MatMul

#include <popsparse/MatMul.hpp>

Sparse matrix multiply operations.

namespace popsparse

Support for sparse matrices.

namespace dynamic

Support for dynamic sparse matrices.

Functions

SparseTensor createSparseDenseMatMulLHS(poplar::Graph &graph, const poplar::Type &inputType, const MatMulParams &params, const poplar::DebugContext &debugContext = {}, const poplar::OptionFlags &options = {}, PlanningCache *cache = nullptr)

Create a sparse tensor that is used as the left-hand operand in a sparse * dense matrix multiplication.

The following options are available:

  • availableMemoryProportion Decimal between 0 and 1 [=0.6]

    The maximum proportion of available memory on each tile that this layer should consume temporarily during the course of the operation.

  • metaInfoBucketOversizeProportion Decimal between 0 and 1 [=0.3]

    This specifies additional elements to allocate in each bucket of meta-information as a proportion of the required size for a perfectly uniformly distributed sparsity pattern.

  • partialsType poplar::Type [=poplar::FLOAT]

    The type to use for partial results.

  • sharedBuckets (true, false) [=true]

    If set, forces the same buckets to be used whether or not the sparse (left-hand) operand is transposed or not. Saves memory at the expense of runtime.

Parameters

  • graph – The Poplar graph.

  • inputType – The type for inputs to the operation.

  • params – Parameters for the matrix multiplication.

  • debugContext – Optional debug information.

  • options – Implementation options for the matrix multiplication.

  • cache – Optional pointer to planning cache to use.

Returns

A sparse tensor with sparse representation of left-hand operand for the matrix multiplication.

poplar::Tensor createSparseDenseMatMulRHS(poplar::Graph &graph, const poplar::Type &inputType, const MatMulParams &params, const poplar::DebugContext &debugContext = {}, const poplar::OptionFlags &options = {}, PlanningCache *cache = nullptr)

Create a dense tensor that is used as the right-hand operand in a sparse * dense matrix multiplication.

Parameters

  • graph – The Poplar graph.

  • inputType – The type for inputs to the operation.

  • params – Parameters for the matrix multiplication.

  • debugContext – Optional debug information.

  • options – Implementation options for the matrix multiplication.

  • cache – Optional pointer to planning cache to use.

Returns

A dense tensor for use as right-hand operand for the matrix multiplication.

poplar::Tensor sparseDenseMatMul(poplar::Graph &graph, const SparseTensor &lhs, const poplar::Tensor &rhs, poplar::program::Sequence &prog, bool transposeLHS = false, bool transposeRHS = false, const poplar::DebugContext &debugContext = {}, const poplar::OptionFlags &options = {}, PlanningCache *cache = nullptr)

Perform a sparse * dense matrix multiplication, yielding a dense result.

The sparse left-hand operand tensor is made up of meta information for the sparsity and the non-zero values of the matrix. This sparse tensor must have been created with createSparseDenseMatMulLHS.

If the sparse left-hand operand was created for the sparse equivalent of a dense matrix multiplication:

[groups][m][k] * [groups][k][n] = [groups][m][n]

Then the same sparse left-hand operand can be used to calculate the above as well as:

[groups][k][m] * [groups][m][n] = [groups][k][n]

through the use of the transposeLHS parameter. transposeRHS is also provided for convenience.

Parameters

  • graph – The Poplar graph.

  • lhs – The sparse left-hand operand to the matrix multiplication.

  • rhs – The dense right-hand operand to the matrix multiplication.

  • prog – A reference to a program sequence which will be appended with the code to perform the matrix multiplication.

  • transposeLHS – Whether or not to transpose the left-hand operand before multiplying.

  • transposeRHS – Whether or not to transpose the right-hand operand before multiplying.

  • debugContext – Optional debug information.

  • options – Implementation options for the matrix multiplication.

  • cache – Optional pointer to planning cache to use.

Returns

The tensor holding the dense result of the matrix multiplication. The tensor will be created, added to the graph, and mapped to tiles.