Uses of Interface
org.apache.sysds.runtime.data.Block
Packages that use Block
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Uses of Block in org.apache.sysds.runtime.data
Classes in org.apache.sysds.runtime.data that implement BlockModifier and TypeClassDescriptionclassThis DenseBlock is an abstraction for different dense, row-major matrix formats.classclassclassclassclassclassclassclassclassDense Large Row Blocks have multiple 1D arrays (blocks), which contain complete rows.classclassclassclassclassclassclassclassThis SparseBlock is an abstraction for different sparse matrix formats.classSparseBlock implementation that realizes a traditional 'coordinate matrix' representation, where the entire sparse block is stored as triples in three arrays: row indexes, column indexes, and values, where row indexes and colunm indexes are sorted in order to allow binary search.classSparseBlock implementation that realizes a traditional 'compressed sparse column' representation, where the entire sparse block is stored as three arrays: ptr of length clen+1 to store offsets per column, and indexes/values of length nnz to store row indexes and values of non-zero entries.classSparseBlock implementation that realizes a traditional 'compressed sparse row' representation, where the entire sparse block is stored as three arrays: ptr of length rlen+1 to store offsets per row, and indexes/values of length nnz to store column indexes and values of non-zero entries.classclassSparseBlock implementation that realizes a 'modified compressed sparse column' representation, where each compressed column is stored as a separate SparseRow object which provides flexibility for unsorted column appends without the need for global reshifting of values/indexes but it incurs additional memory overhead per column for object/array headers per column which also slows down memory-bound operations due to higher memory bandwidth requirements.classSparseBlock implementation that realizes a 'modified compressed sparse row' representation, where each compressed row is stored as a separate SparseRow object which provides flexibility for unsorted row appends without the need for global reshifting of values/indexes but it incurs additional memory overhead per row for object/array headers per row which also slows down memory-bound operations due to higher memory bandwidth requirements.