques, and apparatuses for presentation of direct accessed storage under a logical drive model; for implementing a distributed architecture for cooperative NVM Data protection; data mirroring for consistent SSD latency; for boosting a controller's performance and RAS with DIF support via concurrent RAID processing; for implementing arbitration and resource schemes of a doorbell mechanism, including doorbell arbitration for fairness and prevention of attack congestion; and for implementing multiple interrupt generation using a messaging unit and NTB in a controller through use of an interrupt coalescing scheme.

Abstract: There is disclosed an example of an artificial intelligence (AI) system, including: a first hardware platform; a fabric interface configured to communicatively couple the first hardware platform to a second hardware platform; a processor hosted on the first hardware platform and programmed to operate on an AI problem; and a first training accelerator, including: an accelerator hardware; a platform inter-chip link (ICL) configured to communicatively couple the first training accelerator to a second training accelerator on the first hardware platform without aid of the processor; a fabric ICL to communicatively couple the first training accelerator to a third training accelerator on a second hardware platform without aid of the processor; and a system decoder configured to operate the fabric ICL and platform ICL to share data of the accelerator hardware between the first training accelerator and second and third training accelerators without aid of the processor.

Abstract: There is disclosed an example of an artificial intelligence (AI) system, including: a first hardware platform; a fabric interface configured to communicatively couple the first hardware platform to a second hardware platform; a processor hosted on the first hardware platform and programmed to operate on an AI problem; and a first training accelerator, including: an accelerator hardware; a platform inter-chip link (ICL) configured to communicatively couple the first training accelerator to a second training accelerator on the first hardware platform without aid of the processor; a fabric ICL to communicatively couple the first training accelerator to a third training accelerator on a second hardware platform without aid of the processor; and a system decoder configured to operate the fabric ICL and platform ICL to share data of the accelerator hardware between the first training accelerator and second and third training accelerators without aid of the processor.

Abstract: An embodiment of an electronic apparatus may include one or more substrates, and logic coupled to the one or more substrates, the logic to provide an interface to a pooled memory that is configured as a combination of local memory and remote memory, wherein the remote memory is shared between multiple compute nodes, allocate respective memory portions of the pooled memory to respective tenants, associate respective memory balloons with the respective tenants that correspond to the allocated respective memory portions, and manage the respective memory balloons based on the respective tenants and two or more memory tiers associated with the pooled memory. Other embodiments are disclosed and claimed.

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: 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: In accordance with embodiments disclosed herein, there are provided methods, systems, mechanisms, techniques, and apparatuses for presentation of direct accessed storage under a logical drive model; for implementing a distributed architecture for cooperative NVM Data protection; data mirroring for consistent SSD latency; for boosting a controller's performance and RAS with DIF support via concurrent RAID processing; for implementing arbitration and resource schemes of a doorbell mechanism, including doorbell arbitration for fairness and prevention of attack congestion; and for implementing multiple interrupt generation using a messaging unit and NTB in a controller through use of an interrupt coalescing scheme.

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 utilizing a split memory pool include a compute sled. The compute sled includes multiple processors communicatively coupled together through a processor communication link. Each processor is to communicate with a different memory sled through a respective memory network dedicated to the corresponding processor and memory sled. The compute sled includes a compute engine to generate a memory access request to access a memory address in far memory. The far memory includes memory located on one of the memory sleds. The compute engine is also to determine, as a function of the memory address and a map of memory address ranges to the memory sleds, the memory sled on which to access the far memory, and send the memory access request to the determined memory sled to access the far memory associated with the memory address.