| BasicTensorBlock |
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| DataTensorBlock |
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| DenseBlock |
This DenseBlock is an abstraction for different dense, row-major
matrix formats.
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| DenseBlockBool |
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| DenseBlockDRB |
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| DenseBlockFactory |
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| DenseBlockFP32 |
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| DenseBlockFP64 |
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| DenseBlockFP64DEDUP |
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| DenseBlockInt32 |
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| DenseBlockInt64 |
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| DenseBlockLBool |
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| DenseBlockLDRB |
Dense Large Row Blocks have multiple 1D arrays (blocks), which contain complete rows.
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| DenseBlockLFP32 |
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| DenseBlockLFP64 |
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| DenseBlockLFP64DEDUP |
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| DenseBlockLInt32 |
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| DenseBlockLInt64 |
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| DenseBlockLString |
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| DenseBlockString |
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| IndexedTensorBlock |
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| LibTensorAgg |
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| LibTensorBincell |
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| LibTensorReorg |
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| SparseBlock |
This SparseBlock is an abstraction for different sparse matrix formats.
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| SparseBlockCOO |
SparseBlock 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.
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| SparseBlockCSR |
SparseBlock 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.
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| SparseBlockDCSR |
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| SparseBlockFactory |
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| SparseBlockMCSC |
SparseBlock 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.
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| SparseBlockMCSR |
SparseBlock 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.
|
| SparseRow |
Base class for sparse row implementations such as sparse
row vectors and sparse scalars (single value per row).
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| SparseRowScalar |
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| SparseRowVector |
A sparse row vector that is able to grow dynamically as values are appended to it.
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| TensorBlock |
A TensorBlock is the most top level representation of a tensor.
|
| TensorIndexes |
This represent the indexes to the blocks of the tensor.
|