3 results about "Matrix manipulation" patented technology

For purposes of compression and decompression operations, a tensor is split into tiles having a tile size, and values at a given position in the respective tiles are processed as a stream. In some example implementations, for compression operations, a matrix processing tool can separately apply variable-rate compression to different streams of values of the tensor, with the different streams being associated with different positions of the tile size. For decompression operations, the matrix processing tool can quickly reconstruct different streams of values of the tensor. The decompression operations can be performed in parallel, with different decoders decompressing different streams of values of the tensor. In this way, soon after decompression starts, tensor blocks of values of the tensor can be loaded to local memory of tensor cores for matrix multiplication and accumulation operations, which can help reduce latency and fully utilize the tensor cores.

For purposes of compression and decompression operations, a tensor is split into tiles having a tile size, and values at a given position in the respective tiles are processed as a stream. In some example implementations, for compression operations, a matrix processing tool can separately apply variable-rate compression to different streams of values of the tensor, with the different streams being associated with different positions of the tile size. For decompression operations, the matrix processing tool can quickly reconstruct different streams of values of the tensor. The decompression operations can be performed in parallel, with different decoders decompressing different streams of values of the tensor. In this way, soon after decompression starts, tensor blocks of values of the tensor can be loaded to local memory of tensor cores for matrix multiplication and accumulation operations, which can help reduce latency and fully utilize the tensor cores.

The application discloses a matrix compression method, a matrix processing method and related devices, and belongs to the field of data processing. The method comprises the following steps: dividing a first matrix stored in a memory to obtain a plurality of first sub-matrices; compressing non-zero element groups in each first sub-matrix in the plurality of first sub-matrices according to a first direction to obtain a plurality of second sub-matrices corresponding to the first matrix; dividing each second sub-matrix in the plurality of second sub-matrices to obtain a plurality of third sub-matrices; and generating a compression result of the first matrix based on the plurality of third sub-matrices. According to the application, only non-zero element groups exist in the first sub-matrices, so that a part of elements with a value of zero in the first matrix is removed, and therefore, the compression result of the first matrix can effectively reduce the number of zero elements that need to be stored, thereby saving data storage space.