diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/README.md b/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/README.md
new file mode 100644
index 000000000000..c2fb379879a3
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/README.md
@@ -0,0 +1,150 @@
+
+
+# ggemm
+
+> Perform the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C`.
+
+
+
+
+
+
+
+## Usage
+
+```javascript
+var ggemm = require( '@stdlib/blas/base/ndarray/ggemm' );
+```
+
+#### ggemm( arrays )
+
+Performs the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C`, where `op(X)` is either `op(X) = X` or `op(X) = X^T`, `alpha` and `beta` are scalars, `A`, `B`, and `C` are matrices, with `op(A)` an `M` by `K` matrix, `op(B)` a `K` by `N` matrix, and `C` an `M` by `N` matrix.
+
+
+
+```javascript
+var matrix = require( '@stdlib/ndarray/matrix/ctor' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' );
+
+var A = matrix( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ], 'generic' );
+var B = matrix( [ [ 1.0, 1.0 ], [ 0.0, 1.0 ] ], 'generic' );
+var C = matrix( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ], 'generic' );
+
+var transA = scalar2ndarray( resolveEnum( 'no-transpose' ), {
+ 'dtype': 'int32'
+});
+var transB = scalar2ndarray( resolveEnum( 'no-transpose' ), {
+ 'dtype': 'int32'
+});
+var alpha = scalar2ndarray( 1.0, {
+ 'dtype': 'generic'
+});
+var beta = scalar2ndarray( 1.0, {
+ 'dtype': 'generic'
+});
+
+var out = ggemm( [ A, B, C, transA, transB, alpha, beta ] );
+// returns [ [ 2.0, 5.0 ], [ 6.0, 11.0 ] ]
+
+var bool = ( out === C );
+// returns true
+```
+
+The function has the following parameters:
+
+- **arrays**: array-like object containing the following ndarrays:
+
+ - a two-dimensional input ndarray corresponding to `A`.
+ - a two-dimensional input ndarray corresponding to `B`.
+ - a two-dimensional input/output ndarray corresponding to `C`.
+ - a zero-dimensional ndarray specifying whether `A` should be transposed, conjugate-transposed, or not transposed.
+ - a zero-dimensional ndarray specifying whether `B` should be transposed, conjugate-transposed, or not transposed.
+ - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`.
+ - a zero-dimensional ndarray containing a scalar constant corresponding to `beta`.
+
+
+
+
+
+
+
+
+
+
+
+## Examples
+
+
+
+
+
+```javascript
+var discreteUniform = require( '@stdlib/random/discrete-uniform' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var ggemm = require( '@stdlib/blas/base/ndarray/ggemm' );
+
+var opts = {
+ 'dtype': 'generic'
+};
+
+var A = discreteUniform( [ 3, 4 ], 0, 10, opts );
+var B = discreteUniform( [ 4, 2 ], 0, 10, opts );
+var C = discreteUniform( [ 3, 2 ], 0, 10, opts );
+
+var transA = scalar2ndarray( resolveEnum( 'no-transpose' ), {
+ 'dtype': 'int32'
+});
+var transB = scalar2ndarray( resolveEnum( 'no-transpose' ), {
+ 'dtype': 'int32'
+});
+var alpha = scalar2ndarray( 1.0, opts );
+var beta = scalar2ndarray( 1.0, opts );
+
+var out = ggemm( [ A, B, C, transA, transB, alpha, beta ] );
+console.log( ndarray2array( out ) );
+```
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/benchmark/benchmark.js
new file mode 100644
index 000000000000..ec88e8053ef5
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/benchmark/benchmark.js
@@ -0,0 +1,125 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var uniform = require( '@stdlib/random/uniform' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' );
+var format = require( '@stdlib/string/format' );
+var pkg = require( './../package.json' ).name;
+var ggemm = require( './../lib' );
+
+
+// VARIABLES //
+
+var options = {
+ 'dtype': 'generic'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+ var transA;
+ var transB;
+ var alpha;
+ var beta;
+ var A;
+ var B;
+ var C;
+
+ A = uniform( [ len, len ], -100.0, 100.0, options );
+ B = uniform( [ len, len ], -100.0, 100.0, options );
+ C = uniform( [ len, len ], -100.0, 100.0, options );
+
+ alpha = scalar2ndarray( 1.0, options );
+ beta = scalar2ndarray( 1.0, options );
+ transA = scalar2ndarray( resolveEnum( 'no-transpose' ), {
+ 'dtype': 'int32'
+ });
+ transB = scalar2ndarray( resolveEnum( 'no-transpose' ), {
+ 'dtype': 'int32'
+ });
+
+ return benchmark;
+
+ /**
+ * Benchmark function.
+ *
+ * @private
+ * @param {Benchmark} b - benchmark instance
+ */
+ function benchmark( b ) {
+ var z;
+ var i;
+
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ z = ggemm( [ A, B, C, transA, transB, alpha, beta ] );
+ if ( typeof z !== 'object' ) {
+ b.fail( 'should return an ndarray' );
+ }
+ }
+ b.toc();
+ if ( isnan( z.get( i%len, i%len ) ) ) {
+ b.fail( 'should not return NaN' );
+ }
+ b.pass( 'benchmark finished' );
+ b.end();
+ }
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+ var len;
+ var min;
+ var max;
+ var f;
+ var i;
+
+ min = 1; // 10^min
+ max = 3; // 10^max
+
+ for ( i = min; i <= max; i++ ) {
+ len = pow( 10, i );
+ f = createBenchmark( len );
+ bench( format( '%s:len=%d', pkg, len ), f );
+ }
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/docs/repl.txt b/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/docs/repl.txt
new file mode 100644
index 000000000000..6a4676450cf1
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/docs/repl.txt
@@ -0,0 +1,54 @@
+
+{{alias}}( arrays )
+ Performs the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C`,
+ where `op(X)` is either `op(X) = X` or `op(X) = X^T`, `alpha` and `beta`
+ are scalars, `A`, `B`, and `C` are matrices, with `op(A)` an `M` by `K`
+ matrix, `op(B)` a `K` by `N` matrix, and `C` an `M` by `N` matrix.
+
+ Parameters
+ ----------
+ arrays: ArrayLikeObject
+ Array-like object containing the following ndarrays:
+
+ - a two-dimensional input ndarray corresponding to `A`.
+ - a two-dimensional input ndarray corresponding to `B`.
+ - a two-dimensional input/output ndarray corresponding to `C`.
+ - a zero-dimensional ndarray specifying whether `A` should be
+ transposed, conjugate-transposed, or not transposed.
+ - a zero-dimensional ndarray specifying whether `B` should be
+ transposed, conjugate-transposed, or not transposed.
+ - a zero-dimensional ndarray containing a scalar constant corresponding
+ to `alpha`.
+ - a zero-dimensional ndarray containing a scalar constant corresponding
+ to `beta`.
+
+ Returns
+ -------
+ out: ndarray
+ Output ndarray.
+
+ Examples
+ --------
+ > var abuf = [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ];
+ > var A = {{alias:@stdlib/ndarray/matrix/ctor}}( abuf, 'generic' );
+
+ > var bbuf = [ [ 1.0, 1.0 ], [ 0.0, 1.0 ] ];
+ > var B = {{alias:@stdlib/ndarray/matrix/ctor}}( bbuf, 'generic' );
+
+ > var cbuf = [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ];
+ > var C = {{alias:@stdlib/ndarray/matrix/ctor}}( cbuf, 'generic' );
+
+ > var opts = { 'dtype': 'generic' };
+ > var alpha = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, opts );
+ > var beta = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, opts );
+
+ > var transA = {{alias:@stdlib/ndarray/from-scalar}}( 'no-transpose' );
+ > var transB = {{alias:@stdlib/ndarray/from-scalar}}( 'no-transpose' );
+
+ > {{alias}}( [ A, B, C, transA, transB, alpha, beta ] );
+ > C
+ [ [ 2.0, 5.0 ], [ 6.0, 11.0 ] ]
+
+ See Also
+ --------
+
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/docs/types/index.d.ts
new file mode 100644
index 000000000000..7c2196b143b1
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/docs/types/index.d.ts
@@ -0,0 +1,76 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+// TypeScript Version: 4.1
+
+///
+
+import { typedndarray, ndarray } from '@stdlib/types/ndarray';
+
+/**
+* Performs the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C`, where `op(X)` is either `op(X) = X` or `op(X) = X^T`, `alpha` and `beta` are scalars, `A`, `B`, and `C` are matrices, with `op(A)` an `M` by `K` matrix, `op(B)` a `K` by `N` matrix, and `C` an `M` by `N` matrix.
+*
+* ## Notes
+*
+* - The function expects the following ndarrays:
+*
+* - a two-dimensional input ndarray corresponding to `A`.
+* - a two-dimensional input ndarray corresponding to `B`.
+* - a two-dimensional input/output ndarray corresponding to `C`.
+* - a zero-dimensional ndarray specifying whether `A` should be transposed, conjugate-transposed, or not transposed.
+* - a zero-dimensional ndarray specifying whether `B` should be transposed, conjugate-transposed, or not transposed.
+* - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`.
+* - a zero-dimensional ndarray containing a scalar constant corresponding to `beta`.
+*
+* @param arrays - array-like object containing ndarrays
+* @returns output ndarray
+*
+* @example
+* var matrix = require( '@stdlib/ndarray/matrix/ctor' );
+* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+* var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' );
+*
+* var A = matrix( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ], 'generic' );
+* var B = matrix( [ [ 1.0, 1.0 ], [ 0.0, 1.0 ] ], 'generic' );
+* var C = matrix( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ], 'generic' );
+*
+* var transA = scalar2ndarray( resolveEnum( 'no-transpose' ), {
+* 'dtype': 'int32'
+* });
+* var transB = scalar2ndarray( resolveEnum( 'no-transpose' ), {
+* 'dtype': 'int32'
+* });
+* var alpha = scalar2ndarray( 1.0, {
+* 'dtype': 'generic'
+* });
+* var beta = scalar2ndarray( 1.0, {
+* 'dtype': 'generic'
+* });
+*
+* var z = ggemm( [ A, B, C, transA, transB, alpha, beta ] );
+* // returns [ [ 2.0, 5.0 ], [ 6.0, 11.0 ] ]
+*
+* var bool = ( z === C );
+* // returns true
+*/
+declare function ggemm = typedndarray>( arrays: [ typedndarray, typedndarray, T, ndarray, ndarray, typedndarray, typedndarray ] ): T;
+
+
+// EXPORTS //
+
+export = ggemm;
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/docs/types/test.ts b/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/docs/types/test.ts
new file mode 100644
index 000000000000..0a8d67c099e1
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/docs/types/test.ts
@@ -0,0 +1,93 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+/* eslint-disable space-in-parens */
+
+import zeros = require( '@stdlib/ndarray/zeros' );
+import ggemm = require( '@stdlib/blas/base/ndarray/ggemm' );
+
+
+// TESTS //
+
+// The function returns an ndarray...
+{
+ const A = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+ const B = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+ const C = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+ const transA = zeros( [], {
+ 'dtype': 'int32'
+ });
+ const transB = zeros( [], {
+ 'dtype': 'int32'
+ });
+ const alpha = zeros( [], {
+ 'dtype': 'generic'
+ });
+ const beta = zeros( [], {
+ 'dtype': 'generic'
+ });
+
+ ggemm( [ A, B, C, transA, transB, alpha, beta ] ); // $ExpectType genericndarray
+}
+
+// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays...
+{
+ ggemm( '10' ); // $ExpectError
+ ggemm( 10 ); // $ExpectError
+ ggemm( true ); // $ExpectError
+ ggemm( false ); // $ExpectError
+ ggemm( null ); // $ExpectError
+ ggemm( undefined ); // $ExpectError
+ ggemm( [] ); // $ExpectError
+ ggemm( {} ); // $ExpectError
+ ggemm( ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an unsupported number of arguments...
+{
+ const A = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+ const B = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+ const C = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+ const transA = zeros( [], {
+ 'dtype': 'int32'
+ });
+ const transB = zeros( [], {
+ 'dtype': 'int32'
+ });
+ const alpha = zeros( [], {
+ 'dtype': 'generic'
+ });
+ const beta = zeros( [], {
+ 'dtype': 'generic'
+ });
+
+ ggemm(); // $ExpectError
+ ggemm( [ A, B, C, transA, transB, alpha, beta ], {} ); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/examples/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/examples/index.js
new file mode 100644
index 000000000000..b06c5a45bf25
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/examples/index.js
@@ -0,0 +1,45 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+var discreteUniform = require( '@stdlib/random/discrete-uniform' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var ggemm = require( './../lib' );
+
+var opts = {
+ 'dtype': 'generic'
+};
+
+var A = discreteUniform( [ 3, 4 ], 0, 10, opts );
+var B = discreteUniform( [ 4, 2 ], 0, 10, opts );
+var C = discreteUniform( [ 3, 2 ], 0, 10, opts );
+
+var transA = scalar2ndarray( resolveEnum( 'no-transpose' ), {
+ 'dtype': 'int32'
+});
+var transB = scalar2ndarray( resolveEnum( 'no-transpose' ), {
+ 'dtype': 'int32'
+});
+var alpha = scalar2ndarray( 1.0, opts );
+var beta = scalar2ndarray( 1.0, opts );
+
+var out = ggemm( [ A, B, C, transA, transB, alpha, beta ] );
+console.log( ndarray2array( out ) );
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/lib/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/lib/index.js
new file mode 100644
index 000000000000..147e8a4c4293
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/lib/index.js
@@ -0,0 +1,63 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+/**
+* BLAS level 3 routine to perform the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C`.
+*
+* @module @stdlib/blas/base/ndarray/ggemm
+*
+* @example
+* var matrix = require( '@stdlib/ndarray/matrix/ctor' );
+* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+* var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' );
+* var ggemm = require( '@stdlib/blas/base/ndarray/ggemm' );
+*
+* var A = matrix( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ], 'generic' );
+* var B = matrix( [ [ 1.0, 1.0 ], [ 0.0, 1.0 ] ], 'generic' );
+* var C = matrix( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ], 'generic' );
+*
+* var transA = scalar2ndarray( resolveEnum( 'no-transpose' ), {
+* 'dtype': 'int32'
+* });
+* var transB = scalar2ndarray( resolveEnum( 'no-transpose' ), {
+* 'dtype': 'int32'
+* });
+* var alpha = scalar2ndarray( 1.0, {
+* 'dtype': 'generic'
+* });
+* var beta = scalar2ndarray( 1.0, {
+* 'dtype': 'generic'
+* });
+*
+* var out = ggemm( [ A, B, C, transA, transB, alpha, beta ] );
+* // returns [ [ 2.0, 5.0 ], [ 6.0, 11.0 ] ]
+*
+* var bool = ( out === C );
+* // returns true
+*/
+
+// MODULES //
+
+var main = require( './main.js' );
+
+
+// EXPORTS //
+
+module.exports = main;
diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/lib/main.js b/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/lib/main.js
new file mode 100644
index 000000000000..bf2c490a9afa
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/lib/main.js
@@ -0,0 +1,134 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var getShape = require( '@stdlib/ndarray/base/shape' );
+var getStrides = require( '@stdlib/ndarray/base/strides' );
+var getOffset = require( '@stdlib/ndarray/base/offset' );
+var getData = require( '@stdlib/ndarray/base/data-buffer' );
+var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' );
+var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' );
+var strided = require( '@stdlib/blas/base/ggemm' ).ndarray;
+
+
+// VARIABLES //
+
+var NO_TRANSPOSE = resolveEnum( 'no-transpose' );
+
+
+// MAIN //
+
+/**
+* Performs the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C`, where `op(X)` is either `op(X) = X` or `op(X) = X^T`, `alpha` and `beta` are scalars, `A`, `B`, and `C` are matrices, with `op(A)` an `M` by `K` matrix, `op(B)` a `K` by `N` matrix, and `C` an `M` by `N` matrix.
+*
+* ## Notes
+*
+* - The function expects the following ndarrays:
+*
+* - a two-dimensional input ndarray corresponding to `A`.
+* - a two-dimensional input ndarray corresponding to `B`.
+* - a two-dimensional input/output ndarray corresponding to `C`.
+* - a zero-dimensional ndarray specifying whether `A` should be transposed, conjugate-transposed, or not transposed.
+* - a zero-dimensional ndarray specifying whether `B` should be transposed, conjugate-transposed, or not transposed.
+* - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`.
+* - a zero-dimensional ndarray containing a scalar constant corresponding to `beta`.
+*
+* @param {ArrayLikeObject