diff --git a/internal/ceres/small_blas.h b/internal/ceres/small_blas.h
index 264ac53..34b4ec7 100644
--- a/internal/ceres/small_blas.h
+++ b/internal/ceres/small_blas.h
@@ -38,6 +38,7 @@
 #include "ceres/internal/port.h"
 #include "ceres/internal/eigen.h"
 #include "glog/logging.h"
+#include "small_blas_generic.h"
 
 namespace ceres {
 namespace internal {
@@ -89,6 +90,26 @@
       B, num_row_b, num_col_b,                                          \
       C, start_row_c, start_col_c, row_stride_c, col_stride_c);
 
+#define CERES_GEMM_STORE_SINGLE(p, index, value)                        \
+  if (kOperation > 0) {                                                 \
+    p[index] += value;                                                  \
+  } else if (kOperation < 0) {                                          \
+    p[index] -= value;                                                  \
+  } else {                                                              \
+    p[index] = value;                                                   \
+  }
+
+#define CERES_GEMM_STORE_PAIR(p, index, v1, v2)                         \
+  if (kOperation > 0) {                                                 \
+    p[index] += v1;                                                     \
+    p[index + 1] += v2;                                                 \
+  } else if (kOperation < 0) {                                          \
+    p[index] -= v1;                                                     \
+    p[index + 1] -= v2;                                                 \
+  } else {                                                              \
+    p[index] = v1;                                                      \
+    p[index + 1] = v2;                                                  \
+  }
 
 // For the matrix-matrix functions below, there are three variants for
 // each functionality. Foo, FooNaive and FooEigen. Foo is the one to
@@ -160,24 +181,64 @@
   const int NUM_COL_C = NUM_COL_B;
   DCHECK_LE(start_row_c + NUM_ROW_C, row_stride_c);
   DCHECK_LE(start_col_c + NUM_COL_C, col_stride_c);
+  const int span = 4;
 
-  for (int row = 0; row < NUM_ROW_C; ++row) {
-    for (int col = 0; col < NUM_COL_C; ++col) {
+  // Calculate the remainder part first.
+
+  // Process the last odd column if present.
+  if (NUM_COL_C & 1) {
+    int col = NUM_COL_C - 1;
+    const double* pa = &A[0];
+    for (int row = 0; row < NUM_ROW_C; ++row, pa += NUM_COL_A) {
+      const double* pb = &B[col];
       double tmp = 0.0;
-      for (int k = 0; k < NUM_COL_A; ++k) {
-        tmp += A[row * NUM_COL_A + k] * B[k * NUM_COL_B + col];
+      for (int k = 0; k < NUM_COL_A; ++k, pb += NUM_COL_B) {
+        tmp += pa[k] * pb[0];
       }
 
       const int index = (row + start_row_c) * col_stride_c + start_col_c + col;
-      if (kOperation > 0) {
-        C[index] += tmp;
-      } else if (kOperation < 0) {
-        C[index] -= tmp;
-      } else {
-        C[index] = tmp;
-      }
+      CERES_GEMM_STORE_SINGLE(C, index, tmp);
+    }
+
+    // Return directly for efficiency of extremely small matrix multiply.
+    if (NUM_COL_C == 1) {
+      return;
     }
   }
+
+  // Process the couple columns in remainder if present.
+  if (NUM_COL_C & 2) {
+    int col = NUM_COL_C & (int)(~(span - 1)) ;
+    const double* pa = &A[0];
+    for (int row = 0; row < NUM_ROW_C; ++row, pa += NUM_COL_A) {
+      const double* pb = &B[col];
+      double tmp1 = 0.0, tmp2 = 0.0;
+      for (int k = 0; k < NUM_COL_A; ++k, pb += NUM_COL_B) {
+        double av = pa[k];
+        tmp1 += av * pb[0];
+        tmp2 += av * pb[1];
+      }
+
+      const int index = (row + start_row_c) * col_stride_c + start_col_c + col;
+      CERES_GEMM_STORE_PAIR(C, index, tmp1, tmp2);
+    }
+
+    // Return directly for efficiency of extremely small matrix multiply.
+    if (NUM_COL_C < span) {
+      return;
+    }
+  }
+
+  // Calculate the main part with multiples of 4.
+  int col_m = NUM_COL_C & (int)(~(span - 1));
+  for (int col = 0; col < col_m; col += span) {
+    for (int row = 0; row < NUM_ROW_C; ++row) {
+      const int index = (row + start_row_c) * col_stride_c + start_col_c + col;
+      MMM_mat1x4(NUM_COL_A, &A[row * NUM_COL_A],
+                 &B[col], NUM_COL_B, &C[index], kOperation);
+    }
+  }
+
 }
 
 CERES_GEMM_BEGIN(MatrixMatrixMultiply) {
@@ -220,24 +281,68 @@
   const int NUM_COL_C = NUM_COL_B;
   DCHECK_LE(start_row_c + NUM_ROW_C, row_stride_c);
   DCHECK_LE(start_col_c + NUM_COL_C, col_stride_c);
+  const int span = 4;
 
-  for (int row = 0; row < NUM_ROW_C; ++row) {
-    for (int col = 0; col < NUM_COL_C; ++col) {
+  // Process the remainder part first.
+
+  // Process the last odd column if present.
+  if (NUM_COL_C & 1) {
+    int col = NUM_COL_C - 1;
+    for (int row = 0; row < NUM_ROW_C; ++row) {
+      const double* pa = &A[row];
+      const double* pb = &B[col];
       double tmp = 0.0;
       for (int k = 0; k < NUM_ROW_A; ++k) {
-        tmp += A[k * NUM_COL_A + row] * B[k * NUM_COL_B + col];
+        tmp += pa[0] * pb[0];
+        pa += NUM_COL_A;
+        pb += NUM_COL_B;
       }
 
       const int index = (row + start_row_c) * col_stride_c + start_col_c + col;
-      if (kOperation > 0) {
-        C[index]+= tmp;
-      } else if (kOperation < 0) {
-        C[index]-= tmp;
-      } else {
-        C[index]= tmp;
-      }
+      CERES_GEMM_STORE_SINGLE(C, index, tmp);
+    }
+
+    // Return directly for efficiency of extremely small matrix multiply.
+    if (NUM_COL_C == 1) {
+      return;
     }
   }
+
+  // Process the couple columns in remainder if present.
+  if (NUM_COL_C & 2) {
+    int col = NUM_COL_C & (int)(~(span - 1)) ;
+    for (int row = 0; row < NUM_ROW_C; ++row) {
+      const double* pa = &A[row];
+      const double* pb = &B[col];
+      double tmp1 = 0.0, tmp2 = 0.0;
+      for (int k = 0; k < NUM_ROW_A; ++k) {
+        double av = *pa;
+        tmp1 += av * pb[0];
+        tmp2 += av * pb[1];
+        pa += NUM_COL_A;
+        pb += NUM_COL_B;
+      }
+
+      const int index = (row + start_row_c) * col_stride_c + start_col_c + col;
+      CERES_GEMM_STORE_PAIR(C, index, tmp1, tmp2);
+    }
+
+    // Return directly for efficiency of extremely small matrix multiply.
+    if (NUM_COL_C < span) {
+      return;
+    }
+  }
+
+  // Process the main part with multiples of 4.
+  int col_m = NUM_COL_C & (int)(~(span - 1));
+  for (int col = 0; col < col_m; col += span) {
+    for (int row = 0; row < NUM_ROW_C; ++row) {
+      const int index = (row + start_row_c) * col_stride_c + start_col_c + col;
+      MTM_mat1x4(NUM_ROW_A, &A[row], NUM_COL_A,
+                 &B[col], NUM_COL_B, &C[index], kOperation);
+    }
+  }
+
 }
 
 CERES_GEMM_BEGIN(MatrixTransposeMatrixMultiply) {
@@ -301,21 +406,54 @@
 
   const int NUM_ROW_A = (kRowA != Eigen::Dynamic ? kRowA : num_row_a);
   const int NUM_COL_A = (kColA != Eigen::Dynamic ? kColA : num_col_a);
+  const int span = 4;
 
-  for (int row = 0; row < NUM_ROW_A; ++row) {
+  // Calculate the remainder part first.
+
+  // Process the last odd row if present.
+  if (NUM_ROW_A & 1) {
+    int row  = NUM_ROW_A - 1;
+    const double* pa = &A[row * NUM_COL_A];
+    const double* pb = &b[0];
     double tmp = 0.0;
     for (int col = 0; col < NUM_COL_A; ++col) {
-      tmp += A[row * NUM_COL_A + col] * b[col];
+      tmp += (*pa++) * (*pb++);
     }
+    CERES_GEMM_STORE_SINGLE(c, row, tmp);
 
-    if (kOperation > 0) {
-      c[row] += tmp;
-    } else if (kOperation < 0) {
-      c[row] -= tmp;
-    } else {
-      c[row] = tmp;
+    // Return directly for efficiency of extremely small matrix multiply.
+    if (NUM_ROW_A == 1) {
+      return;
     }
   }
+
+  // Process the couple rows in remainder if present.
+  if (NUM_ROW_A & 2) {
+    int row = NUM_ROW_A & (int)(~(span - 1));
+    const double* pa1 = &A[row * NUM_COL_A];
+    const double* pa2 = pa1 + NUM_COL_A;
+    const double* pb = &b[0];
+    double tmp1 = 0.0, tmp2 = 0.0;
+    for (int col = 0; col < NUM_ROW_A; ++col) {
+      double bv = *pb++;
+      tmp1 += *(pa1++) * bv;
+      tmp2 += *(pa2++) * bv;
+    }
+    CERES_GEMM_STORE_PAIR(c, row, tmp1, tmp2);
+
+    // Return directly for efficiency of extremely small matrix multiply.
+    if (NUM_ROW_A < span) {
+      return;
+    }
+  }
+
+  // Calculate the main part with multiples of 4.
+  int row_m = NUM_ROW_A & (int)(~(span - 1));
+  for (int row = 0; row < row_m; row += span) {
+    MVM_mat4x1(NUM_COL_A, &A[row * NUM_COL_A], NUM_COL_A,
+               &b[0], &c[row], kOperation);
+  }
+
 #endif  // CERES_NO_CUSTOM_BLAS
 }
 
@@ -352,21 +490,55 @@
 
   const int NUM_ROW_A = (kRowA != Eigen::Dynamic ? kRowA : num_row_a);
   const int NUM_COL_A = (kColA != Eigen::Dynamic ? kColA : num_col_a);
+  const int span = 4;
 
-  for (int row = 0; row < NUM_COL_A; ++row) {
+  // Calculate the remainder part first.
+
+  // Process the last odd column if present.
+  if (NUM_COL_A & 1) {
+    int row  = NUM_COL_A - 1;
+    const double* pa = &A[row];
+    const double* pb = &b[0];
     double tmp = 0.0;
     for (int col = 0; col < NUM_ROW_A; ++col) {
-      tmp += A[col * NUM_COL_A + row] * b[col];
+      tmp += *pa * (*pb++);
+      pa += NUM_COL_A;
     }
+    CERES_GEMM_STORE_SINGLE(c, row, tmp);
 
-    if (kOperation > 0) {
-      c[row] += tmp;
-    } else if (kOperation < 0) {
-      c[row] -= tmp;
-    } else {
-      c[row] = tmp;
+    // Return directly for efficiency of extremely small matrix multiply.
+    if (NUM_COL_A == 1) {
+      return;
     }
   }
+
+  // Process the couple columns in remainder if present.
+  if (NUM_COL_A & 2) {
+    int row = NUM_COL_A & (int)(~(span - 1));
+    const double* pa = &A[row];
+    const double* pb = &b[0];
+    double tmp1 = 0.0, tmp2 = 0.0;
+    for (int col = 0; col < NUM_ROW_A; ++col) {
+      double bv = *pb++;
+      tmp1 += *(pa    ) * bv;
+      tmp2 += *(pa + 1) * bv;
+      pa += NUM_COL_A;
+    }
+    CERES_GEMM_STORE_PAIR(c, row, tmp1, tmp2);
+
+    // Return directly for efficiency of extremely small matrix multiply.
+    if (NUM_COL_A < span) {
+      return;
+    }
+  }
+
+  // Calculate the main part with multiples of 4.
+  int row_m = NUM_COL_A & (int)(~(span - 1));
+  for (int row = 0; row < row_m; row += span) {
+    MTV_mat4x1(NUM_ROW_A, &A[row], NUM_COL_A,
+               &b[0], &c[row], kOperation);
+  }
+
 #endif  // CERES_NO_CUSTOM_BLAS
 }
 
@@ -374,6 +546,8 @@
 #undef CERES_GEMM_EIGEN_HEADER
 #undef CERES_GEMM_NAIVE_HEADER
 #undef CERES_CALL_GEMM
+#undef CERES_GEMM_STORE_SINGLE
+#undef CERES_GEMM_STORE_PAIR
 
 }  // namespace internal
 }  // namespace ceres
diff --git a/internal/ceres/small_blas_generic.h b/internal/ceres/small_blas_generic.h
new file mode 100644
index 0000000..978c5d5
--- /dev/null
+++ b/internal/ceres/small_blas_generic.h
@@ -0,0 +1,315 @@
+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2018 Google Inc. All rights reserved.
+// http://ceres-solver.org/
+//
+// Redistribution and use in source and binary forms, with or without
+// modification, are permitted provided that the following conditions are met:
+//
+// * Redistributions of source code must retain the above copyright notice,
+//   this list of conditions and the following disclaimer.
+// * Redistributions in binary form must reproduce the above copyright notice,
+//   this list of conditions and the following disclaimer in the documentation
+//   and/or other materials provided with the distribution.
+// * Neither the name of Google Inc. nor the names of its contributors may be
+//   used to endorse or promote products derived from this software without
+//   specific prior written permission.
+//
+// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
+// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
+// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
+// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
+// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
+// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
+// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
+// POSSIBILITY OF SUCH DAMAGE.
+//
+// Author: yangfan34@lenovo.com (Lenovo Research Device+ Lab - Shanghai)
+//
+// Optimization for simple blas functions used in the Schur Eliminator.
+// These are fairly basic implementations which already yield a significant
+// speedup in the eliminator performance.
+
+#ifndef CERES_INTERNAL_SMALL_BLAS_GENERIC_H_
+#define CERES_INTERNAL_SMALL_BLAS_GENERIC_H_
+
+namespace ceres {
+namespace internal {
+
+// The following macros are used to share code
+#define CERES_GEMM_OPT_NAIVE_HEADER              \
+  double c0 = 0.0;                               \
+  double c1 = 0.0;                               \
+  double c2 = 0.0;                               \
+  double c3 = 0.0;                               \
+  const double* pa = a;                          \
+  const double* pb = b;                          \
+  const int span = 4;                            \
+  int col_r = col_a & (span - 1);                \
+  int col_m = col_a - col_r;
+
+#define CERES_GEMM_OPT_STORE_MAT1X4              \
+  if (kOperation > 0) {                          \
+    *c++ += c0;                                  \
+    *c++ += c1;                                  \
+    *c++ += c2;                                  \
+    *c++ += c3;                                  \
+  } else if (kOperation < 0) {                   \
+    *c++ -= c0;                                  \
+    *c++ -= c1;                                  \
+    *c++ -= c2;                                  \
+    *c++ -= c3;                                  \
+  } else {                                       \
+    *c++ = c0;                                   \
+    *c++ = c1;                                   \
+    *c++ = c2;                                   \
+    *c++ = c3;                                   \
+  }
+
+// Matrix-Matrix Multiplication
+// Figure out 1x4 of Matrix C in one batch
+//
+// c op a * B;
+// where op can be +=, -=, or =, indicated by kOperation.
+//
+//  Matrix C              Matrix A                   Matrix B
+//
+//  C0, C1, C2, C3   op   A0, A1, A2, A3, ...    *   B0, B1, B2, B3
+//                                                   B4, B5, B6, B7
+//                                                   B8, B9, Ba, Bb
+//                                                   Bc, Bd, Be, Bf
+//                                                   . , . , . , .
+//                                                   . , . , . , .
+//                                                   . , . , . , .
+//
+// unroll for loops
+// utilize the data resided in cache
+// NOTE: col_a means the columns of A
+static inline void MMM_mat1x4(const int col_a,
+                              const double* a,
+                              const double* b,
+                              const int col_stride_b,
+                              double* c,
+                              const int kOperation) {
+  CERES_GEMM_OPT_NAIVE_HEADER
+  double av = 0.0;
+  int bi = 0;
+
+#define CERES_GEMM_OPT_MMM_MAT1X4_MUL  \
+  av = pa[k];                          \
+  pb = b + bi;                         \
+  c0 += av * *pb++;                    \
+  c1 += av * *pb++;                    \
+  c2 += av * *pb++;                    \
+  c3 += av * *pb++;                    \
+  bi += col_stride_b;                  \
+  k++;
+
+  for (int k = 0; k < col_m;) {
+    CERES_GEMM_OPT_MMM_MAT1X4_MUL
+    CERES_GEMM_OPT_MMM_MAT1X4_MUL
+    CERES_GEMM_OPT_MMM_MAT1X4_MUL
+    CERES_GEMM_OPT_MMM_MAT1X4_MUL
+  }
+
+  for (int k = col_m; k < col_a;) {
+    CERES_GEMM_OPT_MMM_MAT1X4_MUL
+  }
+
+  CERES_GEMM_OPT_STORE_MAT1X4
+
+#undef CERES_GEMM_OPT_MMM_MAT1X4_MUL
+}
+
+// Matrix Transpose-Matrix multiplication
+// Figure out 1x4 of Matrix C in one batch
+//
+// c op a' * B;
+// where op can be +=, -=, or = indicated by kOperation.
+//
+//                        Matrix A
+//
+//                        A0
+//                        A1
+//                        A2
+//                        A3
+//                        .
+//                        .
+//                        .
+//
+//  Matrix C              Matrix A'                  Matrix B
+//
+//  C0, C1, C2, C3   op   A0, A1, A2, A3, ...    *   B0, B1, B2, B3
+//                                                   B4, B5, B6, B7
+//                                                   B8, B9, Ba, Bb
+//                                                   Bc, Bd, Be, Bf
+//                                                   . , . , . , .
+//                                                   . , . , . , .
+//                                                   . , . , . , .
+//
+// unroll for loops
+// utilize the data resided in cache
+// NOTE: col_a means the columns of A'
+static inline void MTM_mat1x4(const int col_a,
+                              const double* a,
+                              const int col_stride_a,
+                              const double* b,
+                              const int col_stride_b,
+                              double* c,
+                              const int kOperation) {
+  CERES_GEMM_OPT_NAIVE_HEADER
+  double av = 0.0;
+  int ai = 0;
+  int bi = 0;
+
+#define CERES_GEMM_OPT_MTM_MAT1X4_MUL  \
+  av = pa[ai];                         \
+  pb = b + bi;                         \
+  c0 += av * *pb++;                    \
+  c1 += av * *pb++;                    \
+  c2 += av * *pb++;                    \
+  c3 += av * *pb++;                    \
+  ai += col_stride_a;                  \
+  bi += col_stride_b;
+
+  for (int k = 0; k < col_m; k += span) {
+    CERES_GEMM_OPT_MTM_MAT1X4_MUL
+    CERES_GEMM_OPT_MTM_MAT1X4_MUL
+    CERES_GEMM_OPT_MTM_MAT1X4_MUL
+    CERES_GEMM_OPT_MTM_MAT1X4_MUL
+  }
+
+  for (int k = col_m; k < col_a; k++) {
+    CERES_GEMM_OPT_MTM_MAT1X4_MUL
+  }
+
+  CERES_GEMM_OPT_STORE_MAT1X4
+
+#undef CERES_GEMM_OPT_MTM_MAT1X4_MUL
+}
+
+// Matrix-Vector Multiplication
+// Figure out 4x1 of vector c in one batch
+//
+// c op A * b;
+// where op can be +=, -=, or =, indicated by kOperation.
+//
+//  Vector c              Matrix A                   Vector b
+//
+//  C0               op   A0, A1, A2, A3, ...    *   B0
+//  C1                    A4, A5, A6, A7, ...        B1
+//  C2                    A8, A9, Aa, Ab, ...        B2
+//  C3                    Ac, Ad, Ae, Af, ...        B3
+//                                                   .
+//                                                   .
+//                                                   .
+//
+// unroll for loops
+// utilize the data resided in cache
+// NOTE: col_a means the columns of A
+static inline void MVM_mat4x1(const int col_a,
+                              const double* a,
+                              const int col_stride_a,
+                              const double* b,
+                              double* c,
+                              const int kOperation) {
+  CERES_GEMM_OPT_NAIVE_HEADER
+  double bv = 0.0;
+
+#define CERES_GEMM_OPT_MVM_MAT4X1_MUL              \
+  bv = *pb;                                        \
+  c0 += *(pa                   ) * bv;             \
+  c1 += *(pa + col_stride_a    ) * bv;             \
+  c2 += *(pa + col_stride_a * 2) * bv;             \
+  c3 += *(pa + col_stride_a * 3) * bv;             \
+  pa++;                                            \
+  pb++;
+
+  for (int k = 0; k < col_m; k += span) {
+    CERES_GEMM_OPT_MVM_MAT4X1_MUL
+    CERES_GEMM_OPT_MVM_MAT4X1_MUL
+    CERES_GEMM_OPT_MVM_MAT4X1_MUL
+    CERES_GEMM_OPT_MVM_MAT4X1_MUL
+  }
+
+  for (int k = col_m; k < col_a; k++) {
+    CERES_GEMM_OPT_MVM_MAT4X1_MUL
+  }
+
+  CERES_GEMM_OPT_STORE_MAT1X4
+
+#undef CERES_GEMM_OPT_MVM_MAT4X1_MUL
+}
+
+// Matrix Transpose-Vector multiplication
+// Figure out 4x1 of vector c in one batch
+//
+// c op A' * b;
+// where op can be +=, -=, or =, indicated by kOperation.
+//
+//                        Matrix A
+//
+//                        A0, A4, A8, Ac
+//                        A1, A5, A9, Ad
+//                        A2, A6, Aa, Ae
+//                        A3, A7, Ab, Af
+//                        . , . , . , .
+//                        . , . , . , .
+//                        . , . , . , .
+//
+//  Vector c              Matrix A'                  Vector b
+//
+//  C0               op   A0, A1, A2, A3, ...    *   B0
+//  C1                    A4, A5, A6, A7, ...        B1
+//  C2                    A8, A9, Aa, Ab, ...        B2
+//  C3                    Ac, Ad, Ae, Af, ...        B3
+//                                                   .
+//                                                   .
+//                                                   .
+//
+// unroll for loops
+// utilize the data resided in cache
+// NOTE: col_a means the columns of A'
+static inline void MTV_mat4x1(const int col_a,
+                              const double* a,
+                              const int col_stride_a,
+                              const double* b,
+                              double* c,
+                              const int kOperation) {
+  CERES_GEMM_OPT_NAIVE_HEADER
+  double bv = 0.0;
+
+#define CERES_GEMM_OPT_MTV_MAT4X1_MUL  \
+  bv = *pb;                            \
+  c0 += *(pa    ) * bv;                \
+  c1 += *(pa + 1) * bv;                \
+  c2 += *(pa + 2) * bv;                \
+  c3 += *(pa + 3) * bv;                \
+  pa += col_stride_a;                  \
+  pb++;
+
+  for (int k = 0; k < col_m; k += span) {
+    CERES_GEMM_OPT_MTV_MAT4X1_MUL
+    CERES_GEMM_OPT_MTV_MAT4X1_MUL
+    CERES_GEMM_OPT_MTV_MAT4X1_MUL
+    CERES_GEMM_OPT_MTV_MAT4X1_MUL
+  }
+
+  for (int k = col_m; k < col_a; k++) {
+    CERES_GEMM_OPT_MTV_MAT4X1_MUL
+  }
+
+  CERES_GEMM_OPT_STORE_MAT1X4
+
+#undef CERES_GEMM_OPT_MTV_MAT4X1_MUL
+}
+
+#undef CERES_GEMM_OPT_NAIVE_HEADER
+#undef CERES_GEMM_OPT_STORE_MAT1X4
+
+}  // namespace internal
+}  // namespace ceres
+
+#endif  // CERES_INTERNAL_SMALL_BLAS_GENERIC_H_