changed vector to Vector in comments to fix problem in gcc preprocessor

on misnky

src/GPU/cuUtils_template.Xcu

@@ -358,7 +358,7 @@ __global__ void  compute_hh_dotp_c_kernel_complex_single(cuFloatComplex* hh, cuF
 #endif
     int t_idx, v_idx;
 
-    //  The vector index (v_idx) identifies the pair of HH reflectors from which the dot product is computed
+    //  The Vector index (v_idx) identifies the pair of HH reflectors from which the dot product is computed
     v_idx = blockIdx.x  ;
 
     //  The thread index indicates the position within the two HH reflectors

src/elpa1/elpa1_tools_template.X90

@@ -137,7 +137,7 @@
     !         order, D(I) < D(J)  for I < J.
     !
     !  Z      (input) DOUBLE PRECISION array, dimension (N)
-    !         The components of the updating vector.
+    !         The components of the updating Vector.
     !
     !  DELTA  (output) DOUBLE PRECISION array, dimension (N)
     !         DELTA contains (D(j) - lambda_I) in its  j-th component.

src/elpa1/elpa1_trans_ev_template.X90

@@ -275,8 +275,8 @@
         nb = 0
         do ic = ics, ice
 
-          l_colh = local_index(ic  , my_pcol, np_cols, nblk, -1) ! Column of Householder vector
-          l_rows = local_index(ic-1, my_prow, np_rows, nblk, -1) ! # rows of Householder vector
+          l_colh = local_index(ic  , my_pcol, np_cols, nblk, -1) ! Column of Householder Vector
+          l_rows = local_index(ic-1, my_prow, np_rows, nblk, -1) ! # rows of Householder Vector
 
 
           if (my_pcol == cur_pcol) then
@@ -306,7 +306,7 @@
 
         nb = 0
         do ic = ics, ice
-          l_rows = local_index(ic-1, my_prow, np_rows, nblk, -1) ! # rows of Householder vector
+          l_rows = local_index(ic-1, my_prow, np_rows, nblk, -1) ! # rows of Householder Vector
           hvm(1:l_rows,nstor+1) = hvb(nb+1:nb+l_rows)
           if (useGPU) then
             hvm_ubnd = l_rows

src/elpa1/elpa1_tridiag_template.X90

@@ -174,8 +174,8 @@
 
 #if REALCASE == 1
       real(kind=REAL_DATATYPE), allocatable         :: tmp(:), &
-                                                       v_row(:), &   ! used to store calculated Householder vector
-                                                       v_col(:), &   ! the same vector, but transposed - differently distributed among MPI tasks
+                                                       v_row(:), &   ! used to store calculated Householder Vector
+                                                       v_col(:), &   ! the same Vector, but transposed - differently distributed among MPI tasks
                                                        u_row(:), &
                                                        u_col(:)
 #endif
@@ -183,8 +183,8 @@
       complex(kind=COMPLEX_DATATYPE), allocatable   :: tmp(:), v_row(:), v_col(:), u_row(:), u_col(:)
 #endif
       ! the following two matrices store pairs of vectors v and u calculated in each step
-      ! at most max_stored_uv vector pairs are stored, than the matrix A_i is explicitli updated
-      ! u and v are stored both in row and vector forms
+      ! at most max_stored_uv Vector pairs are stored, than the matrix A_i is explicitli updated
+      ! u and v are stored both in row and Vector forms
       ! pattern: v1,u1,v2,u2,v3,u3,....
       ! todo: It is little bit confusing, I think, that variables _row actually store columns and vice versa
 #if REALCASE == 1
@@ -266,7 +266,7 @@
       ! allocate memmory for vectors
       ! todo: It is little bit confusing, I think, that variables _row actually store columns and vice versa
       ! todo: if something has length max_local_rows, it is actually a column, no?
-      ! todo: probably one should read it as v_row = vector v distributed among rows
+      ! todo: probably one should read it as v_row = Vector v distributed among rows
       !
       allocate(tmp(MAX(max_local_rows,max_local_cols)), stat=istat, errmsg=errorMessage)
       call check_alloc("tridiag_&
@@ -359,7 +359,7 @@
       endif
 
       ! main cycle of tridiagonalization
-      ! in each step, 1 Householder vector is calculated
+      ! in each step, 1 Householder Vector is calculated
       do istep = na, 3 ,-1
 
         ! Calculate number of local rows and columns of the still remaining matrix
@@ -367,12 +367,12 @@
         l_rows = local_index(istep-1, my_prow, np_rows, nblk, -1)
         l_cols = local_index(istep-1, my_pcol, np_cols, nblk, -1)
 
-        ! Calculate vector for Householder transformation on all procs
+        ! Calculate Vector for Householder transformation on all procs
         ! owning column istep
 
         if (my_pcol == pcol(istep, nblk, np_cols)) then
 
-          ! Get vector to be transformed; distribute last element and norm of
+          ! Get Vector to be transformed; distribute last element and norm of
           ! remaining elements to all procs in current column
 
           ! copy l_cols + 1 column of A to v_row
@@ -434,7 +434,7 @@
 #endif
                &PRECISION &
                              (vrl, vnorm2, xf, tau(istep))
-          ! Scale v_row and store Householder vector for back transformation
+          ! Scale v_row and store Householder Vector for back transformation
 
           v_row(1:l_rows) = v_row(1:l_rows) * xf
           if (my_prow == prow(istep-1, nblk, np_rows)) then
@@ -444,7 +444,7 @@
             e_vec(istep-1) = vrl
           endif
 
-          ! store Householder vector for back transformation
+          ! store Householder Vector for back transformation
           a_mat(1:l_rows,l_cols+1) = v_row(1:l_rows)
 
           ! add tau after the end of actuall v_row, to be broadcasted with it
@@ -452,7 +452,7 @@
          endif !(my_pcol == pcol(istep, nblk, np_cols))
 
 #ifdef WITH_MPI
-         ! Broadcast the Householder vector (and tau) along columns
+         ! Broadcast the Householder Vector (and tau) along columns
          call MPI_Bcast(v_row, l_rows+1, MPI_MATH_DATATYPE_PRECISION,    &
                         pcol(istep, nblk, np_cols), mpi_comm_cols, mpierr)
 #endif /* WITH_MPI */
@@ -460,7 +460,7 @@
         !recover tau, which has been broadcasted together with v_row
         tau(istep) =  v_row(l_rows+1)
 
-        ! Transpose Householder vector v_row -> v_col
+        ! Transpose Householder Vector v_row -> v_col
         call elpa_transpose_vectors_&
              &MATH_DATATYPE&
              &_&
@@ -533,7 +533,7 @@
 
               ! multiplication by blocks is efficient only for CPU
               ! for GPU we introduced 2 other ways, either by stripes (more simmilar to the original
-              ! CPU implementation) or by one large matrix vector multiply
+              ! CPU implementation) or by one large matrix Vector multiply
               if (.not. useGPU) then
                 call timer%start("blas")
                 call PRECISION_GEMV(BLAS_TRANS_OR_CONJ,  &
@@ -755,7 +755,7 @@
 #endif
         enddo
 
-        ! We have calculated another Hauseholder vector, number of implicitly stored increased
+        ! We have calculated another Hauseholder Vector, number of implicitly stored increased
         n_stored_vecs = n_stored_vecs+1
 
         ! If the limit of max_stored_uv is reached, calculate A + VU**T + UV**T

src/elpa2/elpa2_bandred_template.X90

@@ -646,7 +646,7 @@
 #endif /* REALCASE == 1 */
          do lc = n_cols, 1, -1
 
-           ncol = istep*nbw + lc ! absolute column number of householder vector
+           ncol = istep*nbw + lc ! absolute column number of householder Vector
            nrow = ncol - nbw ! Absolute number of pivot row
 
            lr  = local_index(nrow, my_prow, np_rows, nblk, -1) ! current row length
@@ -660,10 +660,10 @@
 
            if (my_pcol==cur_pcol) then
 
-             ! Get vector to be transformed; distribute last element and norm of
+             ! Get Vector to be transformed; distribute last element and norm of
              ! remaining elements to all procs in current column
 
-             vr(1:lr) = a(1:lr,lch) ! vector to be transformed
+             vr(1:lr) = a(1:lr,lch) ! Vector to be transformed
 
              if (my_prow==prow(nrow, nblk, np_rows)) then
                aux1(1) = dot_product(vr(1:lr-1),vr(1:lr-1))
@@ -706,7 +706,7 @@
 #endif
              &PRECISION &
                               (vrl, vnorm2, xf, tau)
-             ! Scale vr and store Householder vector for back transformation
+             ! Scale vr and store Householder Vector for back transformation
 
              vr(1:lr) = vr(1:lr) * xf
              if (my_prow==prow(nrow, nblk, np_rows)) then
@@ -724,7 +724,7 @@
 
            endif
 
-           ! Broadcast Householder vector and tau along columns
+           ! Broadcast Householder Vector and tau along columns
 
            vr(lr+1) = tau
 #ifdef WITH_MPI
@@ -759,7 +759,7 @@
 #if COMPLEXCASE == 1
            tmat(lc,lc,istep) = conjg(tau) ! Store tau in diagonal of tmat
 #endif
-           ! Transform remaining columns in current block with Householder vector
+           ! Transform remaining columns in current block with Householder Vector
            ! Local dot product
 
 #if REALCASE == 1

src/elpa2/elpa2_compute_real_template.X90

@@ -343,7 +343,7 @@
                 ab(nb+2:,ns+i-1) = CONST_0_0
               enddo
 
-              !send hh-vector
+              !send hh-Vector
               if (iblk==nblocks) then
 #ifdef WITH_MPI
                 call timer%start("mpi_communication")
@@ -402,7 +402,7 @@
 	      &(nb-nb2,nr,nb2,ab(nb+1-nb2,ns+nb2),2*nb-1,w_new,hv_new,work,nb)
             endif
 
-            ! Use new HH vector for the next block
+            ! Use new HH Vector for the next block
             hv(:,:) = hv_new(:,:)
             tau = tau_new
           enddo

src/elpa2/elpa2_trans_ev_band_to_full_template.X90

@@ -344,7 +344,7 @@
           ns = 0
 
           do lc = 1, n_cols
-            ncol = istep*nbw + lc ! absolute column number of householder vector
+            ncol = istep*nbw + lc ! absolute column number of householder Vector
             nrow = ncol - nbw ! absolute number of pivot row
 
             l_rows = local_index(nrow-1, my_prow, np_rows, nblk, -1) ! row length for bcast
@@ -704,9 +704,9 @@
 
           do lc = 1, n_cols
 #ifdef BAND_TO_FULL_BLOCKING
-            ncol = (istep-1)*cwy_blocking + nbw + lc ! absolute column number of householder vector
+            ncol = (istep-1)*cwy_blocking + nbw + lc ! absolute column number of householder Vector
 #else
-            ncol = istep*nbw + lc ! absolute column number of householder vector
+            ncol = istep*nbw + lc ! absolute column number of householder Vector
 #endif
             nrow = ncol - nbw ! absolute number of pivot row
 

src/elpa2/elpa2_trans_ev_tridi_to_band_template.X90

@@ -1486,7 +1486,7 @@
 
         else ! (current_local_n > 1) then
 
-          ! for current_local_n == 1 the one and only HH vector is 0 and not stored in hh_trans_real/complex
+          ! for current_local_n == 1 the one and only HH Vector is 0 and not stored in hh_trans_real/complex
 #if REALCASE == 1
           bcast_buffer(:,1) = CONST_0_0
 #endif

src/elpa2/elpa2_tridiag_band_template.X90

@@ -295,7 +295,7 @@
         call determine_workload(nx, nb, np_rows, limits)
         local_size = limits(my_prow+1) - limits(my_prow)
         ! add to number of householder vectors
-        ! please note: for nx==1 the one and only HH vector is 0 and is neither calculated nor send below!
+        ! please note: for nx==1 the one and only HH Vector is 0 and is neither calculated nor send below!
         if (mod(n-1,np_cols) == my_pcol .and. local_size>0 .and. nx>1) then
           num_hh_vecs = num_hh_vecs + local_size
           num_chunks  = num_chunks+1
@@ -423,7 +423,7 @@
         stop 1
       endif
 
-      hh_cnt(:) = 1 ! The first transfomation vector is always 0 and not calculated at all
+      hh_cnt(:) = 1 ! The first transfomation Vector is always 0 and not calculated at all
       hh_dst(:) = 0 ! PE number for receive
 #ifdef WITH_MPI
       ireq_ab = MPI_REQUEST_NULL
@@ -589,7 +589,7 @@
           endif
         else
           if (na>na_s) then
-            ! Receive Householder vector from previous task, from PE owning subdiagonal
+            ! Receive Householder Vector from previous task, from PE owning subdiagonal
 
 #ifdef WITH_OPENMP
 
@@ -701,7 +701,7 @@
                 hv = hv_t(:,my_thread)
                 tau = tau_t(my_thread)
 
-                ! Store Householder vector for back transformation
+                ! Store Householder Vector for back transformation
 
                 hh_cnt(iblk) = hh_cnt(iblk) + 1
 
@@ -911,7 +911,7 @@
             else
               ! We are at the end of all blocks
 
-              ! Send last HH vector and TAU to next PE if it has been calculated above
+              ! Send last HH Vector and TAU to next PE if it has been calculated above
               ne = na_s + nblocks*nb - (max_threads-1) - 1
               if (istep>=max_threads .and. ne < na) then
 #ifdef WITH_MPI
@@ -937,7 +937,7 @@
 #endif /* WITH_MPI */
               endif
 
-              ! "Send" HH vector and TAU to next OpenMP thread
+              ! "Send" HH Vector and TAU to next OpenMP thread
               do my_thread = max_threads, 2, -1
                 hv_t(:,my_thread) = hv_t(:,my_thread-1)
                 tau_t(my_thread)  = tau_t(my_thread-1)
@@ -953,7 +953,7 @@
           ! The following code is structured in a way to keep waiting times for
           ! other PEs at a minimum, especially if there is only one block.
           ! For this reason, it requests the last column as late as possible
-          ! and sends the Householder vector and the first column as early
+          ! and sends the Householder Vector and the first column as early
           ! as possible.
 
 #endif /* WITH_OPENMP */
@@ -964,7 +964,7 @@
 
             if (ns+n_off>na) exit
 
-            ! Store Householder vector for back transformation
+            ! Store Householder Vector for back transformation
 
             hh_cnt(iblk) = hh_cnt(iblk) + 1
 
@@ -1020,14 +1020,14 @@
             ! The following code is structured in a way to keep waiting times for
             ! other PEs at a minimum, especially if there is only one block.
             ! For this reason, it requests the last column as late as possible
-            ! and sends the Householder vector and the first column as early
+            ! and sends the Householder Vector and the first column as early
             ! as possible.
 #endif /* WITH_OPENMP */
             nc = MIN(na-ns-n_off+1,nb) ! number of columns in diagonal block
             nr = MIN(na-nb-ns-n_off+1,nb) ! rows in subdiagonal block (may be < 0!!!)
                                           ! Note that nr>=0 implies that diagonal block is full (nc==nb)!
 
-            ! Multiply diagonal block and subdiagonal block with Householder vector
+            ! Multiply diagonal block and subdiagonal block with Householder Vector
 
             if (iblk==nblocks .and. nc==nb) then
 
@@ -1312,7 +1312,7 @@
               endif
             endif
 
-            ! Use new HH vector for the next block
+            ! Use new HH Vector for the next block
             hv(:) = hv_new(:)
             tau = tau_new
 

src/elpa2/kernels/elpa2_kernels_real_avx-avx2_2hv_double_precision.c

@@ -156,7 +156,7 @@ void double_hh_trafo_real_avx_avx2_2hv_double(double* q, double* hh, int* pnb, i
 /**
  * Unrolled kernel that computes
  * 24 rows of Q simultaneously, a
- * matrix vector product with two householder
+ * matrix Vector product with two householder
  * vectors + a rank 2 update is performed
  */
  __forceinline void hh_trafo_kernel_24_AVX_2hv_double(double* q, double* hh, int nb, int ldq, int ldh, double s)
@@ -470,7 +470,7 @@ void double_hh_trafo_real_avx_avx2_2hv_double(double* q, double* hh, int* pnb, i
 /**
  * Unrolled kernel that computes
  * 16 rows of Q simultaneously, a
- * matrix vector product with two householder
+ * matrix Vector product with two householder
  * vectors + a rank 2 update is performed
  */
  __forceinline void hh_trafo_kernel_16_AVX_2hv_double(double* q, double* hh, int nb, int ldq, int ldh, double s)
@@ -704,7 +704,7 @@ void double_hh_trafo_real_avx_avx2_2hv_double(double* q, double* hh, int* pnb, i
 /**
  * Unrolled kernel that computes
  * 8 rows of Q simultaneously, a
- * matrix vector product with two householder
+ * matrix Vector product with two householder
  * vectors + a rank 2 update is performed
  */
  __forceinline void hh_trafo_kernel_8_AVX_2hv_double(double* q, double* hh, int nb, int ldq, int ldh, double s)
@@ -858,7 +858,7 @@ void double_hh_trafo_real_avx_avx2_2hv_double(double* q, double* hh, int* pnb, i
 /**
  * Unrolled kernel that computes
  * 4 rows of Q simultaneously, a
- * matrix vector product with two householder
+ * matrix Vector product with two householder
  * vectors + a rank 2 update is performed
  */
  __forceinline void hh_trafo_kernel_4_AVX_2hv_double(double* q, double* hh, int nb, int ldq, int ldh, double s)

src/elpa2/kernels/elpa2_kernels_real_avx-avx2_2hv_single_precision.c

@@ -153,7 +153,7 @@ void double_hh_trafo_real_avx_avx2_2hv_single(float* q, float* hh, int* pnb, int
 /**
  * Unrolled kernel that computes
  * 24 rows of Q simultaneously, a
- * matrix vector product with two householder
+ * matrix Vector product with two householder
  * vectors + a rank 2 update is performed
  */
  __forceinline void hh_trafo_kernel_24_AVX_2hv_single(float* q, float* hh, int nb, int ldq, int ldh, float s)
@@ -470,7 +470,7 @@ void double_hh_trafo_real_avx_avx2_2hv_single(float* q, float* hh, int* pnb, int
 /**
  * Unrolled kernel that computes
  * 16 rows of Q simultaneously, a
- * matrix vector product with two householder
+ * matrix Vector product with two householder
  * vectors + a rank 2 update is performed
  */
  __forceinline void hh_trafo_kernel_16_AVX_2hv_single(float* q, float* hh, int nb, int ldq, int ldh, float s)
@@ -707,7 +707,7 @@ void double_hh_trafo_real_avx_avx2_2hv_single(float* q, float* hh, int* pnb, int
 /**
  * Unrolled kernel that computes
  * 8 rows of Q simultaneously, a
- * matrix vector product with two householder
+ * matrix Vector product with two householder
  * vectors + a rank 2 update is performed
  */
  __forceinline void hh_trafo_kernel_8_AVX_2hv_single(float* q, float* hh, int nb, int ldq, int ldh, float s)
@@ -865,7 +865,7 @@ void double_hh_trafo_real_avx_avx2_2hv_single(float* q, float* hh, int* pnb, int
 /**
  * Unrolled kernel that computes
  * 4 rows of Q simultaneously, a
- * matrix vector product with two householder
+ * matrix Vector product with two householder
  * vectors + a rank 2 update is performed
  */
 __forceinline void hh_trafo_kernel_4_sse_instead_of_avx_2hv_single(float* q, float* hh, int nb, int ldq, int ldh, float s)
@@ -965,7 +965,7 @@ __forceinline void hh_trafo_kernel_4_sse_instead_of_avx_2hv_single(float* q, flo
 /**
  * Unrolled kernel that computes
  * 4 rows of Q simultaneously, a
- * matrix vector product with two householder
+ * matrix Vector product with two householder
  * vectors + a rank 2 update is performed
  */
  __forceinline void hh_trafo_kernel_4_AVX_2hv_single(float* q, float* hh, int nb, int ldq, int ldh, float s)

src/elpa2/kernels/elpa2_kernels_real_avx-avx2_4hv_double_precision.c

@@ -122,7 +122,7 @@ void quad_hh_trafo_real_avx_avx2_4hv_double(double* q, double* hh, int* pnb, int
 	double s_2_4 = hh[(ldh*3)+2];
 	double s_3_4 = hh[(ldh*3)+1];
 
-	// calculate scalar product of first and fourth householder vector
+	// calculate scalar product of first and fourth householder Vector
 	// loop counter = 2
 	s_1_2 += hh[2-1] * hh[(2+ldh)];
 	s_2_3 += hh[(ldh)+2-1] * hh[2+(ldh*2)];
@@ -195,7 +195,7 @@ void quad_hh_trafo_real_avx_avx2_4hv_double(double* q, double* hh, int* pnb, int
 /**
  * Unrolled kernel that computes
  * 12 rows of Q simultaneously, a
- * matrix vector product with two householder
+ * matrix Vector product with two householder
  * vectors + a rank 1 update is performed
  */
 __forceinline void hh_trafo_kernel_12_AVX_4hv_double(double* q, double* hh, int nb, int ldq, int ldh, double s_1_2, double s_1_3, double s_2_3, double s_1_4, double s_2_4, double s_3_4)
@@ -723,7 +723,7 @@ __forceinline void hh_trafo_kernel_12_AVX_4hv_double(double* q, double* hh, int
 /**
  * Unrolled kernel that computes
  * 8 rows of Q simultaneously, a
- * matrix vector product with two householder
+ * matrix Vector product with two householder
  * vectors + a rank 1 update is performed
  */
 __forceinline void hh_trafo_kernel_8_AVX_4hv_double(double* q, double* hh, int nb, int ldq, int ldh, double s_1_2, double s_1_3, double s_2_3, double s_1_4, double s_2_4, double s_3_4)
@@ -1078,7 +1078,7 @@ __forceinline void hh_trafo_kernel_8_AVX_4hv_double(double* q, double* hh, int n
 /**
  * Unrolled kernel that computes
  * 4 rows of Q simultaneously, a
- * matrix vector product with two householder
+ * matrix Vector product with two householder
  * vectors + a rank 1 update is performed
  */
 __forceinline void hh_trafo_kernel_4_AVX_4hv_double(double* q, double* hh, int nb, int ldq, int ldh, double s_1_2, double s_1_3, double s_2_3, double s_1_4, double s_2_4, double s_3_4)

src/elpa2/kernels/elpa2_kernels_real_avx-avx2_4hv_single_precision.c

@@ -108,7 +108,7 @@ void quad_hh_trafo_real_avx_avx2_4hv_single(float* q, float* hh, int* pnb, int*
 	float s_2_4 = hh[(ldh*3)+2];
 	float s_3_4 = hh[(ldh*3)+1];
 
-	// calculate scalar product of first and fourth householder vector
+	// calculate scalar product of first and fourth householder Vector
 	// loop counter = 2
 	s_1_2 += hh[2-1] * hh[(2+ldh)];
 	s_2_3 += hh[(ldh)+2-1] * hh[2+(ldh*2)];
@@ -190,7 +190,7 @@ void quad_hh_trafo_real_avx_avx2_4hv_single(float* q, float* hh, int* pnb, int*
 /**
  * Unrolled kernel that computes
  * 24 rows of Q simultaneously, a
- * matrix vector product with two householder
+ * matrix Vector product with two householder
  * vectors + a rank 1 update is performed
  */
 __forceinline void hh_trafo_kernel_24_AVX_4hv_single(float* q, float* hh, int nb, int ldq, int ldh, float s_1_2, float s_1_3, float s_2_3, float s_1_4, float s_2_4, float s_3_4)
@@ -737,7 +737,7 @@ __forceinline void hh_trafo_kernel_24_AVX_4hv_single(float* q, float* hh, int nb
 /**
  * Unrolled kernel that computes
  * 16 rows of Q simultaneously, a
- * matrix vector product with two householder
+ * matrix Vector product with two householder
  * vectors + a rank 1 update is performed
  */
 __forceinline void hh_trafo_kernel_16_AVX_4hv_single(float* q, float* hh, int nb, int ldq, int ldh, float s_1_2, float s_1_3, float s_2_3, float s_1_4, float s_2_4, float s_3_4)
@@ -1092,7 +1092,7 @@ __forceinline void hh_trafo_kernel_16_AVX_4hv_single(float* q, float* hh, int nb
 /**
  * Unrolled kernel that computes
  * 8 rows of Q simultaneously, a
- * matrix vector product with two householder
+ * matrix Vector product with two householder
  * vectors + a rank 1 update is performed
  */
 __forceinline void hh_trafo_kernel_8_AVX_4hv_single(float* q, float* hh, int nb, int ldq, int ldh, float s_1_2, float s_1_3, float s_2_3, float s_1_4, float s_2_4, float s_3_4)
@@ -1447,7 +1447,7 @@ __forceinline void hh_trafo_kernel_8_AVX_4hv_single(float* q, float* hh, int nb,
 /**
  * Unrolled kernel that computes
  * 4 rows of Q simultaneously, a
- * matrix vector product with two householder
+ * matrix Vector product with two householder
  * vectors + a rank 1 update is performed
  */
 __forceinline void hh_trafo_kernel_4_AVX_4hv_single(float* q, float* hh, int nb, int ldq, int ldh, float s_1_2, float s_1_3, float s_2_3, float s_1_4, float s_2_4, float s_3_4)

src/elpa2/kernels/elpa2_kernels_real_avx-avx2_6hv_double_precision.c

@@ -147,7 +147,7 @@ void hexa_hh_trafo_real_avx_avx2_6hv_double(double* q, double* hh, int* pnb, int
 	scalarprods[13] = hh[(ldh*5)+2];
 	scalarprods[14] = hh[(ldh*5)+1];
 
-	// calculate scalar product of first and fourth householder vector
+	// calculate scalar product of first and fourth householder Vector
 	// loop counter = 2
 	scalarprods[0] += hh[1] * hh[(2+ldh)];
 	scalarprods[2] += hh[(ldh)+1] * hh[2+(ldh*2)];
@@ -317,7 +317,7 @@ void hexa_hh_trafo_real_avx_avx2_6hv_double(double* q, double* hh, int* pnb, int
 //	scalarprods[13] = hh[(ldh*5)+2];
 //	scalarprods[14] = hh[(ldh*5)+1];
 //
-//	// calculate scalar product of first and fourth householder vector
+//	// calculate scalar product of first and fourth householder Vector
 //	// loop counter = 2
 //	scalarprods[0] += hh[1] * hh[(2+ldh)];
 //	scalarprods[2] += hh[(ldh)+1] * hh[2+(ldh*2)];
@@ -415,7 +415,7 @@ void hexa_hh_trafo_real_avx_avx2_6hv_double(double* q, double* hh, int* pnb, int
 /**
  * Unrolled kernel that computes
  * 8 rows of Q simultaneously, a
- * matrix vector product with two householder
+ * matrix Vector product with two householder
  * vectors + a rank 1 update is performed
  */
 __forceinline void hh_trafo_kernel_8_AVX_6hv_double(double* q, double* hh, int nb, int ldq, int ldh, double* scalarprods)
@@ -1188,7 +1188,7 @@ __forceinline void hh_trafo_kernel_8_AVX_6hv_double(double* q, double* hh, int n
 /**
  * Unrolled kernel that computes
  * 4 rows of Q simultaneously, a
- * matrix vector product with two householder
+ * matrix Vector product with two householder
  * vectors + a rank 1 update is performed
  */
 __forceinline void hh_trafo_kernel_4_AVX_6hv_double(double* q, double* hh, int nb, int ldq, int ldh, double* scalarprods)

src/elpa2/kernels/elpa2_kernels_real_avx-avx2_6hv_single_precision.c

@@ -117,7 +117,7 @@ void hexa_hh_trafo_real_avx_avx2_6hv_single(float* q, float* hh, int* pnb, int*
 	scalarprods[13] = hh[(ldh*5)+2];
 	scalarprods[14] = hh[(ldh*5)+1];
 
-	// calculate scalar product of first and fourth householder vector
+	// calculate scalar product of first and fourth householder Vector
 	// loop counter = 2
 	scalarprods[0] += hh[1] * hh[(2+ldh)];
 	scalarprods[2] += hh[(ldh)+1] * hh[2+(ldh*2)];
@@ -215,7 +215,7 @@ void hexa_hh_trafo_real_avx_avx2_6hv_single(float* q, float* hh, int* pnb, int*
 /**
  * Unrolled kernel that computes
  * 16 rows of Q simultaneously, a
- * matrix vector product with two householder
+ * matrix Vector product with two householder
  * vectors + a rank 1 update is performed
  */
 __forceinline void hh_trafo_kernel_16_AVX_6hv_single(float* q, float* hh, int nb, int ldq, int ldh, float* scalarprods)
@@ -988,7 +988,7 @@ __forceinline void hh_trafo_kernel_16_AVX_6hv_single(float* q, float* hh, int nb
 /**
  * Unrolled kernel that computes
  * 4 rows of Q simultaneously, a
- * matrix vector product with two householder
+ * matrix Vector product with two householder
  * vectors + a rank 1 upsate is performed
  */
 __forceinline void hh_trafo_kernel_4_AVX_6hv_single(float* q, float* hh, int nb, int ldq, int ldh, float* scalarprods)
@@ -1559,7 +1559,7 @@ __forceinline void hh_trafo_kernel_4_AVX_6hv_single(float* q, float* hh, int nb,
 /**
  * Unrolled kernel that computes
  * 8 rows of Q simultaneously, a
- * matrix vector product with two householder
+ * matrix Vector product with two householder
  * vectors + a rank 1 update is performed
  */
 __forceinline void hh_trafo_kernel_8_AVX_6hv_single(float* q, float* hh, int nb, int ldq, int ldh, float* scalarprods)

src/elpa2/kernels/elpa2_kernels_real_avx512_2hv_double_precision.c

@@ -123,7 +123,7 @@ void double_hh_trafo_real_avx512_2hv_double(double* q, double* hh, int* pnb, int
 /**
  * Unrolled kernel that computes
  * 32 rows of Q simultaneously, a
- * matrix vector product with two householder
+ * matrix Vector product with two householder
  * vectors + a rank 2 update is performed
  */
  __forceinline void hh_trafo_kernel_32_AVX512_2hv_double(double* q, double* hh, int nb, int ldq, int ldh, double s)
@@ -282,7 +282,7 @@ void double_hh_trafo_real_avx512_2hv_double(double* q, double* hh, int* pnb, int
 /**
  * Unrolled kernel that computes
  * 24 rows of Q simultaneously, a
- * matrix vector product with two householder
+ * matrix Vector product with two householder
  * vectors + a rank 2 update is performed
  */
  __forceinline void hh_trafo_kernel_24_AVX512_2hv_double(double* q, double* hh, int nb, int ldq, int ldh, double s)
@@ -414,7 +414,7 @@ void double_hh_trafo_real_avx512_2hv_double(double* q, double* hh, int* pnb, int
 /**
  * Unrolled kernel that computes
  * 16 rows of Q simultaneously, a
- * matrix vector product with two householder
+ * matrix Vector product with two householder
  * vectors + a rank 2 update is performed
  */
  __forceinline void hh_trafo_kernel_16_AVX512_2hv_double(double* q, double* hh, int nb, int ldq, int ldh, double s)
@@ -521,7 +521,7 @@ void double_hh_trafo_real_avx512_2hv_double(double* q, double* hh, int* pnb, int
 /**
  * Unrolled kernel that computes
  * 8 rows of Q simultaneously, a
- * matrix vector product with two householder
+ * matrix Vector product with two householder
  * vectors + a rank 2 update is performed
  */
  __forceinline void hh_trafo_kernel_8_AVX512_2hv_double(double* q, double* hh, int nb, int ldq, int ldh, double s)
@@ -606,7 +606,7 @@ void double_hh_trafo_real_avx512_2hv_double(double* q, double* hh, int* pnb, int
 /**
  * Unrolled kernel that computes
  * 4 rows of Q simultaneously, a
- * matrix vector product with two householder
+ * matrix Vector product with two householder
  * vectors + a rank 2 update is performed
  */
  __forceinline void hh_trafo_kernel_4_AVX512_2hv_double(double* q, double* hh, int nb, int ldq, int ldh, double s)

src/elpa2/kernels/elpa2_kernels_real_avx512_2hv_single_precision.c

@@ -126,7 +126,7 @@ void double_hh_trafo_real_avx512_2hv_single(float* q, float* hh, int* pnb, int*
 /**
  * Unrolled kernel that computes
  * 64 rows of Q simultaneously, a