Abstract:
Disclosed herein is a method for outer-product-based matrix multiplication for a floating-point data type includes receiving first floating-point data and second floating-point data and performing matrix multiplication on the first floating-point data and the second floating-point data, and the result value of the matrix multiplication is calculated based on the suboperation result values of floating-point units.
Abstract:
The present disclosure relates to a frame grabber, an image processing system, and an image processing method. A frame grabber according to an embodiment of the inventive concept includes a plurality of decoders, a plurality of image controllers, a plurality of memories, a synchronization controller, and a synchronization memory. The plurality of decoders generate a plurality of image data by decoding a plurality of image signals. The plurality of image controllers generate a plurality of pixel data and a plurality of frame information data on the basis of the plurality of image data. The plurality of memories store the plurality of pixel data. The synchronization controller receives the plurality of frame information data, and generates synchronization data on the basis of the plurality of frame information data. The synchronization memory stores the frame information data and the synchronization data.
Abstract:
Disclosed is a simplified sigmoid function circuit which includes a first circuit that performs a computation on input data based on a simplified sigmoid function when a sign of a real region of the input data is positive, a second circuit that performs the computation on the input data based on the simplified sigmoid function when the sign of the real region of the input data is negative, and a first multiplexer that selects and output one of an output of the first circuit and an output of the second circuit, based on the sign of the input data. The simplified sigmoid function is obtained by transforming a sigmoid function of a real region into a sigmoid function of a logarithmic region and performing a variational transformation for the sigmoid function of the logarithmic region.
Abstract:
Disclosed is a processor according to the present disclosure, which includes processing elements, a kernel data memory that provides a kernel data set to the processing elements, a data memory that provides an input data set to the processing elements, and a controller that provides commands to the processing elements, and a first processing element among the processing elements delays a first command received from the controller and first input data received from the data memory for a delay time, and then transfers the delayed first command and the delayed first input data to a second processing element, and the controller adjusts the delay time.
Abstract:
A convolutional operation device for performing convolutional neural network processing includes an input sharing network including first and second input feature map registers configured to shift each input feature map, which is inputted in row units, in a row or column direction and output the shifted input feature map and arranged in rows and columns, a first MAC array connected to the first input feature map registers, an input feature map switching network configured to select one of the first and second input feature map registers, a second MAC array connected to one selected by the input feature map switching network among the first and second input feature map registers, and an output shift network configured to shift the output feature map from the first MAC array and the second MAC array to transmit the shifted output feature map to an output memory.
Abstract:
A neural network accelerator in which processing elements are configured in a systolic array structure includes a memory to store a plurality of feature data including first and second feature data and a plurality of kernel data including first and second kernel data, a first processing element to perform an operation based on the first feature data and the first kernel data and output the first feature data, a selection circuit to select one of the first feature data and the second feature data, based on a control signal, and output the selected feature data, a second processing element to perform an operation based on the selected feature data and one of the first and the second kernel data, and a controller to generate the control signal, based on a neural network characteristic associated with the plurality of feature data and kernel data.
Abstract:
Provided is a data generation device for generating input data to be inputted to a parallel processing device. The data generation device includes: a controller configured to output padding data; and a data processing device configured to receive original data and to generate the input data in which at least a portion of the original data is padded with the padding data. The data processing device includes: a first multiplexer configured to receive the padding data and the original data; a register configured to store data outputted from the first multiplexer; and a second multiplexer configured to receive data outputted from the first multiplexer and data stored in the register.
Abstract:
Provided is an operating method of a road guide system including collecting traffic information around a portable device through the portable device; delivering, to a server, the traffic information collected from the portable device and travel path information; updating the delivered travel path information based on the delivered traffic information; and feeding back the updated travel path information from the server to the portable device.
Abstract:
Disclosed is an operating method of a vehicle control apparatus controlling autonomous driving based on a vehicle external object including performing primary object detection based on a first vehicle external image received from a camera to obtain first object information, setting a first reflective area for reflection light based on the first object information, generating a second vehicle external image, in which a reflective image inside the first reflective area is removed from the first vehicle external image, using pixel values inside the first reflective area, performing secondary object detection based on the second vehicle external image to obtain second object information, determining reliability of the second object information based on information about the reflective image and the second object information, and controlling the autonomous driving of the vehicle based on the second object information when the reliability of the second object information is higher than a setting value.
Abstract:
In the present invention, by providing an apparatus for processing a convolutional neural network (CNN), including a weight memory configured to store a first weight group of a first layer, a feature map memory configured to store an input feature map where the first weight group is to be applied, an address generator configured to determine a second position spaced from a first position of a first input pixel of the input feature map based on a size of the first weight group, and determine a plurality of adjacent pixels adjacent to the second position; and a processor configured to apply the first weight group to the plurality of adjacent pixels to obtain a first output pixel corresponding to the first position, a memory space may be efficiently used by saving the memory space.