36results about How to "Reduce data transfer overhead" patented technology

A VLAN tagging unit associated with a WAN is used to add VLAN tags based upon logical interfaces. In one example, data received across the logical interface is tagged with an associated VLAN ID by the unit. In another embodiment, flow-based VLAN tagging is done in which in addition to the logical interface other indications are used in the VLAN tagging.

The invention provides a training system of back propagation neural network DNN (Deep Neural Network). The training system of the back propagation neural network DNN comprises a first graphics processor assembly, a second graphics processor assembly and a controller assembly, wherein the first graphics processor assembly is used for performing DNN forward calculation and weight update calculation; the second graphics processor assembly is used for perform DNN forward calculation and DNN back calculation; the controller assembly is used for controlling the first graphics processor assembly and the second graphics processor assembly to perform Nth-layer DNN forward calculation respectively according to respective input data, and after the completion of the forward calculation, controlling the first graphics processor assembly to perform the weight update calculation and controlling the second graphics processor assembly to perform the DNN back calculation; and N is a positive integer. The training system provided by the invention has the advantages of high training speed and low data transmission cost, so that the training speed of the back propagation neural network DNN is promoted.

The present disclosure relates to a communication technique for convergence of a 5G communication system for supporting a higher data transmission rate beyond a 4G system with an IoT technology, and a system therefor. The present disclosure may be applied to an intelligent service (for example, smart home, smart building, smart city, smart car or connected car, health care, digital education, retail business, security and safety-related service, etc.) on the basis of a 5G communication technology and an IoT-related technology. The present disclosure relates to a method of a terminal, the method comprising the steps of: determining a path loss reference beam on the basis of whether information indicating the path loss reference beam is received; obtaining a path loss on the basis of the path loss reference beam; obtaining a power headroom (PH) on the basis of the path loss; and transmitting a power headroom report (PHR) including the PH.

The invention discloses a data acquisition method and device based on a Spark computing framework. The method includes the steps of receiving a table object access request, and acquiring computing resource information of Spark and data distribution information of a data table to be accessed in an MPP cluster; generating a plurality of Partitions according to the computing resource information andthe data distribution information, wherein each Partition corresponds to part of the data in the data table; obtaining the data table from the MPP cluster by generating the Partitions. The method fully utilizes the data storage characteristics of the MPP cluster, and quickly acquires a data set directly from a storage node of the MPP through the multiple Partitions. Further, in the case that computing resources are sufficient, the data table of the storage node may be further split to achieve the purpose of improving parallelism and improving data import performance. According to the data distribution condition of the MPP cluster, data can be preferentially obtained from local storage, data transmission overhead is reduced, network bandwidth is saved, network delay is reduced, and computing performance is improved.

Accessing privileged objects in a server environment. A privileged object is associated with an application comprising at least one process resource and a corresponding semi-privileged instruction. The association is filed in an entity of an operating system kernel. A central processing unit (CPU) performs an authorization check if the semi-privileged instruction is issued and attempts to access the privileged object. The CPU executes the semi-privileged instruction and grants access to the privileged object if the operating system kernel has issued the semi-privileged instruction; or accesses the entity if a process resource of the application has issued the semi-privileged instruction to determine authorization of the process resource to access the privileged object. Upon positive authorization the CPU executes the semi-privileged instruction and grants access to the privileged object, and upon authorization failure denies execution of the semi-privileged instruction and performs a corresponding authorization check failure handling.

The invention discloses a cooperative spectrum sensing method utilizing space diversity. The method comprises the steps that sensing nodes participating in cooperative spectrum sensing calculate power magnitudes of received signals, the sensing nodes participating in cooperative spectrum sensing send the power magnitudes of the received signals to a fusion center, the fusion center calculates an inspection statistics magnitude according to the power magnitudes of the signals received by the sensing nodes participating in cooperative spectrum sensing, and finally, the fusion center judges whether an authorized user signal exists in the signals received by the sensing nodes to achieve spectrum sensing by comparing the inspection statistics magnitude with a judgment threshold. The method has the advantages that the noise power magnitude does not need to be known, and the performance is close to that of the energy inspection method based on soft combination with the noise power magnitude known.

A method and system for answering set-expression cardinality queries while lowering data communication costs by utilizing a coordinator site to provide global knowledge of the distribution of certain frequently occurring stream elements to significantly reduce the transmission of element state information to the central site and, optionally, capturing the semantics of the input set expression in a Boolean logic formula and using models of the formula to determine whether an element state change at a remote site can affect the set expression result.

The invention provides data decoding method and equipment with uplink coordinated multiple points. The data decoding method comprises the following steps: a main district receives constellation point information from a cooperation district, wherein the data quantity of the constellation point information is smaller than that of uplink data received by the cooperation district; the main district carries out weighted combination on the constellation point information to obtain combined constellation point information; and the main district carries out demodulation and decoding on the combined constellation point information to obtain original information. With the adoption of the technical scheme of the invention, the data transmission cost between the main district and the cooperation district is reduced, the problem that the gain is lowered caused by decoding soft bits after being combined is solved.

The invention discloses an integrated circuit non-pessimistic path analysis method for GPU accelerated calculation. The method comprises the steps of circuit structure flattening, circuit structure layering preprocessing, multi-GPU parallel candidate path generation and global candidate path merging. The multi-GPU parallel candidate path generation comprises the steps of multi-GPU task allocation, delay grouping initialization, parallel delay propagation, parallel progressive candidate path generation and parallel local candidate path pre-merging. According to the invention, by introducing equivalent transformation of an algorithm and a data structure, dense calculation in non-pessimistic time sequence analysis is completed in parallel on a plurality of GPUs, and data and control scheduling work among the GPUs is completed by using a CPU. Through cooperation of a single CPU-multi-GPU heterogeneous calculation model, compared with an original CPU algorithm, the performance can be improved by dozens of times, the calculation cost of non-pessimistic path analysis is greatly reduced, and the invention can be popularized and applied to the technical field of chip design automation.