Add cuda files

test/cuda_jamfile

@@ -0,0 +1,31 @@
+# Copyright 2024 Matt Borland
+# Distributed under the Boost Software License, Version 1.0.
+# https://www.boost.org/LICENSE_1_0.txt
+
+import testing ;
+import ../../config/checks/config : requires ;
+
+project : requirements
+    [ requires cxx14_decltype_auto cxx14_generic_lambdas cxx14_return_type_deduction cxx14_variable_templates cxx14_constexpr ]
+    ;
+
+# Autodiff Tests
+run test_autodiff_1.cpp ;
+
+# Tools Tests
+run test_polynomial.cpp ;
+
+# Distributions
+run test_arcsine.cpp ;
+run test_arcsine_cdf_double.cu ;
+run test_arcsine_cdf_float.cu ;
+run test_arcsine_pdf_double.cu ;
+run test_arcsine_pdf_float.cu ;
+run test_arcsine_quan_double.cu ;
+run test_arcsine_quan_float.cu ;
+run test_binomial.cpp ;
+
+# Special Functions
+# run test_beta_simple.cpp ;
+run test_beta_double.cu ;
+run test_beta_float.cu ;

test/test_arcsine_cdf_double.cu

@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/arcsine.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::arcsine_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::arcsine_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}

test/test_arcsine_cdf_float.cu

@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/arcsine.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::arcsine_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::arcsine_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}

test/test_arcsine_pdf_double.cu

@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/arcsine.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::arcsine_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::arcsine_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}

test/test_arcsine_pdf_float.cu

@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/arcsine.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::arcsine_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::arcsine_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}

test/test_arcsine_quan_double.cu

@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/arcsine.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::arcsine_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::arcsine_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}

test/test_arcsine_quan_float.cu

@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/arcsine.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::arcsine_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::arcsine_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}

test/test_beta_double.cu

@@ -0,0 +1,132 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/array.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type * in2, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::beta(in1[i], in2[i]);
+    }
+}
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "beta_med_data.ipp"
+#include "beta_small_data.ipp"
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+    // Consolidate the test data:
+    std::vector<float_type> v1, v2;
+
+    for(unsigned i = 0; i < beta_med_data.size(); ++i)
+    {
+       v1.push_back(beta_med_data[i][0]);
+       v2.push_back(beta_med_data[i][1]);
+    }
+    for(unsigned i = 0; i < beta_small_data.size(); ++i)
+    {
+       v1.push_back(beta_small_data[i][0]);
+       v2.push_back(beta_small_data[i][1]);
+    }
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        int table_id = i % v1.size();
+        input_vector1[i] = v1[table_id];
+        input_vector2[i] = v2[table_id];
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::beta(input_vector1[i], input_vector2[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 300)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
+
+

test/test_beta_float.cu

@@ -0,0 +1,130 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/array.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type * in2, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::beta(in1[i], in2[i]);
+    }
+}
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "beta_med_data.ipp"
+#include "beta_small_data.ipp"
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+    // Consolidate the test data:
+    std::vector<float_type> v1, v2;
+
+    for(unsigned i = 0; i < beta_med_data.size(); ++i)
+    {
+       v1.push_back(beta_med_data[i][0]);
+       v2.push_back(beta_med_data[i][1]);
+    }
+    for(unsigned i = 0; i < beta_small_data.size(); ++i)
+    {
+       v1.push_back(beta_small_data[i][0]);
+       v2.push_back(beta_small_data[i][1]);
+    }
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        int table_id = i % v1.size();
+        input_vector1[i] = v1[table_id];
+        input_vector2[i] = v2[table_id];
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::beta(input_vector1[i], input_vector2[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 300)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
+