A convolutional operation device, comprising: a Dynamic Voltage Frequency Scaling device, an instruction storage unit, a control unit, a data access unit, an interconnection module, a primary computation module and N secondary computation modules, where N is an integer larger than 1, wherein the instruction storage unit is configured to store an instruction read in by the data access unit; the control unit is configured to read the instruction from the instruction storage unit and decode the instruction into a control signal for controlling an operation of other modules, where the other modules comprise the data access unit, the primary computation module, and the N secondary computation modules; the data access unit is configured to perform data or instruction read/write operation between an external address space and the convolutional operation device; the N secondary computation modules are configured to implement convolutional operation of input data and convolution kernels in a convolutional neural network algorithm; the interconnection module is configured for data transfer between the primary computation module and the secondary computation modules; the primary computation module is configured to splice intermediate vectors of all the input data into an intermediate result and perform subsequent operation on the intermediate result, wherein the primary computation module is configured to add the intermediate result and offset data, and to perform an activation operation; the Dynamic Voltage Frequency Scaling device is configured to acquire working state information of the convolutional operation device and send voltage frequency scaling information to the convolutional operation device according to the working state information of the convolutional operation device, where the voltage frequency scaling information is configured to instruct the convolutional operation device to scale its working voltage or working frequency. a Dynamic Voltage Frequency Scaling device, an instruction storage unit, a control unit, a data access unit, an interconnection module, a primary computation module and N secondary computation modules, where N is an integer larger than 1, wherein the instruction storage unit is configured to store an instruction read in by the data access unit; the control unit is configured to read the instruction from the instruction storage unit and decode the instruction into a control signal for controlling an operation of other modules, where the other modules comprise the data access unit, the primary computation module, and the N secondary computation modules; the data access unit is configured to perform data or instruction read/write operation between an external address space and the convolutional operation device; the N secondary computation modules are configured to implement convolutional operation of input data and convolution kernels in a convolutional neural network algorithm; the interconnection module is configured for data transfer between the primary computation module and the secondary computation modules; the primary computation module is configured to splice intermediate vectors of all the input data into an intermediate result and perform subsequent operation on the intermediate result, wherein the primary computation module is configured to add the intermediate result and offset data, and to perform an activation operation; the Dynamic Voltage Frequency Scaling device is configured to acquire working state information of the convolutional operation device and send voltage frequency scaling information to the convolutional operation device according to the working state information of the convolutional operation device, where the voltage frequency scaling information is configured to instruct the convolutional operation device to scale its working voltage or working frequency.