diff --git a/internal/ceres/context_impl.cc b/internal/ceres/context_impl.cc
index 20fe5cb..2b9d9cc 100644
--- a/internal/ceres/context_impl.cc
+++ b/internal/ceres/context_impl.cc
@@ -1,5 +1,5 @@
 // Ceres Solver - A fast non-linear least squares minimizer
-// Copyright 2018 Google Inc. All rights reserved.
+// Copyright 2023 Google Inc. All rights reserved.
 // http://ceres-solver.org/
 //
 // Redistribution and use in source and binary forms, with or without
@@ -30,13 +30,167 @@
 
 #include "ceres/context_impl.h"
 
-namespace ceres {
-namespace internal {
+#include <string>
+
+#include "ceres/internal/config.h"
+#include "ceres/stringprintf.h"
+#include "ceres/wall_time.h"
+
+#ifndef CERES_NO_CUDA
+#include "cublas_v2.h"
+#include "cuda_runtime.h"
+#include "cusolverDn.h"
+#endif  // CERES_NO_CUDA
+
+namespace ceres::internal {
+
+ContextImpl::ContextImpl() = default;
+
+#ifndef CERES_NO_CUDA
+void ContextImpl::TearDown() {
+  if (cusolver_handle_ != nullptr) {
+    cusolverDnDestroy(cusolver_handle_);
+    cusolver_handle_ = nullptr;
+  }
+  if (cublas_handle_ != nullptr) {
+    cublasDestroy(cublas_handle_);
+    cublas_handle_ = nullptr;
+  }
+  if (cusparse_handle_ != nullptr) {
+    cusparseDestroy(cusparse_handle_);
+    cusparse_handle_ = nullptr;
+  }
+  for (auto& s : streams_) {
+    if (s != nullptr) {
+      cudaStreamDestroy(s);
+      s = nullptr;
+    }
+  }
+  is_cuda_initialized_ = false;
+}
+
+std::string ContextImpl::CudaConfigAsString() const {
+  return ceres::internal::StringPrintf(
+      "======================= CUDA Device Properties ======================\n"
+      "Cuda version              : %d.%d\n"
+      "Device ID                 : %d\n"
+      "Device name               : %s\n"
+      "Total GPU memory          : %6.f MiB\n"
+      "GPU memory available      : %6.f MiB\n"
+      "Compute capability        : %d.%d\n"
+      "Warp size                 : %d\n"
+      "Max threads per block     : %d\n"
+      "Max threads per dim       : %d %d %d\n"
+      "Max grid size             : %d %d %d\n"
+      "Multiprocessor count      : %d\n"
+      "cudaMallocAsync supported : %s\n"
+      "====================================================================",
+      cuda_version_major_,
+      cuda_version_minor_,
+      gpu_device_id_in_use_,
+      gpu_device_properties_.name,
+      gpu_device_properties_.totalGlobalMem / 1024.0 / 1024.0,
+      GpuMemoryAvailable() / 1024.0 / 1024.0,
+      gpu_device_properties_.major,
+      gpu_device_properties_.minor,
+      gpu_device_properties_.warpSize,
+      gpu_device_properties_.maxThreadsPerBlock,
+      gpu_device_properties_.maxThreadsDim[0],
+      gpu_device_properties_.maxThreadsDim[1],
+      gpu_device_properties_.maxThreadsDim[2],
+      gpu_device_properties_.maxGridSize[0],
+      gpu_device_properties_.maxGridSize[1],
+      gpu_device_properties_.maxGridSize[2],
+      gpu_device_properties_.multiProcessorCount,
+      // In CUDA 12.0.0+ cudaDeviceProp has field memoryPoolsSupported, but it
+      // is not available in older versions
+      is_cuda_memory_pools_supported_ ? "Yes" : "No");
+}
+
+size_t ContextImpl::GpuMemoryAvailable() const {
+  size_t free, total;
+  cudaMemGetInfo(&free, &total);
+  return free;
+}
+
+bool ContextImpl::InitCuda(std::string* message) {
+  if (is_cuda_initialized_) {
+    return true;
+  }
+  CHECK_EQ(cudaGetDevice(&gpu_device_id_in_use_), cudaSuccess);
+  int cuda_version;
+  CHECK_EQ(cudaRuntimeGetVersion(&cuda_version), cudaSuccess);
+  cuda_version_major_ = cuda_version / 1000;
+  cuda_version_minor_ = (cuda_version % 1000) / 10;
+  CHECK_EQ(
+      cudaGetDeviceProperties(&gpu_device_properties_, gpu_device_id_in_use_),
+      cudaSuccess);
+#if CUDART_VERSION >= 11020
+  int is_cuda_memory_pools_supported;
+  CHECK_EQ(cudaDeviceGetAttribute(&is_cuda_memory_pools_supported,
+                                  cudaDevAttrMemoryPoolsSupported,
+                                  gpu_device_id_in_use_),
+           cudaSuccess);
+  is_cuda_memory_pools_supported_ = is_cuda_memory_pools_supported == 1;
+#endif
+  VLOG(3) << "\n" << CudaConfigAsString();
+  EventLogger event_logger("InitCuda");
+  if (cublasCreate(&cublas_handle_) != CUBLAS_STATUS_SUCCESS) {
+    *message =
+        "CUDA initialization failed because cuBLAS::cublasCreate failed.";
+    cublas_handle_ = nullptr;
+    return false;
+  }
+  event_logger.AddEvent("cublasCreate");
+  if (cusolverDnCreate(&cusolver_handle_) != CUSOLVER_STATUS_SUCCESS) {
+    *message =
+        "CUDA initialization failed because cuSolverDN::cusolverDnCreate "
+        "failed.";
+    TearDown();
+    return false;
+  }
+  event_logger.AddEvent("cusolverDnCreate");
+  if (cusparseCreate(&cusparse_handle_) != CUSPARSE_STATUS_SUCCESS) {
+    *message =
+        "CUDA initialization failed because cuSPARSE::cusparseCreate failed.";
+    TearDown();
+    return false;
+  }
+  event_logger.AddEvent("cusparseCreate");
+  for (auto& s : streams_) {
+    if (cudaStreamCreateWithFlags(&s, cudaStreamNonBlocking) != cudaSuccess) {
+      *message =
+          "CUDA initialization failed because CUDA::cudaStreamCreateWithFlags "
+          "failed.";
+      TearDown();
+      return false;
+    }
+  }
+  event_logger.AddEvent("cudaStreamCreateWithFlags");
+  if (cusolverDnSetStream(cusolver_handle_, DefaultStream()) !=
+          CUSOLVER_STATUS_SUCCESS ||
+      cublasSetStream(cublas_handle_, DefaultStream()) !=
+          CUBLAS_STATUS_SUCCESS ||
+      cusparseSetStream(cusparse_handle_, DefaultStream()) !=
+          CUSPARSE_STATUS_SUCCESS) {
+    *message = "CUDA initialization failed because SetStream failed.";
+    TearDown();
+    return false;
+  }
+  event_logger.AddEvent("SetStream");
+  is_cuda_initialized_ = true;
+  return true;
+}
+#endif  // CERES_NO_CUDA
+
+ContextImpl::~ContextImpl() {
+#ifndef CERES_NO_CUDA
+  TearDown();
+#endif  // CERES_NO_CUDA
+}
 
 void ContextImpl::EnsureMinimumThreads(int num_threads) {
-#ifdef CERES_USE_CXX_THREADS
   thread_pool.Resize(num_threads);
-#endif  // CERES_USE_CXX_THREADS
 }
-}  // namespace internal
-}  // namespace ceres
+
+}  // namespace ceres::internal