Fungible, Inc.

Microsoft Technology Licensing, LLC

Chelsio Communications, Inc.

Felix A Marti

Wael Noureddine

Jean-Marc Frailong

Bertrand Serlet

Pradeep S Sindhu

Rajan Goyal

Deepak Goel

Paul Kim

Charles Edward Gray

Asgeir Thor Eiriksson

Aibing Zhou

Dimitrios Michailidis

Hoai Vu Thanh Tran

Aravind Vidhyasagar Lappasi

Leith Alan Leedom

Dmitriy Leonidovich Budko

Gaurav Gupte

Rajesh Nair

Pratapa Reddy Vaka

Rajesh G Nair

A new processing architecture is described that utilizes a data processing unit (DPU). Unlike conventional compute models that are centered around a central processing unit (CPU), the DPU that is designed for a data-centric computing model in which the data processing tasks are centered around the DPU. The DPU may be viewed as a highly programmable, high-performance I/O and data-processing hub designed to aggregate and process network and storage I/O to and from other devices. The DPU comprises a network interface to connect to a network, one or more host interfaces to connect to one or more application processors or storage devices, and a multi-core processor with two or more processing cores executing a run-to-completion data plane operating system and one or more processing cores executing a multi-tasking control plane operating system. The data plane operating system is configured to support software functions for performing the data processing tasks.

Data processing unit for stream processing

Techniques are described for providing a scaled-out transport supported by interconnected data processing units (DPUs) that operates as a single system bus connection proxy for device-to-device communications within a data center. As one example, this disclosure describes techniques for providing a Peripheral Component Interconnect Express (PCIe) proxy for device-to-device communications employing the PCIe standard. The disclosed techniques include adding PCIe proxy logic on top of a host unit of a DPU to expose a PCIe proxy model to application processors, storage devices, network interface controllers, field programmable gate arrays, or other PCIe endpoint devices. The PCIe proxy model may be implemented as a physically distributed Ethernet-based switch fabric with PCIe proxy logic at the edge and fronting the PCIe endpoint devices. The interconnected DPUs and the distributed Ethernet-based switch fabric together provide a reliable, low-latency, and scaled-out transport that operates as a PCIe proxy.

Scaled-out transport as connection proxy for device-to-device communications

Techniques are described in which a system having multiple processing units processes a series of work units in a processing pipeline, where some or all of the work units access or manipulate data stored in non-coherent memory. In one example, this disclosure describes a method that includes identifying, prior to completing processing of a first work unit with a processing unit of a processor having multiple processing units, a second work unit that is expected to be processed by the processing unit after the first work unit. The method also includes processing the first work unit, and prefetching, from non-coherent memory, data associated with the second work unit into a second cache segment of the buffer cache, wherein prefetching the data associated with the second work unit occurs concurrently with at least a portion of the processing of the first work unit by the processing unit.

Efficient work unit processing in a multicore system

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.

Data processing unit for compute nodes and storage nodes

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.

Access node for data centers

Techniques are described in which a device, such as a network device, compute node or storage device, is configured to utilize a work unit (WU) stack data structure in a multiple core processor system to help manage an event driven, run-to-completion programming model of an operating system executed by the multiple core processor system. The techniques may be particularly useful when processing streams of data at high rates. The WU stack may be viewed as a stack of continuation work units used to supplement a typical program stack as an efficient means of moving the program stack between cores. The work unit data structure itself is a building block in the WU stack to compose a processing pipeline and services execution. The WU stack structure carries state, memory, and other information in auxiliary variables.

Work unit stack data structures in multiple core processor system for stream data processing

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.

Access node integrated circuit for data centers which includes a networking unit, a plurality of host units, processing clusters, a data network fabric, and a control network fabric

A host is coupled to a network via an intelligent network adaptor. The host is executing an application configured to receive application data from a peer via the network and the intelligent network adaptor using a stateful connection according to a connection-oriented protocol. The intelligent network adaptor performs protocol processing of the connection. Application data is copied from host memory not configured for access by the application (possibly OS-associated host memory) to host memory associated with the application (application-associated host memory). The application data is received from the peer by the intelligent network adaptor and copied to host memory not configured for access by the application. The operating system selectively provides, to the intelligent network adaptor, information of the memory associated with the application. At least one portion of the application data for the connection is provided directly from the intelligent network adaptor to the memory associated with the application.

Growing community of inventors

San Francisco, CA, United States of America

Felix A Marti