function blockedunary2d( fcn, arrays, views, strides, opts ) {
	var bsize;
	var ybuf;
	var set;
	var dv0;
	var dv1;
	var ov1;
	var sh;
	var s0;
	var s1;
	var sv;
	var ov;
	var iv;
	var i0;
	var i1;
	var j0;
	var j1;
	var N;
	var x;
	var y;
	var o;
	var k;

	// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...

	N = arrays.length;
	x = arrays[ 0 ];
	y = arrays[ 1 ];

	// Resolve the loop interchange order:
	o = loopOrder( y.shape, strides, y.strides );
	sh = o.sh;
	sv = [ o.sx, o.sy ];
	for ( k = 2; k < N; k++ ) {
		sv.push( takeIndexed( arrays[k].strides, o.idx ) );
	}
	// Determine the block size:
	bsize = blockSize( x.dtype, y.dtype );

	// Resolve a list of pointers to the first indexed elements in the respective ndarrays:
	ov = offsets( arrays );

	// Cache a reference to the output ndarray buffer:
	ybuf = y.data;

	// Cache accessors:
	set = y.accessors[1];

	// Cache offset increments for the innermost loop...
	dv0 = [];
	for ( k = 0; k < N; k++ ) {
		dv0.push( sv[k][0] );
	}
	// Initialize loop variables...
	ov1 = zeros( N );
	dv1 = zeros( N );
	iv = zeros( N );

	// Iterate over blocks...
	for ( j1 = sh[1]; j1 > 0; ) {
		if ( j1 < bsize ) {
			s1 = j1;
			j1 = 0;
		} else {
			s1 = bsize;
			j1 -= bsize;
		}
		for ( k = 0; k < N; k++ ) {
			ov1[ k ] = ov[k] + ( j1*sv[k][1] );
		}
		for ( j0 = sh[0]; j0 > 0; ) {
			if ( j0 < bsize ) {
				s0 = j0;
				j0 = 0;
			} else {
				s0 = bsize;
				j0 -= bsize;
			}
			// Compute index offsets and loop offset increments for the first ndarray elements in the current block...
			for ( k = 0; k < N; k++ ) {
				iv[ k ] = ov1[k] + ( j0*sv[k][0] );
				dv1[ k ] = sv[k][1] - ( s0*sv[k][0] );
			}
			// Iterate over the non-reduced ndarray dimensions...
			for ( i1 = 0; i1 < s1; i1++ ) {
				for ( i0 = 0; i0 < s0; i0++ ) {
					setViewOffsets( views, iv );
					set( ybuf, iv[1], fcn( views, opts ) );
					incrementOffsets( iv, dv0 );
				}
				incrementOffsets( iv, dv1 );
			}
		}
	}
}
Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.

@private
@param {Function} fcn - reduction function
@param {Array<Object>} arrays - ndarrays
@param {Array<Object>} views - initialized ndarray-like objects representing sub-array views
@param {IntegerArray} strides - loop dimension strides for the input ndarray
@param {Options} opts - function options
@returns {void}

@example
var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
var accessors = require( '@stdlib/array/base/accessors' );
var Float64Array = require( '@stdlib/array/float64' );
var filled = require( '@stdlib/array/base/filled' );
var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
var base = require( '@stdlib/ndarray/base/every' );

// Create data buffers:
var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );
var ybuf = toAccessorArray( filled( false, 3 ) );

// Define the array shapes:
var xsh = [ 1, 3, 2, 2 ];
var ysh = [ 1, 3 ];

// Define the array strides:
var sx = [ 12, 4, 2, 1 ];
var sy = [ 3, 1 ];

// Define the index offsets:
var ox = 0;
var oy = 0;

// Create an input ndarray-like object:
var x = {
    'dtype': 'float64',
    'data': xbuf,
    'shape': xsh,
    'strides': sx,
    'offset': ox,
    'order': 'row-major',
    'accessors': accessors( xbuf ).accessors
};

// Create an output ndarray-like object:
var y = {
    'dtype': 'generic',
    'data': ybuf,
    'shape': ysh,
    'strides': sy,
    'offset': oy,
    'order': 'row-major',
    'accessors': accessors( ybuf ).accessors
};

// Initialize ndarray-like objects representing sub-array views:
var views = [
    {
        'dtype': x.dtype,
        'data': x.data,
        'shape': [ 2, 2 ],
        'strides': [ 2, 1 ],
        'offset': x.offset,
        'order': x.order
    }
];

// Perform a reduction:
blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );

var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );
// returns [ [ true, false, true ] ]