@stdlib/blas-base-dsdot

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dsdot

Calculate the dot product with extended accumulation and result of two single-precision floating-point vectors.

The dot product (or scalar product) is defined as

Installation

npm install @stdlib/blas-base-dsdot

Usage

var dsdot = require( '@stdlib/blas-base-dsdot' );

dsdot( N, x, strideX, y, strideY )

Calculates the dot product of vectors x and y with extended accumulation and result.

var Float32Array = require( '@stdlib/array-float32' );

var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );
var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );

var z = dsdot( x.length, x, 1, y, 1 );
// returns -5.0

The function has the following parameters:

• N: number of indexed elements.
• x: input Float32Array.
• strideX: index increment for x.
• y: input Float32Array.
• strideY: index increment for y.

The N and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to calculate the dot product of every other value in x and the first N elements of y in reverse order,

var Float32Array = require( '@stdlib/array-float32' );

var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );

var z = dsdot( 3, x, 2, y, -1 );
// returns 9.0

Note that indexing is relative to the first index. To introduce an offset, use typed array views.

var Float32Array = require( '@stdlib/array-float32' );

// Initial arrays...
var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );

// Create offset views...
var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // start at 4th element

var z = dsdot( 3, x1, -2, y1, 1 );
// returns 128.0

dsdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )

Calculates the dot product of x and y with extended accumulation and result and using alternative indexing semantics.

var Float32Array = require( '@stdlib/array-float32' );

var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );
var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );

var z = dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 );
// returns -5.0

The function has the following additional parameters:

• offsetX: starting index for x.
• offsetY: starting index for y.

While typed array views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to calculate the dot product of every other value in x starting from the second value with the last 3 elements in y in reverse order

var Float32Array = require( '@stdlib/array-float32' );

var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
var y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );

var z = dsdot.ndarray( 3, x, 2, 1, y, -1, y.length-1 );
// returns 128.0

Notes

• If N <= 0, both functions return 0.0.
• dsdot() corresponds to the BLAS level 1 function dsdot.

Examples

var discreteUniform = require( '@stdlib/random-array-discrete-uniform' );
var dsdot = require( '@stdlib/blas-base-dsdot' );

var opts = {
    'dtype': 'float32'
};
var x = discreteUniform( 10, 0, 100, opts );
console.log( x );

var y = discreteUniform( x.length, 0, 10, opts );
console.log( y );

var out = dsdot.ndarray( x.length, x, 1, 0, y, -1, y.length-1 );
console.log( out );

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C APIs

Usage

#include "stdlib/blas/base/dsdot.h"

c_dsdot( N, *X, strideX, *Y, strideY )

Computes the dot product of two single-precision floating-point vectors with extended accumulation and result.

const float x[] = { 4.0f, 2.0f, -3.0f, 5.0f, -1.0f };
const float y[] = { 2.0f, 6.0f, -1.0f, -4.0f, 8.0f };

double v = c_dsdot( 5, x, 1, y, 1 );
// returns -5.0

The function accepts the following arguments:

• N: [in] CBLAS_INT number of indexed elements.
• X: [in] float* first input array.
• strideX: [in] CBLAS_INT index increment for X.
• Y: [in] float* second input array.
• strideY: [in] CBLAS_INT index increment for Y.

double c_dsdot( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const float *Y, const CBLAS_INT strideY );

Examples

#include "stdlib/blas/base/dsdot.h"
#include <stdio.h>

int main( void ) {
    // Create strided arrays:
    const float x[] = { 1.0f, -2.0f, 3.0f, -4.0f, 5.0f, -6.0f, 7.0f, -8.0f };
    const float y[] = { 1.0f, -2.0f, 3.0f, -4.0f, 5.0f, -6.0f, 7.0f, -8.0f };

    // Specify the number of elements:
    const int N = 8;

    // Specify strides:
    const int strideX = 1;
    const int strideY = -1;

    // Compute the dot product:
    double d = c_dsdot( N, x, strideX, y, strideY );

    // Print the result:
    printf( "dot product: %lf\n", d );
}

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References

• Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald Kincaid. 1979. "Algorithm 539: Basic Linear Algebra Subprograms for Fortran Usage [F1]." ACM Transactions on Mathematical Software 5 (3). New York, NY, USA: Association for Computing Machinery: 324–25. doi:10.1145/355841.355848.

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See Also

• @stdlib/blas-base/ddot: calculate the dot product of two double-precision floating-point vectors.
• @stdlib/blas-base/sdot: calculate the dot product of two single-precision floating-point vectors.
• @stdlib/blas-base/sdsdot: calculate the dot product of two single-precision floating-point vectors with extended accumulation.

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Notice

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For more information on the project, filing bug reports and feature requests, and guidance on how to develop stdlib, see the main project repository.

Community

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License

See LICENSE.

Copyright

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