sdot

Compute the dot product of x and y.

Usage

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

sdot.main( N, x, strideX, y, strideY )

Computes the dot product of x and y.

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 = sdot.main( x.length, x, 1, y, 1 );
// returns -5.0

The function has the following parameters:

  • N: number of indexed elements.
  • x: first input Float32Array.
  • strideX: index increment for x.
  • y: second 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 = sdot.main( 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 = sdot.main( 3, x1, -2, y1, 1 );
// returns 128.0

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

Computes the dot product of x and y 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 = sdot.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 = sdot.ndarray( 3, x, 2, 1, y, -1, y.length-1 );
// returns 128.0

Module

sdot.Module( memory )

Returns a new WebAssembly module wrapper instance which uses the provided WebAssembly memory instance as its underlying memory.

var Memory = require( '@stdlib/wasm/memory' );

// Create a new memory instance with an initial size of 10 pages (640KiB) and a maximum size of 100 pages (6.4MiB):
var mem = new Memory({
    'initial': 10,
    'maximum': 100
});

// Create a BLAS routine:
var mod = new sdot.Module( mem );
// returns <Module>

// Initialize the routine:
mod.initializeSync();

sdot.Module.prototype.main( N, xp, sx, yp, sy )

Computes the dot product of x and y.

var Memory = require( '@stdlib/wasm/memory' );
var oneTo = require( '@stdlib/array/one-to' );
var ones = require( '@stdlib/array/ones' );
var zeros = require( '@stdlib/array/zeros' );
var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' );

// Create a new memory instance with an initial size of 10 pages (640KiB) and a maximum size of 100 pages (6.4MiB):
var mem = new Memory({
    'initial': 10,
    'maximum': 100
});

// Create a BLAS routine:
var mod = new sdot.Module( mem );
// returns <Module>

// Initialize the routine:
mod.initializeSync();

// Define a vector data type:
var dtype = 'float32';

// Specify a vector length:
var N = 5;

// Define pointers (i.e., byte offsets) for storing two vectors:
var xptr = 0;
var yptr = N * bytesPerElement( dtype );

// Write vector values to module memory:
mod.write( xptr, oneTo( N, dtype ) );
mod.write( yptr, ones( N, dtype ) );

// Perform computation:
var z = mod.main( N, xptr, 1, yptr, 1 );

console.log( z );

The function has the following parameters:

  • N: number of indexed elements.
  • xp: first input Float32Array pointer (i.e., byte offset).
  • sx: index increment for x.
  • yp: second input Float32Array pointer (i.e., byte offset).
  • sy: index increment for y.

sdot.Module.prototype.ndarray( N, xp, sx, ox, yp, sy, oy )

Computes the dot product of x and y using alternative indexing semantics.

var Memory = require( '@stdlib/wasm/memory' );
var oneTo = require( '@stdlib/array/one-to' );
var ones = require( '@stdlib/array/ones' );
var zeros = require( '@stdlib/array/zeros' );
var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' );

// Create a new memory instance with an initial size of 10 pages (640KiB) and a maximum size of 100 pages (6.4MiB):
var mem = new Memory({
    'initial': 10,
    'maximum': 100
});

// Create a BLAS routine:
var mod = new sdot.Module( mem );
// returns <Module>

// Initialize the routine:
mod.initializeSync();

// Define a vector data type:
var dtype = 'float32';

// Specify a vector length:
var N = 5;

// Define pointers (i.e., byte offsets) for storing two vectors:
var xptr = 0;
var yptr = N * bytesPerElement( dtype );

// Write vector values to module memory:
mod.write( xptr, oneTo( N, dtype ) );
mod.write( yptr, ones( N, dtype ) );

// Perform computation:
var z = mod.ndarray( N, xptr, 1, 0, yptr, 1, 0 );

console.log( z );

The function has the following additional parameters:

  • ox: starting index for x.
  • oy: starting index for y.

Notes

  • If N <= 0, both main and ndarray methods return 0.0.
  • This package implements routines using WebAssembly. When provided arrays which are not allocated on a sdot module memory instance, data must be explicitly copied to module memory prior to computation. Data movement may entail a performance cost, and, thus, if you are using arrays external to module memory, you should prefer using @stdlib/blas/base/sdot. However, if working with arrays which are allocated and explicitly managed on module memory, you can achieve better performance when compared to the pure JavaScript implementations found in @stdlib/blas/base/sdot. Beware that such performance gains may come at the cost of additional complexity when having to perform manual memory management. Choosing between implementations depends heavily on the particular needs and constraints of your application, with no one choice universally better than the other.
  • sdot() corresponds to the BLAS level 1 function sdot.

Examples

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

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 z = sdot.ndarray( x.length, x, 1, 0, y, -1, y.length-1 );
console.log( z );
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