MSBFS #90
MSBFS #90
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Benchmarks fix
| open GraphBLAS.FSharp.Backend.Matrix.LIL | ||
| open GraphBLAS.FSharp.Backend.Matrix.COO | ||
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| module internal MSBFS = |
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Can BFS also be Parents and Leveles? Can unified interface be created?
| /// </remarks> | ||
| /// <param name="clContext">OpenCL context.</param> | ||
| /// <param name="workGroupSize">Should be a power of 2 and greater than 1.</param> | ||
| let mergeDisjoint (clContext: ClContext) workGroupSize = |
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Why it is not an element-wise operation over two matrices?
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Element-wise operations are slow due to the use of a prefix sum. And they allocate much more
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We can implement it using map2, but, I guess, it will be less efficient, because inside map2 dense matrix is allocated first. MergeDisjoint allocates matrix of the required size without the need to truncate it later.
| @@ -393,8 +393,7 @@ module Matrix = | |||
| { Context = clContext | |||
| RowCount = matrix.RowCount | |||
| ColumnCount = matrix.ColumnCount | |||
| Rows = rows | |||
| NNZ = matrix.NNZ } | |||
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I made a property inside LIL for recounting NNZ instead of keeping fixed NNZ in this field.
| /// </remarks> | ||
| /// <param name="clContext">OpenCL context.</param> | ||
| /// <param name="workGroupSize">Should be a power of 2 and greater than 1.</param> | ||
| let mergeDisjoint (clContext: ClContext) workGroupSize = |
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Element-wise operations are slow due to the use of a prefix sum. And they allocate much more
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