38 results about "Performance per watt" patented technology

The invention provides an apparatus and method for realizing an accelerator of a sparse convolutional neural network. According to the invention, the apparatus herein includes a convolutional and pooling unit, a full connection unit and a control unit. The method includes the following steps: on the basis of control information, reading convolutional parameter information, and input data and intermediate computing data, and reading full connected layer weight matrix position information, in accordance with the convolutional parameter information, conducting convolution and pooling on the input data with first iteration times, then on the basis of the full connected layer weight matrix position information, conducting full connection computing with second iteration times. Each input data is divided into a plurality of sub-blocks, and the convolutional and pooling unit and the full connection unit separately operate on the plurality of sub-blocks in parallel. According to the invention, the apparatus herein uses a specific circuit, supports a full connected layer sparse convolutional neural network, uses parallel ping-pang buffer design and assembly line design, effectively balances I / O broadband and computing efficiency, and acquires better performance power consumption ratio.

Systems and methods for designing and generating integrated circuits using a high-level language are described. The high-level language is used to generate performance models, functional models, synthesizable register transfer level code defining the integrated circuit, and verification environments. The high-level language may be used to generate templates for custom computation logical units for specific user-determined functionality. The high-level language and compiler permit optimizations for power savings and custom circuit layout, resulting in integrated circuits with improved performance per watt of power consumption.

The invention discloses a device and a method for executing forward operation of an artificial neural network, and the device comprises a floating point data statistics module which is used for carrying out statistics analysis on various types of required data, and obtaining the decimal point position Point locality of fixed point data; a data conversion unit which is used for realizing conversionfrom the long-bit floating point data type to the short-bit fixed point data type according to the decimal point position of the fixed point data; And a fixed-point data operation module which is used for carrying out artificial neural network forward operation on the short-digit fixed-point data. According to the device disclosed by the invention, the data in the forward operation of the multilayer artificial neural network is represented by using the short-digit fixed points, and the corresponding fixed-point operation module is used, so that the short-digit fixed-point forward operation ofthe artificial neural network is realized, and the performance power consumption ratio of hardware is greatly improved.

Systems and methods for designing and generating integrated circuits using a high-level language are described. The high-level language is used to generate performance models, functional models, synthesizable register transfer level code defining the integrated circuit, and verification environments. The high-level language may be used to generate templates for custom computation logical units for specific user-determined functionality. The high-level language and compiler permit optimizations for power savings and custom circuit layout, resulting in integrated circuits with improved performance per watt of power consumption.

A computing system has a stack of microprocessor chips that are designed to work together in a multiprocessor system. The chips are interconnected with 3D through vias, or alternatively by compatible package carriers having the interconnections, while logically the chips in the stack are interconnected via specialized cache coherent interconnections. All of the chips in the stack use the same logical chip design, even though they can be easily personalized by setting specialized latches on the chips. One or more of the individual microprocessor chips utilized in the stack are implemented in a silicon process that is optimized for high performance while others are implemented in a silicon process that is optimized for power consumption i.e. for the best performance per Watt of electrical power consumed. The hypervisor or operating system controls the utilization of individual chips of a stack.

An apparatus for selecting a function includes a comparison module that compares energy consumption characteristics of a plurality of processors available for execution of a function, where each energy consumption characteristic varies as a function of function size. The apparatus includes a selection module that selects, based on the size of the function, a processor from the plurality of processors with a lowest energy consumption for execution of the function. The apparatus includes an execution module that executes the function on the selected processor.

The invention discloses an energy consumption-oriented cloud workflow scheduling optimization method. The method comprises the following steps: (1) establishing energy consumption-oriented cloud workflow process model and resource model; (2) calculating a task priority; (3) taking out a task t with highest priority from a task set T, finding out a virtual machine set VMt capable of executing the task t, and calculating energy consumption for distributing the task t to each virtual machine in the VMt and completing all distributed tasks; (4) finding out a vm with minimal energy consumption, if only one vm has the minimal energy consumption, distributing the task t to the vm, and if a plurality of vms have the minimal energy consumption, distributing the task t to the vm with characteristics that the vm has the minimal energy consumption and a host in which the vm is located has highest performance per watt; deleting the task t from the task set T, and if the task set T is not null, going to the step (3), or otherwise, going to the step (5); and (5) outputting a workflow scheduling scheme. According to the scheduling optimization method provided by the invention, an energy consumption factor is considered, so that the energy consumption for task processing by the host is effectively reduced while workflow execution time efficiency is kept.

The invention discloses a method and mobile terminal for adjusting WIFI scanning frequency based on a motion state. The method comprises the steps that A, a motion sensor acquires the motion state information of the mobile terminal; B, the motion state of the mobile terminal is calculated according to the motion state information, whether the motion state is changed or not is judged, and the scanning frequency of a WIFI module is adaptively adjusted according to the change of the motion state when the motion state is changed. According to the method and mobile terminal for adjusting the WIFI scanning frequency based on the motion state, the scanning frequency of the WIFI module can be adaptively adjusted according to the change of the motion state, therefore, a WIFI can work more efficiently, the performance per watt can be improved, the battery time of the mobile terminal under a WIFI work mode can be prolonged, and the user experience is improved.