An initiator emulator is implemented on a control plane of a switch fabric connected to target ports of a storage array having storage configured with logical partitions. After an initiator port of a server logs into the switch fabric and is blocked from discovering the target ports, the initiator emulator, acting as proxy for the initiator port, discovers information that indicates logical partition masking enforced at the target ports for the initiator port. The initiator emulator determines allowed (initiator (I), target (T)) (I, T) port combinations that should be allowed access via the switch fabric based on the information from the discovery. The initiator emulator configures the switch fabric with one or more zones based on the allowed (I, T) port combinations. The initiator emulator then sends to the initiator port an indication of a zone change to the switch fabric.

Techniques in advanced deep learning provide improvements in one or more of accuracy, performance, and energy efficiency. An array of processing elements performs flow based computations on wavelets of data. Each processing element has a compute element and a routing element. Each compute element has memory. Each router enables communication via wavelets with nearest neighbors in a 2D mesh. A compute element receives a wavelet. If a control specifier of the wavelet is a first value, then instructions are read from the memory of the compute element in accordance with an index specifier of the wavelet. If the control specifier is a second value, then instructions are read from the memory of the compute element in accordance with a virtual channel specifier of the wavelet. Then the compute element initiates execution of the instructions.

An external processing system includes a port configured to exchange signals with a router and one or more processors configured to instantiate an operating system and a hypervisor based on information provided by the router in response to the external processing system being connected to the router. The processors implement a user plane layer that generates feedback representative of a processing load and provides the feedback to the router via the port. The router includes a port allocated to an external processing system and a controller that provides the information representing the operating system and hypervisor in response to connection of the external processing system. The controller also receives feedback indicating a processing load at the external processing system. A queue holds packets prior to providing the packets to the external processing system. The controller discards one or more of the packets from the queue based on the feedback.

A network processor provides for in-line encryption and decryption of received and transmitted packets. For packet transmittal, a processor core generates packet data for encryption and forwards an encryption instruction to a cryptographic unit. The cryptographic unit generates an encrypted packet, and enqueues a send descriptor to a network interface controller, which, in turn, constructs and transmits an outgoing packet. For received encrypted packets, the network interface controller communicates with the cryptographic unit to decrypt the packet prior to enqueuing work to the processor core, thereby providing the processor core with a decrypted packet.

Techniques in advanced deep learning provide improvements in one or more of accuracy, performance, and energy efficiency. An array of processing elements performs flow-based computations on wavelets of data. Each processing element comprises a respective compute element and a respective routing element. Each compute element comprises virtual input queues. Each router enables communication via wavelets with at least nearest neighbors in a 2D mesh. Routing is controlled by respective virtual channel specifiers in each wavelet and routing configuration information in each router. Each router comprises data queues. The virtual input queues of the compute element and the data queues of the router are managed in accordance with the virtual channels. Backpressure information, per each of the virtual channels, is generated, communicated, and used to prevent overrun of the virtual input queues and the data queues.

The present invention discloses a packet control method and a node device, to improve reliability of a data flow in a transmission process. The method includes: After receiving a pause frame, a first node automatically applies, based on adjustment information that is of a send queue of a data flow and that is recorded in a state record set, the pause frame to all queues associated in an adjustment process of the send queue of the data flow. In this way, a packet loss problem in a data transmission process can be avoided without adjusting an XOFF/XON threshold of a receive queue and without increasing a quantity of pause frames in a network system, thereby improving reliability of the data flow in the transmission process.

Examples describe a manner of scheduling packet segment fetches at a rate that is based on one or more of: a packet drop indication, packet drop rate, incast level, operation of queues in SAF or VCT mode, or fabric congestion level. Headers of packets can be fetched faster than payload or body portions of packets and processed prior to queueing of all body portions. In the event a header is identified as droppable, fetching of the associated body portions can be halted and any body portion that is queued can be discarded. Fetch overspeed can be applied for packet headers or body portions associated with packet headers that are approved for egress.

Techniques in advanced deep learning provide improvements in one or more of accuracy, performance, and energy efficiency. An array of processing elements performs flow-based computations on wavelets of data. Each processing element has a compute element and a routing element. Each router enables communication via wavelets with at least nearest neighbors in a 2D mesh. Routing is controlled by virtual channel specifiers in each wavelet and routing configuration information in each router. Execution of an activate instruction or completion of a fabric vector operation activates one of the virtual channels. A virtual channel is selected from a pool comprising previously activated virtual channels and virtual channels associated with previously received wavelets. A task corresponding to the selected virtual channel is activated by executing instructions corresponding to the selected virtual channel.

Techniques in advanced deep learning provide improvements in one or more of accuracy, performance, and energy efficiency. An array of processing elements performs flow-based computations on wavelets of data. Each processing element has a compute element and a routing element. Each router enables communication via wavelets with at least nearest neighbors in a 2D mesh. Routing is controlled by virtual channel specifiers in each wavelet and routing configuration information in each router. Execution of an activate instruction or completion of a fabric vector operation activates one of the virtual channels. A virtual channel is selected from a pool comprising previously activated virtual channels and virtual channels associated with previously received wavelets. A task corresponding to the selected virtual channel is activated by executing instructions corresponding to the selected virtual channel.

An apparatus for load balancing based on available bandwidth estimation includes a bandwidth module configured to determine for a networking device a first available bandwidth estimate for a first egress port and a second available bandwidth estimate for a second egress port, a load balancing module configured to select the first egress port as a selected port in response to determining that the first available bandwidth estimate of the first egress port exceeds a predetermined level and to select the second egress port as the selected port in response to determining that the available bandwidth estimate of the first egress port does not exceed the predetermined level and that the second available bandwidth estimate of the second egress port exceeds the predetermined level, and a transmission module configured to transmit a packet from the selected port. A method and network switching device work similarly to the apparatus.