The embodiments herein describe a 3D SmartNIC that spatially distributes compute, storage, or network functions in three dimensions using a plurality of layers. That is, unlike current SmartNIC that can perform acceleration functions in a 2D, a 3D Smart can distribute these functions across multiple stacked layers, where each layer can communicate directly or indirectly with the other layers.

Racks and rack systems to support a plurality of sleds are disclosed herein. A rack comprises an elongated support post and a plurality of support chassis. The elongated support post extends vertically. The plurality of support chassis are coupled to the elongated support post. Each support chassis of the plurality of support chassis is sized to house a corresponding sled of the plurality of sleds.

A network input/output structure of an electronic device includes a FPGA module, a multiple of UART voltage conversion transceivers, at least one network connector and at least one detection module. Each UART voltage conversion transceiver has an input/output pin definition of a brand specification of a network device. The FPGA module uses the detection module to detect the pin definition of an external network device to confirm the brand specification of the network device and turn on a voltage conversion chip of the UART voltage conversion transceiver of the brand specification, so that the external network device can transmit network information with the electronic device automatically.

Technologies for allocating resources across data centers include a compute device to obtain resource utilization data indicative of a utilization of resources for a managed node to execute a workload. The compute device is also to determine whether a set of resources presently available to the managed node in a data center in which the compute device is located satisfies the resource utilization data. Additionally, the compute device is to allocate, in response to a determination that the set of resources presently available to the managed node does not satisfy the resource utilization data, a supplemental set of resources to the managed node. The supplemental set of resources are located in an off-premises data center that is different from the data center in which the compute device is located. Other embodiments are also described and claimed.

Techniques for implementing hardware-assisted memory disaggregation with recovery from network failures/problems are provided. In one set of embodiments, a hardware controller of a computer system can maintain a copy of a “remote memory” of the computer system (i.e., a section of the physical memory address space of the computer system that maps to a portion of the physical system memory of a remote computer system) in a local backup memory. The backup memory may be implemented using a non-volatile memory that is slower, but also less expensive, than conventional dynamic random-access memory (DRAM). Then, if the hardware controller is unable to retrieve data in the remote memory from the remote computer system within a specified time window due to, e.g., a network failure or other problem, the hardware controller can retrieve the data from the backup memory, thereby avoiding a hardware error condition (and potential application/system crash).

Technologies for load balancing a storage network include a system. The system includes circuitry to adjust routing rules in a network interface controller to deliver a packet from one of multiple uplinks to one of any physical functions, circuitry to remap, in response to a failure of a switch, a port from one physical function to another physical function, and circuitry to communicate control data between a software defined network controller and one or more agents in one or more host endpoints with a hierarchical distributed hashing table.

Techniques for implementing hardware-assisted memory disaggregation with recovery from network failures/problems are provided. In one set of embodiments, a hardware controller of a computer system can maintain a copy of a “remote memory” of the computer system (i.e., a section of the physical memory address space of the computer system that maps to a portion of the physical system memory of a remote computer system) in a local backup memory. The backup memory may be implemented using a non-volatile memory that is slower, but also less expensive, than conventional dynamic random-access memory (DRAM). Then, if the hardware controller is unable to retrieve data in the remote memory from the remote computer system within a specified time window due to, e.g., a network failure or other problem, the hardware controller can retrieve the data from the backup memory, thereby avoiding a hardware error condition (and potential application/system crash).

The embodiments herein describe a 3D SmartNIC that spatially distributes compute, storage, or network functions in three dimensions using a plurality of layers. That is, unlike current SmartNIC that can perform acceleration functions in a 2D, a 3D Smart can distribute these functions across multiple stacked layers, where each layer can communicate directly or indirectly with the other layers.

Technologies for providing streamlined provisioning of accelerated functions in a disaggregated architecture include a compute sled. The compute sled includes a network interface controller and circuitry to determine whether to accelerate a function of a workload executed by the compute sled, and send, to a memory sled and in response to a determination to accelerate the function, a data set on which the function is to operate. The circuitry is also to receive, from the memory sled, a service identifier indicative of a memory location independent handle for data associated with the function, send, to a compute device, a request to schedule acceleration of the function on the data set, receive a notification of completion of the acceleration of the function, and obtain, in response to receipt of the notification and using the service identifier, a resultant data set from the memory sled. The resultant data set was produced by an accelerator device during acceleration of the function on the data set. Other embodiments are also described and claimed.

One example provides an integrated computing device, comprising one or more computing clusters, and one or more network controllers, each network controller comprising a local data notification queue to queue send message notifications originating from the computing clusters on the integrated computing device, a remote data notification queue to queue receive message notifications originating from network controllers on remote integrated computing devices, a local no-data notification queue to queue receive message notifications originating from computing clusters on the integrated computing device, and a connection scheduler configured to schedule sending of data from memory on the integrated computing device when a send message notification in the local data notification queue is matched with a receive message notification in the remote data notification queue, and to schedule sending of receive message notifications from the local no-data notification queue.