2019-12-12 15:37 −311. Sparse Matrix Multiplication 稀疏矩阵的计算。稀疏矩阵的特点是有大量的0,如果采用暴力算法则比然会有很多无意义的计算。 C[ i ][ j ] += A[ i ] [ k ] * B[ k ] [ j ] 我们首先遍历A数组,要确保A[i][k]不为0... ...
Sparse matrices can be used in arithmetic operations: they support addition, subtraction, multiplication, division, and matrix power Advantages of the CSR format efficient arithmetic operations CSR + CSR, CSR * CSR, etc. efficient row slicing fast matrix vector products Disadvantages of the CSR forma...
csr_matrix是Compressed Sparse Row matrix的缩写组合,下面介绍其两种初始化方法 csr_matrix((data, (row_ind, col_ind)), [shape=(M, N)]) wheredata,row_indandcol_indsatisfy the relationshipa[row_ind[k],col_ind[k]]=data[k]. csr_matrix((data, indices, indptr), [shape=(M, N)]) is t...
The invention discloses a sparse matrix storage method CSRL (Compressed Sparse Row with Local Information) and an SpMV (Sparse Matrix Vector Multiplication) realization method based on the same. The storage method comprises the following steps of scanning a sparse matrix A in rows and storing ...
Sparse matrix-vector multiplication (SpMV) is an important operation in scientific computations. Compressed sparse row (CSR) is the most frequently used format to store sparse matrices. However, CSR-based SpMVs on graphic processing units (GPUs), for example, CSR-scalar and CSR-vector, usually ...
Sparse matrices can be used in arithmetic operations: they support addition, subtraction, multiplication, division, and matrix power. Advantages of the CSR format efficient arithmetic operations CSR + CSR, CSR * CSR, etc. efficient row slicing ...
DIA和ELL格式在进行稀疏矩阵-矢量乘积(sparse matrix-vector products)时效率最高,所以它们是应用迭代法(如共轭梯度法)解稀疏线性系统最快的格式; COO和CSR格式比起DIA和ELL来,更加灵活,易于操作; ELL的优点是快速,而COO优点是灵活,二者结合后的HYB格式是一种不错的稀疏矩阵表示格式; ...
scipy.sparse.coo_matrix scipy.sparse.coo_matrix scipy.sparse.coo_matrix(arg1, shape=None, dtype=None, copy=False) 坐标格式的稀疏矩阵。 也称为“ ijv”或“三胞胎”格式。 可以通过这几种方式实例化: coo_matrix(D) 带有密集矩阵D coo_matrix(S) 与另一个稀疏......
基于上述的稀疏矩阵存储方法,下面提供一种SpMV实现方法SpMV是Sparse MatrixVector Multiplication的简写,即稀疏矩阵向量乘y=A*x。其中y和x为稠密向量,A为稀疏矩阵,采用CSRL方法存储。 (1)对于第i(i=1,m)行,先计算稀疏矩阵中每个连续非零元段与x相乘的结果。用户计算平台一次存取和计算的双精度个数记为s,对每个...
DIA和ELL格式在进行稀疏矩阵-矢量乘积(sparse matrix-vector products)时效率最高,所以它们是应用迭代法(如共轭梯度法)解稀疏线性系统最快的格式; COO和CSR格式比起DIA和ELL来,更加灵活,易于操作; ELL的优点是快速,而COO优点是灵活,二者结合后的HYB格式是一种不错的稀疏矩阵表示格式; ...