LabVIEW Multicore Analysis and Sparse Matrix Toolkit API Reference

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  • Updated2023-02-21
  • 3 minute(s) read

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Owning Palette: Numeric VIs

Requires: Multicore Analysis and Sparse Matrix Toolkit

Computes the element-wise sum of two sparse matrices.

Wire data to the A and B inputs to determine the polymorphic instance to use or manually select the instance.

Details  

Add Sparse to Sparse (DBL)

A specifies the first sparse matrix. The number of rows and columns in A must be equal to the number of row and columns in B, respectively.
B specifies the second sparse matrix. The number of rows and columns in B must be equal to the number of row and columns in A, respectively.
A+B returns the element-wise sum of A and B.

Add Sparse to Sparse (SGL)

A specifies the first sparse matrix. The number of rows and columns in A must be equal to the number of row and columns in B, respectively.
B specifies the second sparse matrix. The number of rows and columns in B must be equal to the number of row and columns in A, respectively.
A+B returns the element-wise sum of A and B.

Add Sparse to Sparse (CDB)

A specifies the first sparse matrix. The number of rows and columns in A must be equal to the number of row and columns in B, respectively.
B specifies the second sparse matrix. The number of rows and columns in B must be equal to the number of row and columns in A, respectively.
A+B returns the element-wise sum of A and B.

Add Sparse to Sparse (CSG)

A specifies the first sparse matrix. The number of rows and columns in A must be equal to the number of row and columns in B, respectively.
B specifies the second sparse matrix. The number of rows and columns in B must be equal to the number of row and columns in A, respectively.
A+B returns the element-wise sum of A and B.

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The following table lists the support characteristics of this VI.

Supported on RT targets Yes
Suitable for bounded execution times on RT No

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