diff --git a/code/scipy/linalg/linalg.c b/code/scipy/linalg/linalg.c
index dc71ca07..53efd182 100644
--- a/code/scipy/linalg/linalg.c
+++ b/code/scipy/linalg/linalg.c
@@ -410,16 +410,15 @@ static mp_obj_t linalg_svd(mp_obj_t _a) {
     }
     #endif
 
-    ndarray_obj_t *B = ndarray_new_dense_ndarray(2, A->shape, NDARRAY_FLOAT);
-    mp_float_t *b = (mp_float_t *)B->array;
-    
     mp_float_t (*get_A_element)(void *) = ndarray_get_float_function(A->dtype);
     uint8_t *a = (uint8_t *)A->array;
     
-    size_t ncolumns = B->shape[ULAB_MAX_DIMS - 1];
-    size_t nrows = B->shape[ULAB_MAX_DIMS - 2];
+    size_t ncolumns = A->shape[ULAB_MAX_DIMS - 1];
+    size_t nrows = A->shape[ULAB_MAX_DIMS - 2];
 
-    // copy data from a to B
+    mp_float_t *b = m_new(mp_float_t, nrows * ncolumns);
+    
+    // copy data from a to b
     for(size_t i = 0; i < ncolumns; i++) {
         for(size_t j = 0; j < nrows; j++) {
             *b++ = get_A_element(a);
@@ -762,8 +761,35 @@ static mp_obj_t linalg_svd(mp_obj_t _a) {
     // // solve for (something)
     // B = matd_op("M'*F*M", LP, B, RP);
 
-    // // update LS and RS, remembering that RS will be transposed.
+    ndarray_obj_t *S = ndarray_new_dense_ndarray(2, ndarray_shape_vector(0, 0, nrows, ncolumns), NDARRAY_FLOAT);
+    mp_float_t *s = (mp_float_t *)S->array;
+
+    // B * RP
+    mp_float_t *x = m_new(mp_float_t, nrows * ncolumns);
+    for(size_t i = 0; i < nrows; i++) {
+        for(size_t j = 0; j < ncolumns; j++) {
+            mp_float_t tmp = 0.0;
+            for(size_t k = 0; k < ncolumns; k++) {
+                tmp += b[i * nrows + k] * RP[k * nrows + j]; /* B[i, k] * RP[k, j] */
+            }
+            x[i * nrows + j] = tmp; /* x[i, j] */ 
+        }
+    }
     
+    // S = LS' * x = LS' * (B * RP)
+    for(size_t i = 0; i < nrows; i++) {
+        for(size_t j = 0; j < nrows; j++) {
+            mp_float_t tmp = 0.0;
+            for(size_t k = 0; k < nrows; k++) {
+                tmp += LS[k * nrows + i] * x[k * nrows + j]; /* LS[k, i] * x[k, j] */
+            }
+            s[i * nrows + j] = tmp; /* S[i, j] */ 
+        }
+    }
+
+    m_del(mp_float_t, x, nrows * ncolumns);
+    m_del(mp_float_t, b, nrows * ncolumns);
+
     // LS = matd_op("F*M", LS, LP);
     ndarray_obj_t *U = ndarray_new_dense_ndarray(2, ndarray_shape_vector(0, 0, nrows, nrows), NDARRAY_FLOAT);
     mp_float_t *u = (mp_float_t *)U->array;
@@ -797,18 +823,18 @@ static mp_obj_t linalg_svd(mp_obj_t _a) {
     m_del(mp_float_t, RS, ncolumns * ncolumns);
     m_del(mp_float_t, RP, ncolumns * ncolumns);
 
-    // make B exactly diagonal
+    // make S exactly diagonal
     for(size_t i = 0; i < ncolumns; i++) {
         for(size_t j = 0; j < nrows; j++) {
             if(i != j) {
-                b[i * ncolumns + j] = 0.0; /* B[i, j] */
+                s[i * ncolumns + j] = 0.0; /* B[i, j] */
             }
         }
     }
 
     mp_obj_t *items = m_new(mp_obj_t, 3);
     items[0] = U;
-    items[1] = B;
+    items[1] = S;
     items[2] = V;
     
     mp_obj_t tuple = mp_obj_new_tuple(3, items);