diff --git a/internal/ceres/CMakeLists.txt b/internal/ceres/CMakeLists.txt
index 56e88cb..018c5b4 100644
--- a/internal/ceres/CMakeLists.txt
+++ b/internal/ceres/CMakeLists.txt
@@ -72,6 +72,7 @@
     covariance.cc
     covariance_impl.cc
     cxsparse.cc
+    dense_cholesky.cc
     dense_normal_cholesky_solver.cc
     dense_qr_solver.cc
     dense_sparse_matrix.cc
@@ -453,6 +454,7 @@
   ceres_test(covariance)
   ceres_test(cubic_interpolation)
   ceres_test(dense_linear_solver)
+  ceres_test(dense_cholesky)
   ceres_test(dense_sparse_matrix)
   ceres_test(detect_structure)
   ceres_test(dogleg_strategy)
diff --git a/internal/ceres/dense_cholesky.cc b/internal/ceres/dense_cholesky.cc
new file mode 100644
index 0000000..1037ad3
--- /dev/null
+++ b/internal/ceres/dense_cholesky.cc
@@ -0,0 +1,175 @@
+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2022 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: sameeragarwal@google.com (Sameer Agarwal)
+
+#include "ceres/dense_cholesky.h"
+
+#include <algorithm>
+#include <memory>
+
+#ifndef CERES_NO_LAPACK
+
+// C interface to the LAPACK Cholesky factorization and triangular solve.
+extern "C" void dpotrf_(
+    const char* uplo, const int* n, double* a, const int* lda, int* info);
+
+extern "C" void dpotrs_(const char* uplo,
+                        const int* n,
+                        const int* nrhs,
+                        const double* a,
+                        const int* lda,
+                        double* b,
+                        const int* ldb,
+                        int* info);
+#endif
+
+namespace ceres {
+namespace internal {
+
+std::unique_ptr<DenseCholesky> DenseCholesky::Create(
+    const LinearSolver::Options& options) {
+  std::unique_ptr<DenseCholesky> dense_cholesky;
+
+  switch (options.dense_linear_algebra_library_type) {
+    case EIGEN:
+      dense_cholesky = std::make_unique<EigenDenseCholesky>();
+      break;
+
+    case LAPACK:
+#ifndef CERES_NO_LAPACK
+      dense_cholesky = std::make_unique<LAPACKDenseCholesky>();
+      break;
+#else
+      LOG(FATAL) << "Ceres was compiled without support for LAPACK.";
+#endif
+
+    default:
+      LOG(FATAL) << "Unknown dense linear algebra library type : "
+                 << DenseLinearAlgebraLibraryTypeToString(
+                        options.dense_linear_algebra_library_type);
+  }
+  return dense_cholesky;
+}
+
+LinearSolverTerminationType DenseCholesky::FactorAndSolve(
+    int num_cols,
+    double* lhs,
+    const double* rhs,
+    double* solution,
+    std::string* message) {
+  LinearSolverTerminationType termination_type =
+      Factorize(num_cols, lhs, message);
+  if (termination_type == LINEAR_SOLVER_SUCCESS) {
+    termination_type = Solve(rhs, solution, message);
+  }
+  return termination_type;
+}
+
+LinearSolverTerminationType EigenDenseCholesky::Factorize(
+    int num_cols, double* lhs, std::string* message) {
+  Eigen::Map<Eigen::MatrixXd> m(lhs, num_cols, num_cols);
+  llt_.reset(new LLTType(m));
+  if (llt_->info() != Eigen::Success) {
+    *message = "Eigen failure. Unable to perform dense Cholesky factorization.";
+    return LINEAR_SOLVER_FAILURE;
+  }
+
+  *message = "Success.";
+  return LINEAR_SOLVER_SUCCESS;
+}
+
+LinearSolverTerminationType EigenDenseCholesky::Solve(const double* rhs,
+                                                      double* solution,
+                                                      std::string* message) {
+  if (llt_->info() != Eigen::Success) {
+    *message = "Eigen failure. Unable to perform dense Cholesky factorization.";
+    return LINEAR_SOLVER_FAILURE;
+  }
+
+  VectorRef(solution, llt_->cols()) =
+      llt_->solve(ConstVectorRef(rhs, llt_->cols()));
+  *message = "Success.";
+  return LINEAR_SOLVER_SUCCESS;
+}
+
+LinearSolverTerminationType LAPACKDenseCholesky::Factorize(
+    int num_cols, double* lhs, std::string* message) {
+  lhs_ = lhs;
+  num_cols_ = num_cols;
+
+  const char uplo = 'L';
+  int info = 0;
+  dpotrf_(&uplo, &num_cols_, lhs_, &num_cols_, &info);
+
+  if (info < 0) {
+    termination_type_ = LINEAR_SOLVER_FATAL_ERROR;
+    LOG(FATAL) << "Congratulations, you found a bug in Ceres."
+               << "Please report it."
+               << "LAPACK::dpotrf fatal error."
+               << "Argument: " << -info << " is invalid.";
+  } else if (info > 0) {
+    termination_type_ = LINEAR_SOLVER_FAILURE;
+    *message = StringPrintf(
+        "LAPACK::dpotrf numerical failure. "
+        "The leading minor of order %d is not positive definite.",
+        info);
+  } else {
+    termination_type_ = LINEAR_SOLVER_SUCCESS;
+    *message = "Success.";
+  }
+  return termination_type_;
+}
+
+LinearSolverTerminationType LAPACKDenseCholesky::Solve(const double* rhs,
+                                                       double* solution,
+                                                       std::string* message) {
+  const char uplo = 'L';
+  const int nrhs = 1;
+  int info = 0;
+
+  std::copy_n(rhs, num_cols_, solution);
+  dpotrs_(
+      &uplo, &num_cols_, &nrhs, lhs_, &num_cols_, solution, &num_cols_, &info);
+
+  if (info < 0) {
+    termination_type_ = LINEAR_SOLVER_FATAL_ERROR;
+    LOG(FATAL) << "Congratulations, you found a bug in Ceres."
+               << "Please report it."
+               << "LAPACK::dpotrs fatal error."
+               << "Argument: " << -info << " is invalid.";
+  }
+
+  *message = "Success";
+  termination_type_ = LINEAR_SOLVER_SUCCESS;
+
+  return termination_type_;
+}
+
+}  // namespace internal
+}  // namespace ceres
diff --git a/internal/ceres/dense_cholesky.h b/internal/ceres/dense_cholesky.h
new file mode 100644
index 0000000..0859c68
--- /dev/null
+++ b/internal/ceres/dense_cholesky.h
@@ -0,0 +1,133 @@
+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2022 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: sameeragarwal@google.com (Sameer Agarwal)
+
+#ifndef CERES_INTERNAL_DENSE_CHOLESKY_H_
+#define CERES_INTERNAL_DENSE_CHOLESKY_H_
+
+// This include must come before any #ifndef check on Ceres compile options.
+// clang-format off
+#include "ceres/internal/port.h"
+// clang-format on
+
+#include <memory>
+
+#include "Eigen/Dense"
+#include "ceres/linear_solver.h"
+#include "glog/logging.h"
+
+namespace ceres {
+namespace internal {
+
+// An interface that abstracts away the internal details of various dense linear
+// algebra libraries and offers a simple API for solving dense symmetric
+// positive definite linear systems using a Cholesky factorization.
+class CERES_EXPORT_INTERNAL DenseCholesky {
+ public:
+  static std::unique_ptr<DenseCholesky> Create(
+      const LinearSolver::Options& options);
+
+  virtual ~DenseCholesky() = default;
+
+  // Computes the Cholesky factorization of the given matrix.
+  //
+  // The input matrix lhs is assumed to be a column-major num_cols x num_cols
+  // matrix, that is symmetric positive definite with its lower triangular part
+  // containing the left hand side of the linear system being solved.
+  //
+  // The input matrix lhs may be modified by the implementation to store the
+  // factorization, irrespective of whether the factorization succeeds or not.
+  // As a result it is the user's responsibility to ensure that lhs is valid
+  // when Solve is called.
+  virtual LinearSolverTerminationType Factorize(int num_cols,
+                                                double* lhs,
+                                                std::string* message) = 0;
+
+  // Computes the solution to the equation
+  //
+  // lhs * solution = rhs
+  //
+  // Calling Solve without calling Factorize is undefined behaviour. It is the
+  // user's responsibility to ensure that the input matrix lhs passed to
+  // Factorize has not been freed/modified when Solve is called.
+  virtual LinearSolverTerminationType Solve(const double* rhs,
+                                            double* solution,
+                                            std::string* message) = 0;
+
+  // Convenience method which combines a call to Factorize and Solve. Solve is
+  // only called if Factorize returns LINEAR_SOLVER_SUCCESS.
+  //
+  // The input matrix lhs may be modified by the implementation to store the
+  // factorization, irrespective of whether the method succeeds or not. It is
+  // the user's responsibility to ensure that lhs is valid if and when Solve is
+  // called again after this call.
+  LinearSolverTerminationType FactorAndSolve(int num_cols,
+                                             double* lhs,
+                                             const double* rhs,
+                                             double* solution,
+                                             std::string* message);
+};
+
+class CERES_EXPORT_INTERNAL EigenDenseCholesky : public DenseCholesky {
+ public:
+  ~EigenDenseCholesky() override = default;
+
+  LinearSolverTerminationType Factorize(int num_cols,
+                                        double* lhs,
+                                        std::string* message) override;
+  LinearSolverTerminationType Solve(const double* rhs,
+                                    double* solution,
+                                    std::string* message) override;
+
+ private:
+  using LLTType = Eigen::LLT<Eigen::Ref<Eigen::MatrixXd>, Eigen::Lower>;
+  std::unique_ptr<LLTType> llt_;
+};
+
+class CERES_EXPORT_INTERNAL LAPACKDenseCholesky : public DenseCholesky {
+ public:
+  ~LAPACKDenseCholesky() override = default;
+
+  LinearSolverTerminationType Factorize(int num_cols,
+                                        double* lhs,
+                                        std::string* message) override;
+  LinearSolverTerminationType Solve(const double* rhs,
+                                    double* solution,
+                                    std::string* message) override;
+
+ private:
+  double* lhs_ = nullptr;
+  int num_cols_ = -1;
+  LinearSolverTerminationType termination_type_ = LINEAR_SOLVER_FATAL_ERROR;
+};
+
+}  // namespace internal
+}  // namespace ceres
+
+#endif  // CERES_INTERNAL_DENSE_CHOLESKY_H_
diff --git a/internal/ceres/dense_cholesky_test.cc b/internal/ceres/dense_cholesky_test.cc
new file mode 100644
index 0000000..1b0ee65
--- /dev/null
+++ b/internal/ceres/dense_cholesky_test.cc
@@ -0,0 +1,107 @@
+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2022 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: sameeragarwal@google.com (Sameer Agarwal)
+
+#include "ceres/dense_cholesky.h"
+
+#include <memory>
+#include <numeric>
+#include <vector>
+
+#include "Eigen/Dense"
+#include "ceres/internal/eigen.h"
+#include "ceres/linear_solver.h"
+#include "glog/logging.h"
+#include "gmock/gmock.h"
+#include "gtest/gtest.h"
+
+namespace ceres {
+namespace internal {
+
+typedef DenseLinearAlgebraLibraryType Param;
+
+std::string ParamInfoToString(testing::TestParamInfo<Param> info) {
+  return DenseLinearAlgebraLibraryTypeToString(info.param);
+}
+
+class DenseCholeskyTest : public ::testing::TestWithParam<Param> {};
+
+TEST_P(DenseCholeskyTest, FactorAndSolve) {
+  // TODO(sameeragarwal): Convert these tests into type parameterized tests so
+  // that we can test the single and double precision solvers.
+
+  using Scalar = double;
+  using MatrixType = Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic>;
+  using VectorType = Eigen::Matrix<Scalar, Eigen::Dynamic, 1>;
+
+  LinearSolver::Options options;
+  options.dense_linear_algebra_library_type = GetParam();
+  std::unique_ptr<DenseCholesky> dense_cholesky =
+      DenseCholesky::Create(options);
+
+  const int kNumTrials = 10;
+  const int kMinNumCols = 1;
+  const int kMaxNumCols = 10;
+
+  for (int num_cols = kMinNumCols; num_cols < kMaxNumCols; ++num_cols) {
+    for (int trial = 0; trial < kNumTrials; ++trial) {
+      const MatrixType a = MatrixType::Random(num_cols, num_cols);
+      MatrixType lhs = a.transpose() * a;
+      lhs += VectorType::Ones(num_cols).asDiagonal();
+      Vector x = VectorType::Random(num_cols);
+      Vector rhs = lhs * x;
+      Vector actual = Vector::Random(num_cols);
+
+      LinearSolver::Summary summary;
+      summary.termination_type = dense_cholesky->FactorAndSolve(
+          num_cols, lhs.data(), rhs.data(), actual.data(), &summary.message);
+      EXPECT_EQ(summary.termination_type, LINEAR_SOLVER_SUCCESS);
+      EXPECT_NEAR((x - actual).norm() / x.norm(),
+                  0.0,
+                  std::numeric_limits<double>::epsilon() * 10)
+          << "\nexpected: " << x.transpose()
+          << "\nactual  : " << actual.transpose();
+    }
+  }
+}
+
+#ifndef CERES_NO_LAPACK
+INSTANTIATE_TEST_SUITE_P(_,
+                         DenseCholeskyTest,
+                         ::testing::Values(EIGEN, LAPACK),
+                         ParamInfoToString);
+#else
+INSTANTIATE_TEST_SUITE_P(_,
+                         DenseCholeskyTest,
+                         ::testing::Values(EIGEN),
+                         ParamInfoToString);
+#endif
+
+}  // namespace internal
+}  // namespace ceres
diff --git a/internal/ceres/dense_linear_solver_test.cc b/internal/ceres/dense_linear_solver_test.cc
index 3929a6f..419ec3e 100644
--- a/internal/ceres/dense_linear_solver_test.cc
+++ b/internal/ceres/dense_linear_solver_test.cc
@@ -105,7 +105,9 @@
   const double residual = (expected_normal_rhs - actual_normal_rhs).norm() /
                           expected_normal_rhs.norm();
 
-  EXPECT_NEAR(residual, 0.0, 10 * std::numeric_limits<double>::epsilon());
+  EXPECT_NEAR(residual, 0.0, 10 * std::numeric_limits<double>::epsilon())
+      << "\nexpected: " << expected_normal_rhs.transpose()
+      << "\nactual: " << actual_normal_rhs.transpose();
 }
 
 namespace {
diff --git a/internal/ceres/dense_normal_cholesky_solver.cc b/internal/ceres/dense_normal_cholesky_solver.cc
index 51c6390..73e5bf8 100644
--- a/internal/ceres/dense_normal_cholesky_solver.cc
+++ b/internal/ceres/dense_normal_cholesky_solver.cc
@@ -36,7 +36,6 @@
 #include "ceres/blas.h"
 #include "ceres/dense_sparse_matrix.h"
 #include "ceres/internal/eigen.h"
-#include "ceres/lapack.h"
 #include "ceres/linear_solver.h"
 #include "ceres/types.h"
 #include "ceres/wall_time.h"
@@ -46,25 +45,13 @@
 
 DenseNormalCholeskySolver::DenseNormalCholeskySolver(
     const LinearSolver::Options& options)
-    : options_(options) {}
+    : options_(options), cholesky_(DenseCholesky::Create(options_)) {}
 
 LinearSolver::Summary DenseNormalCholeskySolver::SolveImpl(
     DenseSparseMatrix* A,
     const double* b,
     const LinearSolver::PerSolveOptions& per_solve_options,
     double* x) {
-  if (options_.dense_linear_algebra_library_type == EIGEN) {
-    return SolveUsingEigen(A, b, per_solve_options, x);
-  } else {
-    return SolveUsingLAPACK(A, b, per_solve_options, x);
-  }
-}
-
-LinearSolver::Summary DenseNormalCholeskySolver::SolveUsingEigen(
-    DenseSparseMatrix* A,
-    const double* b,
-    const LinearSolver::PerSolveOptions& per_solve_options,
-    double* x) {
   EventLogger event_logger("DenseNormalCholeskySolver::Solve");
 
   const int num_rows = A->num_rows();
@@ -94,64 +81,12 @@
 
   LinearSolver::Summary summary;
   summary.num_iterations = 1;
-  summary.termination_type = LINEAR_SOLVER_SUCCESS;
-  Eigen::LLT<Matrix, Eigen::Upper> llt =
-      lhs.selfadjointView<Eigen::Upper>().llt();
+  summary.termination_type = cholesky_->FactorAndSolve(
+      num_cols, lhs.data(), rhs.data(), x, &summary.message);
+  event_logger.AddEvent("FactorAndSolve");
 
-  if (llt.info() != Eigen::Success) {
-    summary.termination_type = LINEAR_SOLVER_FAILURE;
-    summary.message = "Eigen LLT decomposition failed.";
-  } else {
-    summary.termination_type = LINEAR_SOLVER_SUCCESS;
-    summary.message = "Success.";
-  }
-
-  VectorRef(x, num_cols) = llt.solve(rhs);
-  event_logger.AddEvent("Solve");
   return summary;
 }
 
-LinearSolver::Summary DenseNormalCholeskySolver::SolveUsingLAPACK(
-    DenseSparseMatrix* A,
-    const double* b,
-    const LinearSolver::PerSolveOptions& per_solve_options,
-    double* x) {
-  EventLogger event_logger("DenseNormalCholeskySolver::Solve");
-
-  if (per_solve_options.D != NULL) {
-    // Temporarily append a diagonal block to the A matrix, but undo
-    // it before returning the matrix to the user.
-    A->AppendDiagonal(per_solve_options.D);
-  }
-
-  const int num_cols = A->num_cols();
-  Matrix lhs(num_cols, num_cols);
-  event_logger.AddEvent("Setup");
-
-  // lhs = A'A
-  //
-  // Note: This is a bit delicate, it assumes that the stride on this
-  // matrix is the same as the number of rows.
-  BLAS::SymmetricRankKUpdate(
-      A->num_rows(), num_cols, A->values(), true, 1.0, 0.0, lhs.data());
-
-  if (per_solve_options.D != NULL) {
-    // Undo the modifications to the matrix A.
-    A->RemoveDiagonal();
-  }
-
-  // TODO(sameeragarwal): Replace this with a gemv call for true blasness.
-  //   rhs = A'b
-  VectorRef(x, num_cols) =
-      A->matrix().transpose() * ConstVectorRef(b, A->num_rows());
-  event_logger.AddEvent("Product");
-
-  LinearSolver::Summary summary;
-  summary.num_iterations = 1;
-  summary.termination_type = LAPACK::SolveInPlaceUsingCholesky(
-      num_cols, lhs.data(), x, &summary.message);
-  event_logger.AddEvent("Solve");
-  return summary;
-}
 }  // namespace internal
 }  // namespace ceres
diff --git a/internal/ceres/dense_normal_cholesky_solver.h b/internal/ceres/dense_normal_cholesky_solver.h
index 68ea611..d81dee9 100644
--- a/internal/ceres/dense_normal_cholesky_solver.h
+++ b/internal/ceres/dense_normal_cholesky_solver.h
@@ -34,6 +34,7 @@
 #ifndef CERES_INTERNAL_DENSE_NORMAL_CHOLESKY_SOLVER_H_
 #define CERES_INTERNAL_DENSE_NORMAL_CHOLESKY_SOLVER_H_
 
+#include "ceres/dense_cholesky.h"
 #include "ceres/linear_solver.h"
 
 namespace ceres {
@@ -84,19 +85,8 @@
       const LinearSolver::PerSolveOptions& per_solve_options,
       double* x) final;
 
-  LinearSolver::Summary SolveUsingLAPACK(
-      DenseSparseMatrix* A,
-      const double* b,
-      const LinearSolver::PerSolveOptions& per_solve_options,
-      double* x);
-
-  LinearSolver::Summary SolveUsingEigen(
-      DenseSparseMatrix* A,
-      const double* b,
-      const LinearSolver::PerSolveOptions& per_solve_options,
-      double* x);
-
   const LinearSolver::Options options_;
+  std::unique_ptr<DenseCholesky> cholesky_;
 };
 
 }  // namespace internal
diff --git a/internal/ceres/lapack.cc b/internal/ceres/lapack.cc
index a159ec7..7ce00a5 100644
--- a/internal/ceres/lapack.cc
+++ b/internal/ceres/lapack.cc
@@ -35,18 +35,6 @@
 #include "glog/logging.h"
 
 #ifndef CERES_NO_LAPACK
-// C interface to the LAPACK Cholesky factorization and triangular solve.
-extern "C" void dpotrf_(char* uplo, int* n, double* a, int* lda, int* info);
-
-extern "C" void dpotrs_(char* uplo,
-                        int* n,
-                        int* nrhs,
-                        double* a,
-                        int* lda,
-                        double* b,
-                        int* ldb,
-                        int* info);
-
 extern "C" void dgels_(char* uplo,
                        int* m,
                        int* n,
@@ -63,52 +51,6 @@
 namespace ceres {
 namespace internal {
 
-LinearSolverTerminationType LAPACK::SolveInPlaceUsingCholesky(
-    int num_rows,
-    const double* in_lhs,
-    double* rhs_and_solution,
-    std::string* message) {
-#ifdef CERES_NO_LAPACK
-  LOG(FATAL) << "Ceres was built without a BLAS library.";
-  return LINEAR_SOLVER_FATAL_ERROR;
-#else
-  char uplo = 'L';
-  int n = num_rows;
-  int info = 0;
-  int nrhs = 1;
-  double* lhs = const_cast<double*>(in_lhs);
-
-  dpotrf_(&uplo, &n, lhs, &n, &info);
-  if (info < 0) {
-    LOG(FATAL) << "Congratulations, you found a bug in Ceres."
-               << "Please report it."
-               << "LAPACK::dpotrf fatal error."
-               << "Argument: " << -info << " is invalid.";
-    return LINEAR_SOLVER_FATAL_ERROR;
-  }
-
-  if (info > 0) {
-    *message = StringPrintf(
-        "LAPACK::dpotrf numerical failure. "
-        "The leading minor of order %d is not positive definite.",
-        info);
-    return LINEAR_SOLVER_FAILURE;
-  }
-
-  dpotrs_(&uplo, &n, &nrhs, lhs, &n, rhs_and_solution, &n, &info);
-  if (info < 0) {
-    LOG(FATAL) << "Congratulations, you found a bug in Ceres."
-               << "Please report it."
-               << "LAPACK::dpotrs fatal error."
-               << "Argument: " << -info << " is invalid.";
-    return LINEAR_SOLVER_FATAL_ERROR;
-  }
-
-  *message = "Success";
-  return LINEAR_SOLVER_SUCCESS;
-#endif
-}
-
 int LAPACK::EstimateWorkSizeForQR(int num_rows, int num_cols) {
 #ifdef CERES_NO_LAPACK
   LOG(FATAL) << "Ceres was built without a LAPACK library.";
diff --git a/internal/ceres/schur_complement_solver.cc b/internal/ceres/schur_complement_solver.cc
index 65e7854..866fd67 100644
--- a/internal/ceres/schur_complement_solver.cc
+++ b/internal/ceres/schur_complement_solver.cc
@@ -46,7 +46,6 @@
 #include "ceres/conjugate_gradients_solver.h"
 #include "ceres/detect_structure.h"
 #include "ceres/internal/eigen.h"
-#include "ceres/lapack.h"
 #include "ceres/linear_solver.h"
 #include "ceres/sparse_cholesky.h"
 #include "ceres/triplet_sparse_matrix.h"
@@ -201,8 +200,8 @@
   summary.termination_type = LINEAR_SOLVER_SUCCESS;
   summary.message = "Success.";
 
-  const BlockRandomAccessDenseMatrix* m =
-      down_cast<const BlockRandomAccessDenseMatrix*>(lhs());
+  BlockRandomAccessDenseMatrix* m =
+      down_cast<BlockRandomAccessDenseMatrix*>(mutable_lhs());
   const int num_rows = m->num_rows();
 
   // The case where there are no f blocks, and the system is block
@@ -212,26 +211,8 @@
   }
 
   summary.num_iterations = 1;
-
-  if (options().dense_linear_algebra_library_type == EIGEN) {
-    Eigen::LLT<Matrix, Eigen::Upper> llt =
-        ConstMatrixRef(m->values(), num_rows, num_rows)
-            .selfadjointView<Eigen::Upper>()
-            .llt();
-    if (llt.info() != Eigen::Success) {
-      summary.termination_type = LINEAR_SOLVER_FAILURE;
-      summary.message =
-          "Eigen failure. Unable to perform dense Cholesky factorization.";
-      return summary;
-    }
-
-    VectorRef(solution, num_rows) = llt.solve(ConstVectorRef(rhs(), num_rows));
-  } else {
-    VectorRef(solution, num_rows) = ConstVectorRef(rhs(), num_rows);
-    summary.termination_type = LAPACK::SolveInPlaceUsingCholesky(
-        num_rows, m->values(), solution, &summary.message);
-  }
-
+  summary.termination_type = cholesky_->FactorAndSolve(
+      num_rows, m->mutable_values(), rhs(), solution, &summary.message);
   return summary;
 }
 
@@ -377,8 +358,8 @@
     preconditioner_.reset(new BlockRandomAccessDiagonalMatrix(blocks_));
   }
 
-  BlockRandomAccessSparseMatrix* sc = down_cast<BlockRandomAccessSparseMatrix*>(
-      const_cast<BlockRandomAccessMatrix*>(lhs()));
+  BlockRandomAccessSparseMatrix* sc =
+      down_cast<BlockRandomAccessSparseMatrix*>(mutable_lhs());
 
   // Extract block diagonal from the Schur complement to construct the
   // schur_jacobi preconditioner.
diff --git a/internal/ceres/schur_complement_solver.h b/internal/ceres/schur_complement_solver.h
index 3bfa22f..60af043 100644
--- a/internal/ceres/schur_complement_solver.h
+++ b/internal/ceres/schur_complement_solver.h
@@ -40,6 +40,7 @@
 #include "ceres/block_random_access_matrix.h"
 #include "ceres/block_sparse_matrix.h"
 #include "ceres/block_structure.h"
+#include "ceres/dense_cholesky.h"
 #include "ceres/internal/port.h"
 #include "ceres/linear_solver.h"
 #include "ceres/schur_eliminator.h"
@@ -130,10 +131,12 @@
  protected:
   const LinearSolver::Options& options() const { return options_; }
 
-  const BlockRandomAccessMatrix* lhs() const { return lhs_.get(); }
   void set_lhs(BlockRandomAccessMatrix* lhs) { lhs_.reset(lhs); }
-  const double* rhs() const { return rhs_.get(); }
+  const BlockRandomAccessMatrix* lhs() const { return lhs_.get(); }
+  BlockRandomAccessMatrix* mutable_lhs() { return lhs_.get(); }
+
   void set_rhs(double* rhs) { rhs_.reset(rhs); }
+  const double* rhs() const { return rhs_.get(); }
 
  private:
   virtual void InitStorage(const CompressedRowBlockStructure* bs) = 0;
@@ -152,7 +155,8 @@
 class DenseSchurComplementSolver : public SchurComplementSolver {
  public:
   explicit DenseSchurComplementSolver(const LinearSolver::Options& options)
-      : SchurComplementSolver(options) {}
+      : SchurComplementSolver(options),
+        cholesky_(DenseCholesky::Create(options)) {}
   DenseSchurComplementSolver(const DenseSchurComplementSolver&) = delete;
   void operator=(const DenseSchurComplementSolver&) = delete;
 
@@ -163,6 +167,8 @@
   LinearSolver::Summary SolveReducedLinearSystem(
       const LinearSolver::PerSolveOptions& per_solve_options,
       double* solution) final;
+
+  std::unique_ptr<DenseCholesky> cholesky_;
 };
 
 // Sparse Cholesky factorization based solver.
diff --git a/internal/ceres/sparse_cholesky.h b/internal/ceres/sparse_cholesky.h
index a6af6b2..39670d5 100644
--- a/internal/ceres/sparse_cholesky.h
+++ b/internal/ceres/sparse_cholesky.h
@@ -104,11 +104,10 @@
   // Convenience method which combines a call to Factorize and
   // Solve. Solve is only called if Factorize returns
   // LINEAR_SOLVER_SUCCESS.
-  virtual LinearSolverTerminationType FactorAndSolve(
-      CompressedRowSparseMatrix* lhs,
-      const double* rhs,
-      double* solution,
-      std::string* message);
+  LinearSolverTerminationType FactorAndSolve(CompressedRowSparseMatrix* lhs,
+                                             const double* rhs,
+                                             double* solution,
+                                             std::string* message);
 };
 
 class IterativeRefiner;