A packet processing method and device are provided, to save CPU resources consumed by parsing a packet. The method includes: parsing, by an intelligent network interface card, a received first packet to obtain an identifier of the first packet; updating, by the intelligent network interface card, a control field of a first memory buffer based on the identifier of the first packet; storing, by the intelligent network interface card, a payload of the first packet or a packet header and a payload of the first packet into the first address space through DMA based on an aggregation position of the first packet; aggregating, by a host, the first address information and at least one piece of second address information based on an updated control field in the first mbuf; and reading, by a virtual machine, address information, to obtain data in an address space indicated by the address information.

Systems, apparatuses, and methods for implementing a primary input/output (PIO) queue for host and guest operating systems (OS's) are disclosed. A system includes a PIO queue, one or more compute units, and a control unit. The PIO queue is able to store work commands for multiple different types of OS's, including host and guest OS's. The control unit is able to dispatch multiple work commands from multiple OS's to execute concurrently on the compute unit(s). This allows for execution of work commands by different OS's without the processing device(s) having to incur the latency of a world switch.

A neural network operation method and apparatus are disclosed, where the network operation method including receiving data for a neural network operation, determining whether a size of the data is less than or equal to a threshold, generating stacked data by stacking a portion of the data based on the determining, and performing the neural network operation in parallel based on the stacked data.

A method, computer program product, and computing system for coupling a multi-host remote direct memory access (RDMA) card to at least a pair of central processing units (CPUs). One or more signals may be routed, via the multi-host RDMA card, between the at least a pair of CPUs.

An apparatus is provided comprising storage elements to store data blocks, where each data block has capability metadata associated therewith identifying whether the data block specifies a capability, at least one capability type being a bounded pointer. Processing circuitry is then arranged to be responsive to a bulk capability metadata operation identifying a plurality of the storage elements, to perform an operation on the capability metadata associated with each data block stored in the plurality of storage elements. Via a single specified operation, this hence enables query and/or modification operations to be performed on multiple items of capability metadata, hence providing more efficient access to such capability metadata.

Systems, methods, and devices for software-driven resource reservation of an input/output memory management unit (IOMMU) are provided. A system may include a peripheral device and a processing device. The peripheral device may be accessible to a virtual machine running on the processing device via direct memory access (DMA) that is translated by an IOMMU). The processing device may run the virtual machine and a virtual machine manager. The processing device also includes the IOMMU, which is configurable to reserve a subset of resources of the IOMMU to the virtual machine based on a descriptor provided by the virtual machine manager.

System and method for implementing accelerated memory transfers in an integrated circuit includes identifying memory access parameters for configuring memory access instructions for accessing a target corpus of data from within a defined region of an n-dimensional memory; converting the memory access parameters to direct memory access (DMA) controller-executable instructions, wherein the converting includes: (i) defining dimensions of a data access tile based on a first parameter of the memory access parameters; (ii) generating multi-directional data accessing instructions that, when executed, automatically moves the data access tile along multiple distinct axes within the defined region of the n-dimensional memory based at least on a second parameter of the memory access parameters; transferring a corpus of data from the n-dimensional memory to a target memory based on executing the DMA controller-executable instructions.

Methods, apparatus, systems, and articles of manufacture are disclosed. An example apparatus includes interface circuitry to receive an analog signal. The example apparatus also includes sequencer circuitry to: determine whether the apparatus is to operate in a single transfer state or a multiple transfer state; access a configuration from a control register in a plurality of control registers; initiate a conversion of the analog signal to a digital value based on the configuration; and write the digital value to a result register in a plurality of result registers based on the determination.

Systems and methods are presented for secured communications in a controller area network for a vehicle system. A first electronic processor is communicatively coupled to a memory and configured to operate one or more vehicle systems. A second electronic processor is configured to generate message authentication codes to verify data communications between the first electronic processor and at least one other vehicle system controller in the controller area network. The direct memory access (DMA) module is configured to facilitate direct communications between the second electronic processor and the memory so that the first electronic processor can continue to execute other instructions while message authentication codes are generated by the second electronic processor for incoming and outgoing message data.

A matrix operation method is provided, applied to an accelerator configured to perform a matrix operation. A matrix operation accelerator (100) respectively stores, in response to a received matrix operation instruction, subsets of a first matrix and subsets of a second matrix in a first storage space and a second storage space of a memory (120); stores, in a third storage space of the memory (120), subsets obtained after the subsets of the first matrix are multiplied by the subsets of the second matrix; and performs matrix operations on the subsets of the first matrix and the subsets of the second matrix based on the matrix operation instruction, to obtain matrix operation results. The dedicated matrix operation accelerator (100) is used to perform a matrix operation, so that a large-scale matrix operation can be completed in relatively short time, thereby offloading a matrix operation burden of a processor.