9 results about "K matrix" patented technology

This invention provides an improved method, system, and computer program for performing matrix multiplication computer instructions. [Solution] The method is a processor having a control register and a vector register whose length is indicated in the control register, in which a matrix operation A × B = C is performed, where A is an M × K matrix with elements of a first bit width, B is a K × N matrix with elements of a second bit width, and C is an M × N matrix with elements of a third bit width. The instruction has three parameters that encode the type of multiplication to be performed and indicate which vector register to sequentially store the elements of each matrix in. The method also obtains the length from the control register, decodes the instruction to obtain the multiplication type, determines the first and second bit widths according to the multiplication type, determines the values ​​of M, N, and K according to the length and the first and second bit widths, and performs matrix multiplication considering the three parameters, the first and second bit widths, and the values ​​of M, N, and K.

The application discloses a kind of converter electromagnetic transient simulation parallel optimization method, equipment and storage medium, belong to power system electromagnetic transient simulation technical field, by merging significantly reduces unnecessary intermediate variable, shortens simulation calculation process;And since C, D matrix and Un, k matrix multiplication operation with Itotal of A, B matrix and multiplication are carried out simultaneously, and the calculation process between row and row is independent, increase the parallel degree of electromagnetic transient simulation calculation;Since parameter matrix does not change with the change of switch state, it is calculated and stored in advance in simulation initialization stage, only needs to consume register reading operation time in the calculation of single simulation step;Coefficient matrix A, B, C, D are all square matrix of scale Nb*Nb, the formula for calculating Ub and Ib is the same in structure, to lay the algorithm foundation for saving logic resources while improving the calculation efficiency of simulation program using pipeline and other hardware development techniques.

Embodiments of the present disclosure provide a method, apparatus, computing device and storage medium for calculating matrix-vector multiplication, where the matrix is an M*K matrix and the vector is a K*1 vector, M and K are positive integers. The method comprises: converting the M*K matrix into an M*(K / N)*N first tensor, where N is a positive integer, N>1, and K is a multiple of N; converting the K*1 vector into an N*(K / N) second tensor; using a tensor computing core to batch-process the general matrix multiplication of the M*(K / N)*N first tensor and the N*(K / N) second tensor to obtain M result matrices; and adding the elements on the diagonal of each of the M result matrices to obtain each element on the M*1 result vector of the M*K matrix multiplied by the K*1 vector. The above scheme uses a tensor computing core to implement high-throughput, low-latency high-speed matrix-vector multiplication (MMV) operation.

The application provides an image segmentation method based on block-level self-attention and block correlation mechanism, comprising the following steps: 1, building a ResNet101 backbone network; 2, dividing the output features of the backbone network into blocks, and using 1*1 convolution to generate a query matrix (Q), a key matrix (K) and a value matrix (V) for each feature block, and using a block correlation mechanism (BCM) to calculate the correlation of the Q matrix of each feature block and the global features; 3, building a self-attention network with relative position offset, embedding the BCM into the self-attention calculation process of each feature block, using the output M matrix of the BCM and the K matrix and the V matrix for self-attention calculation, and introducing a relative position offset for the M, K and V matrices of each feature block to jointly form a block-level self-attention (BLSA) module; 4, splicing the output of each feature block in the spatial dimension and sending it into a segmentation head for segmentation, and performing experimental comparison.

A method for estimating delays and Doppler shifts of GNSS signals comprises obtaining respective output sequences from N correlators for a snapshot of a received GNSS signal, wherein each sequence has K values, the N correlators correspond to N different delays of a pseudorandom noise, PRN, code sequence, the K values are correlation values at K sampling time points in each sequence, N and K are positive integers. The method further comprises, for each output sequence, obtaining a frequency spectrum by computing a K-point discrete Fourier transform, DFT, of the output sequence; obtaining a N×K matrix using the N frequency spectra; determining at least one peak value in the N×K matrix; and estimating a delay and a Doppler shift of the received GNSS signal using indices of the at least one peak value in the N×K matrix.

Video coding using reduced-rank matrices for matrix intra prediction (MIP). In a video coding method, information is obtained indicating a matrix rank, k, and a matrix intra prediction mode for a current block. The current block has a block shape, and neighboring reference samples. Based on the intra prediction mode and the current block shape, a first and second matrix are selected from a stored set of intra prediction matrices. Each of the stored matrices is associated with a respective block shape and intra prediction mode. A first rank-k matrix is obtained from the first matrix, and a second rank-k matrix is obtained from the second matrix. The current block is then predicted using a product of the first rank-k matrix, the second rank- k matrix, and the reference samples.

A partial fixed caching method and system based on large model inference, a device, and a medium, relating to the technical fields of artificial intelligence and natural language processing. The technical problem to be solved is how to find a balance between computing resources and storage resources that is more suitable for localized inference of large models, thereby improving inference efficiency. The technical solution used is: a pre-filling stage: inputting a sequence or text, preprocessing same to complete format conversion from the original input sequence or text into a large model input matrix, and caching a K matrix and a V matrix of an original input token in each attention layer on the basis of a KVcache method; and a decoding stage: unlike the conventional KVcache method, before each decoding, pre-determining whether to cache a K matrix and a V matrix of a current input token, and on the basis of the result, determining whether to cache the K matrix and the V matrix of the current input token during the current decoding.

The invention relates to a method for estimating delay and Doppler shift of global navigation satellite system signals. A method of estimating delays and Doppler shifts of a GNSS signal includes obtaining respective output sequences from N correlators for snapshots of a received GNSS signal, where each sequence has K values, the N correlators corresponding to N different delays of a pseudorandom noise (PRN) code sequence, the K values being correlation values at K sampling time points in each sequence, n and K are positive integers. The method further comprises: for each output sequence, obtaining a spectrum by calculating a K-point discrete Fourier transform (DFT) of the output sequence; obtaining an N * K matrix by using the N frequency spectrums; determining at least one peak value in the N * K matrix; and estimating the delay and Doppler shift of the received GNSS signal using an index of the at least one peak in the N * K matrix.

Embodiments of the present application relate to a slot value extraction method and device based on slot meaning of a large model, related information of an mth slot at a current time is obtained; the related information is spliced from a to-be-filled sentence, an original input text and a fill-in-the-blank instruction; the to-be-filled sentence is composed of a slot name, a meaning explanation and a corresponding slot value of a first slot, a slot name, a meaning explanation and a corresponding slot value of a second slot, and a slot name, a meaning explanation and a corresponding slot value of a third slot; based on the related information of the mth slot at the current time, a parameter matrix, and a hidden layer representation vector of a decoder at a previous time, an attention matrix of the mth slot is determined; the parameter matrix includes q matrix, k matrix and v matrix in the attention mechanism; based on the attention matrix of the mth slot, a word table probability distribution corresponding to the mth slot is determined; based on the word table probability distribution, a slot value corresponding to the mth slot is determined, and a corresponding blank symbol is replaced to fill in a completed sentence.