Abstract: Aspects for vector operations in neural network are described herein. The aspects may include a vector caching unit configured to store a first vector and a second vector, wherein the first vector includes one or more first elements and the second vector includes one or more second elements. The aspects may further include one or more adders and a combiner. The one or more adders may be configured to respectively add each of the first elements to a corresponding one of the second elements to generate one or more addition results. The combiner may be configured to combine a combiner configured to combine the one or more addition results into an output vector.

Abstract: Aspects for backpropagation of a convolutional neural network are described herein. The aspects may include a direct memory access unit configured to receive input data from a storage device and a master computation module configured to select one or more portions of the input data based on a predetermined convolution window. Further, the aspects may include one or more slave computation modules respectively configured to convolute one of the one or more portions of the input data with one of one or more previously calculated first data gradients to generate a kernel gradient, wherein the master computation module is further configured to update a prestored convolution kernel based on the kernel gradient.

Abstract: Aspects for generating a dot product for two vectors in neural network are described herein. The aspects may include a controller unit configured to receive a vector load instruction that includes a first address of a first vector and a length of the first vector. The aspects may further include a direct memory access unit configured to retrieve the first vector from a storage device based on the first address of the first vector. Further still, the aspects may include a caching unit configured to store the first vector.

Abstract: A mechanism is provided for identifying suggestions as to which log files associated with data in a data warehouse to search for particular data. Features from the contents of a plurality of log files from a set of log files are selected. The plurality of log files are grouped based on the selected features. Using extracted log event sequences, a correlation between the log event sequences and a plurality of data transaction tables from a set of data transaction tables in the data warehouse is calculated. Suggestions as to which log files in the set of log files should be searched is then identified for particular data based on a business relevance value and a utilized data ratio.