CSR (Compressed Sparse Row)
E839061
CSR (Compressed Sparse Row) is a memory-efficient sparse matrix storage format that stores only nonzero elements and their indices in row-major order to enable fast arithmetic and matrix–vector operations.
Statements (46)
| Predicate | Object |
|---|---|
| instanceOf |
data structure
ⓘ
sparse matrix storage format ⓘ |
| advantageOverDense |
avoids computation on zero entries
ⓘ
reduces memory for highly sparse matrices ⓘ |
| alsoKnownAs |
CRS
ⓘ
CSR format ⓘ Compressed Sparse Row NERFINISHED ⓘ compressed row storage ⓘ |
| complexity |
O(nnz) storage complexity
ⓘ
O(nnz) time for matrix–vector multiplication ⓘ |
| component |
column indices array
ⓘ
row pointer array ⓘ values array ⓘ |
| contrastedWith |
COO (Coordinate format)
ⓘ
CSC (Compressed Sparse Column) ⓘ DIA (Diagonal format) NERFINISHED ⓘ |
| domain |
numerical linear algebra
ⓘ
sparse matrix computation ⓘ |
| limitation |
inefficient for column slicing
ⓘ
insertion of new nonzeros is expensive ⓘ |
| property |
enables fast arithmetic operations
ⓘ
enables fast matrix–vector operations ⓘ good cache locality for row-wise access ⓘ memory-efficient for sparse matrices ⓘ stores only nonzero entries ⓘ supports efficient row slicing ⓘ |
| rowPointerArrayMeaning | prefix sum of nonzeros per row ⓘ |
| storageOrder | row-major ⓘ |
| stores |
column indices of nonzero elements
ⓘ
nonzero matrix elements ⓘ row pointer array ⓘ |
| supportedBy |
Eigen
NERFINISHED
ⓘ
MKL NERFINISHED ⓘ PETSc NERFINISHED ⓘ SciPy NERFINISHED ⓘ cuSPARSE NERFINISHED ⓘ |
| typicalIndexBase | 0-based indices GENERATED ⓘ |
| typicalUseCase |
finite element methods
ⓘ
sparse linear algebra libraries ⓘ |
| usedFor |
graph algorithms
ⓘ
high‑performance computing ⓘ iterative linear solvers ⓘ scientific computing ⓘ sparse matrix–matrix multiplication ⓘ sparse matrix–vector multiplication ⓘ storing sparse matrices ⓘ |
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.