VarStructure

#include <poputil/VarStructure.hpp>

Manage partitioning and grouping in tensors.

namespace poputil

General utility functions for building graphs.

Typedefs

using GroupingInfo = std::pair<unsigned, unsigned>

Grouped dimension info.

The first in the pair is the grouped dimension The second in the pair is the grouping in that dimension

Functions

unsigned detectInnermostGrouping(const poplar::Graph &graph, const poplar::Tensor &t)

Detect if the tensor t has a grouping in its innermost dimension.

Parameters

  • graph – The graph to add the function to.

  • t – The tensor to check for grouping.

Throws

poputil::poplibs_error – If the rank of t is zero.

Returns

The size of the group. 1 if there is no grouping.

std::vector<GroupingInfo> detectDimGroupings(const poplar::Graph &graph, const poplar::Tensor &t)

Find all grouped dimensions from the innermost grouped dimension moving outwards, returning groupings for each.

The same dimension may appear more than once. This uses detectInnermostGrouping() iteratively.

Parameters

  • graph – The graph to add the function to.

  • t – The tensor to check for grouping.

Throws

poputil::poplibs_error – If the rank of t is zero.

Returns

A list of the grouped dimensions starting with the innermost.

poplar::Tensor createPartitionableTensor(poplar::Graph &graph, const poplar::Type &type, const std::vector<std::size_t> &shape, const std::vector<std::size_t> &nPartitions, const poplar::DebugContext &debugContext = {})

Create a tensor with the given shape, so that when it is partitioned into slices according to the given number of partitions in each dimension, each slice is a single contiguous region.

This partitions the tensor so that the maximum number of elements in each partition of a dimension is minimised as well as the number of partitions. That is, if a dimension has n elements, and the number of partitions in that dimension is d then: 

a * ceil(n/d) + 1 * (n%d) = n

There will be a partitions with ceil(n/d) elements followed by b partitions with floor(n/d) elements and possibly some number of partitions with 0 elements.

The returned tensor has no tile mapping set.

Parameters

  • graph – The graph to add the variable to.

  • type – The type of the elements in the returned tensor.

  • shape – The shape of the returned tensor.

  • nPartitions – The number of partitions the shape will be partitioned into in each dimension.

  • debugContext – Optional debug information.

Throws

poputil::poplibs_error – If the size of shape and nPartitions are not equal.

Returns

A tensor with the given shape where each partition is contiguous.

void iterateTensorPartitions(const poplar::Tensor &t, const std::vector<std::size_t> &nPartitions, const std::function<void(const std::vector<std::size_t> &i, const poplar::Tensor &s)> &f)

Iterate a function over the partitions of a tensor.

Partitioning follows the same definition as described for createPartitionableTensor().

Parameters

  • t – The tensor to iterate over.

  • nPartitions – The number of partitions the tensor is partitioned into in each dimension.

  • i –

  • f – A function taking the indices of the partition in the range [0, splits[d]) in each dimension of the tensor as well as the slice of the tensor corresponding to that partition.

Throws

poputil::poplibs_error – If the rank of t and the size of nPartitions are not equal.