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Lowering graphblas.reduce_to_scalar to Generic Form

This example will go over how to use the --graphblas-structuralize pass from graphblas-opt to lower graphblas.reduce_to_scalar ops to graphblas.reduce_to_scalar_generic ops.

graphblas.reduce_to_scalar ops specify behavior via an aggregator attributes. The --graphblas-structuralize pass will lower those ops into equivalent graphblas.reduce_to_scalar_generic ops with blocks specifying the behavior indicated by those semirings.

Let’s first import some necessary libraries.

import tempfile
from mlir_graphblas.cli import GRAPHBLAS_OPT_EXE

Since sparse tensor encodings can be very verbose in MLIR, let’s import some helpers to make the MLIR code more readable.

from mlir_graphblas.tools import tersify_mlir

Example

Here’s some example graphblas.apply code using the “plus” aggregator.

mlir_text = """
#CSR64 = #sparse_tensor.encoding<{
  dimLevelType = [ "dense", "compressed" ],
  dimOrdering = affine_map<(i,j) -> (i,j)>,
  pointerBitWidth = 64,
  indexBitWidth = 64
}>

module {
    func @matrix_reduce_to_scalar_plus(%sparse_tensor: tensor<2x3xi64, #CSR64>) -> i64 {
        %answer = graphblas.reduce_to_scalar %sparse_tensor { aggregator = "plus" } : tensor<2x3xi64, #CSR64> to i64
        return %answer : i64
    }
}
"""

Let’s see what code we get when we run it through graphblas-opt with the --graphblas-structuralize pass.

with tempfile.NamedTemporaryFile() as temp:
    temp_file_name = temp.name
    with open(temp_file_name, 'w') as f:
        f.write(mlir_text)
    temp.flush()

    output_mlir = ! cat $temp_file_name | $GRAPHBLAS_OPT_EXE --graphblas-structuralize
    output_mlir = "\n".join(output_mlir)
    output_mlir = tersify_mlir(output_mlir)

print(output_mlir)

#CSR64 = #sparse_tensor.encoding<{
    dimLevelType = [ "dense", "compressed" ],
    dimOrdering = affine_map<(d0, d1) -> (d0, d1)>,
    pointerBitWidth = 64,
    indexBitWidth = 64
}>

builtin.module  {
  builtin.func @matrix_reduce_to_scalar_plus(%arg0: tensor<2x3xi64, #CSR64>) -> i64 {
    %c0_i64 = constant 0 : i64
    %0 = graphblas.reduce_to_scalar_generic %arg0 : tensor<2x3xi64, #CSR64> to i64  {
      graphblas.yield agg_identity %c0_i64 : i64
    },  {
    ^bb0(%arg1: i64, %arg2: i64):  // no predecessors
      %1 = addi %arg1, %arg2 : i64
      graphblas.yield agg %1 : i64
    }
    return %0 : i64
  }
}

As shown above, --graphblas-structuralize expanded the “plus” aggregator into blocks performing that exact behavior.

We’ll leave exploring how the other aggregators expand as an exercise for the reader.

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Lowering graphblas.apply to Generic Form

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