A new processing architecture is described in which a data processing unit (DPU) is utilized within a device. Unlike conventional compute models that are centered around a central processing unit (CPU), example implementations described herein leverage a DPU that is specially designed and optimized for a data-centric computing model in which the data processing tasks are centered around, and the primary responsibility of, the DPU. For example, various data processing tasks, such as networking, security, and storage, as well as related work acceleration, distribution and scheduling, and other such tasks are the domain of the DPU. The DPU may be viewed as a highly programmable, high-performance input/output (I/O) and data-processing hub designed to aggregate and process network and storage I/O to and from multiple other components and/or devices. This frees resources of the CPU, if present, for computing-intensive tasks.

An access node that can be configured and optimized to perform input and output (I/O) tasks, such as storage and retrieval of data to and from network devices (such as solid state drives), networking, data processing, and the like. For example, the access node may be configured to receive data to be processed, wherein the access node includes a plurality of processing cores, a data network fabric, and a control network fabric; receive, over the control network fabric, a work unit message indicating a processing task to be performed a processing core; and process the work unit message, wherein processing the work unit message includes retrieving data associated with the work unit message over the data network fabric.

A new processing architecture is described in which a data processing unit (DPU) is utilized within a device. Unlike conventional compute models that are centered around a central processing unit (CPU), example implementations described herein leverage a DPU that is specially designed and optimized for a data-centric computing model in which the data processing tasks are centered around, and the primary responsibility of, the DPU. For example, various data processing tasks, such as networking, security, and storage, as well as related work acceleration, distribution and scheduling, and other such tasks are the domain of the DPU. The DPU may be viewed as a highly programmable, high-performance input/output (I/O) and data-processing hub designed to aggregate and process network and storage I/O to and from multiple other components and/or devices. This frees resources of the CPU, if present, for computing-intensive tasks.

A new processing architecture is described in which a data processing unit (DPU) is utilized within a device. Unlike conventional compute models that are centered around a central processing unit (CPU), example implementations described herein leverage a DPU that is specially designed and optimized for a data-centric computing model in which the data processing tasks are centered around, and the primary responsibility of, the DPU. For example, various data processing tasks, such as networking, security, and storage, as well as related work acceleration, distribution and scheduling, and other such tasks are the domain of the DPU. The DPU may be viewed as a highly programmable, high-performance input/output (I/O) and data-processing hub designed to aggregate and process network and storage I/O to and from multiple other components and/or devices. This frees resources of the CPU, if present, for computing-intensive tasks.

An access node that can be configured and optimized to perform input and output (I/O) tasks, such as storage and retrieval of data to and from network devices (such as solid state drives), networking, data processing, and the like. For example, the access node may be configured to receive data to be processed, wherein the access node includes a plurality of processing cores, a data network fabric, and a control network fabric; receive, over the control network fabric, a work unit message indicating a processing task to be performed a processing core; and process the work unit message, wherein processing the work unit message includes retrieving data associated with the work unit message over the data network fabric.

A highly-programmable access node is described that can be configured and optimized to perform input and output (I/O) tasks, such as storage and retrieval of data to and from storage devices (such as solid state drives), networking, data processing, and the like. For example, the access node may be configured to execute a large number of data I/O processing tasks relative to a number of instructions that are processed. The access node may be highly programmable such that the access node may expose hardware primitives for selecting and programmatically configuring data processing operations. As one example, the access node may be used to provide high-speed connectivity and I/O operations between and on behalf of computing devices and storage components of a network, such as for providing interconnectivity between those devices and a switch fabric of a data center.

Examples of methods, apparatus, and computer program products are disclosed for facilitating access to one or more services in a network environment. At a host, a request is received from a client machine in communication with the host over a network. An asynchronous service description file indicates one or more asynchronous communication techniques configured to be performed to access or communicate with a service over the network. The asynchronous service description file is a conversion of a synchronous service description file indicating one or more synchronous communication techniques for accessing or communicating with a synchronous service. The asynchronous service description file is provided to the client machine.

A new processing architecture is described in which a data processing unit (DPU) is utilized within a device. Unlike conventional compute models that are centered around a central processing unit (CPU), example implementations described herein leverage a DPU that is specially designed and optimized for a data-centric computing model in which the data processing tasks are centered around, and the primary responsibility of, the DPU. For example, various data processing tasks, such as networking, security, and storage, as well as related work acceleration, distribution and scheduling, and other such tasks are the domain of the DPU. The DPU may be viewed as a highly programmable, high-performance input/output (I/O) and data-processing hub designed to aggregate and process network and storage I/O to and from multiple other components and/or devices. This frees resources of the CPU, if present, for computing-intensive tasks.

A highly-programmable access node is described that can be configured and optimized to perform input and output (I/O) tasks, such as storage and retrieval of data to and from storage devices (such as solid state drives), networking, data processing, and the like. For example, the access node may be configured to execute a large number of data I/O processing tasks relative to a number of instructions that are processed. The access node may be highly programmable such that the access node may expose hardware primitives for selecting and programmatically configuring data processing operations. As one example, the access node may be used to provide high-speed connectivity and I/O operations between and on behalf of computing devices and storage components of a network, such as for providing interconnectivity between those devices and a switch fabric of a data center.

A method of statistical multiplexing with one of Layer 0 Flexible Grid optical spectrum and Layer 1 Time Division Multiplexed (TDM) bandwidth in a multi-layer network includes obtaining a sampling of bandwidth usage over time on ports and links in the multi-layer network for one of Layer 0 and Layer 1 traffic using a plurality of statistical parameters, wherein the plurality of statistical parameters are defined for the one of Layer 0 and Layer 1 traffic; monitoring the plurality of statistical parameters; and triggering based on the monitoring one of i) adjustments to the one of Layer 0 and Layer 1 traffic and ii) adjustments to routing parameters on the links for new traffic, wherein the triggering is one of through a control plane and a Software Defined Networking (SDN) controller.