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# SparseMultiply(_:_:_:)

Performs the multiplication *y = Ax* on a vector of double-precision, floating-point values.

```
func SparseMultiply(_ A: SparseMatrix_Double, _ x: DenseVector_Double, _ y: DenseVector_Double)
```

## Parameters

`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 sparse matrix by a dense vector. The following equation is an example of a matrix-vector multiplication where the matrix is sparse:

![A mathematical formula that describes the matrix multiplication, y equals A x. A four-by-four matrix multiplied by a four-element column matrix equals a four-element column matrix.](images/com.apple.accelerate/media-3703085@2x.png)

Call [`SparseMultiply(_:_:_:)`](/documentation/Accelerate/SparseMultiply(_:_:_:)-9d57s) to calculate the result.

```swift
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]

/// The values for _y_ in _y=Ax_.
let yValues = [Double](unsafeUninitializedCapacity: xValues.count) {
    resultBuffer, count 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: resultBuffer.baseAddress!)
        
        SparseMultiply(A, x, y)
    }
    
    count = xValues.count
}

/// On return, `yValues` contains:
///      `[ 140.0, 0.0, 0.0,  200.0 ]`
```

---

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