SparseMultiplyAdd(_:_:_:_:)
Performs the multiply operation y += alpha * Ax on a vector of double-precision, floating-point values.
Declaration
func SparseMultiplyAdd(_ alpha: Double, _ A: SparseMatrix_Double, _ x: DenseVector_Double, _ y: DenseVector_Double)Parameters
- alpha:
The scalar value alpha in y += alpha * Ax.
- A:
The sparse matrix A in y += Ax.
- x:
The dense vector x in y += Ax.
- y:
The dense vector y in y += Ax.
Discussion
Use this function to multiply a scalar by a sparse matrix, then by a dense vector, and accumulate the result. The following equation is an example of a matrix-vector multiplication where the matrix is sparse:
[Image]
Call SparseMultiplyAdd(_:_:_:_:) to calculate the result.
let rowCount = Int32(4)
let columnCount = Int32(4)
let blockCount = 4
let blockSize = UInt8(1)
let rowIndices: [Int32] = [0, 3, 0, 3]
let columnIndices: [Int32] = [0, 0, 3, 3]
let data = [1.0, 4.0, 13.0, 16.0]
/// The _A_ in _y+=Ax_.
let A = SparseConvertFromCoordinate(rowCount, columnCount,
blockCount, blockSize,
SparseAttributes_t(),
rowIndices, columnIndices,
data)
defer {
SparseCleanup(A)
}
/// The values for _x_ in _y+=Ax_.
var xValues = [10.0, -1.0, -1.0, 10.0]
var yValues = [1.0, 1.0, 1.0, 1.0]
let alpha = 2.0
/// The values for _y_ in _y+=Ax_.
yValues.withUnsafeMutableBufferPointer { yValuesPtr in
xValues.withUnsafeMutableBufferPointer { xValuesPtr in
/// The _x_ in _y+=Ax_.
let x = DenseVector_Double(count: 4,
data: xValuesPtr.baseAddress!)
/// The _y_ in _y+=Ax_.
let y = DenseVector_Double(count: 4,
data: yValuesPtr.baseAddress!)
SparseMultiplyAdd(alpha, A, x, y)
}
}
/// On return, `yValues` contains:
/// `[ 281.0, 1.0, 1.0, 401.0 ]`