// ----------------------------------------------------------------------------
// -                        Open3D: www.open3d.org                            -
// ----------------------------------------------------------------------------
// Copyright (c) 2018-2024 www.open3d.org
// SPDX-License-Identifier: MIT
// ----------------------------------------------------------------------------

#pragma once

#include <cstdint>
#include <type_traits>

#include "open3d/core/Device.h"
#include "open3d/utility/Logging.h"
#include "open3d/utility/Overload.h"
#include "open3d/utility/Parallel.h"
#include "open3d/utility/Preprocessor.h"

#ifdef __CUDACC__
#include <cuda.h>
#include <cuda_runtime.h>

#include "open3d/core/CUDAUtils.h"
#endif

namespace open3d {
namespace core {

#ifdef __CUDACC__

static constexpr int64_t OPEN3D_PARFOR_BLOCK = 128;
static constexpr int64_t OPEN3D_PARFOR_THREAD = 4;

/// Calls f(n) with the "grid-stride loops" pattern.
template <int64_t block_size, int64_t thread_size, typename func_t>
__global__ void ElementWiseKernel_(int64_t n, func_t f) {
    int64_t items_per_block = block_size * thread_size;
    int64_t idx = blockIdx.x * items_per_block + threadIdx.x;
#pragma unroll
    for (int64_t i = 0; i < thread_size; ++i) {
        if (idx < n) {
            f(idx);
            idx += block_size;
        }
    }
}

/// Run a function in parallel on CUDA.
template <typename func_t>
void ParallelForCUDA_(const Device& device, int64_t n, const func_t& func) {
    if (device.GetType() != Device::DeviceType::CUDA) {
        utility::LogError("ParallelFor for CUDA cannot run on device {}.",
                          device.ToString());
    }
    if (n == 0) {
        return;
    }

    CUDAScopedDevice scoped_device(device);
    int64_t items_per_block = OPEN3D_PARFOR_BLOCK * OPEN3D_PARFOR_THREAD;
    int64_t grid_size = (n + items_per_block - 1) / items_per_block;

    ElementWiseKernel_<OPEN3D_PARFOR_BLOCK, OPEN3D_PARFOR_THREAD>
            <<<grid_size, OPEN3D_PARFOR_BLOCK, 0, core::cuda::GetStream()>>>(
                    n, func);
    OPEN3D_GET_LAST_CUDA_ERROR("ParallelFor failed.");
}

#else

/// Run a function in parallel on CPU.
template <typename func_t>
void ParallelForCPU_(const Device& device, int64_t n, const func_t& func) {
    if (!device.IsCPU()) {
        utility::LogError("ParallelFor for CPU cannot run on device {}.",
                          device.ToString());
    }
    if (n == 0) {
        return;
    }

#pragma omp parallel for num_threads(utility::EstimateMaxThreads())
    for (int64_t i = 0; i < n; ++i) {
        func(i);
    }
}

#endif

/// Run a function in parallel on CPU or CUDA.
///
/// \param device The device for the parallel for loop to run on.
/// \param n The number of workloads.
/// \param func The function to be executed in parallel. The function should
/// take an int64_t workload index and returns void, i.e., `void func(int64_t)`.
///
/// \note This is optimized for uniform work items, i.e. where each call to \p
/// func takes the same time.
/// \note If you use a lambda function, capture only the required variables
/// instead of all to prevent accidental race conditions. If you want the
/// kernel to be used on both CPU and CUDA, capture the variables by value.
/// \note This does not dispatch to SYCL, since SYCL has extra constraints:
///      - Lambdas may capture by value only.
///      - No function pointers / virtual functions.
/// Auto dispatch to SYCL will enforce these conditions even on CPU devices. Use
/// ParallelForSYCL instead.
template <typename func_t>
void ParallelFor(const Device& device, int64_t n, const func_t& func) {
#ifdef __CUDACC__
    ParallelForCUDA_(device, n, func);
#else
    ParallelForCPU_(device, n, func);
#endif
}

/// Run a potentially vectorized function in parallel on CPU or CUDA.
///
/// \param device The device for the parallel for loop to run on.
/// \param n The number of workloads.
/// \param func The function to be executed in parallel. The function should
/// take an int64_t workload index and returns void, i.e., `void func(int64_t)`.
/// \param vec_func The vectorized function to be executed in parallel. The
/// function should be provided using the OPEN3D_VECTORIZED macro, e.g.,
/// `OPEN3D_VECTORIZED(MyISPCKernel, some_used_variable)`.
///
/// \note This is optimized for uniform work items, i.e. where each call to \p
/// func takes the same time.
/// \note If you use a lambda function, capture only the required variables
/// instead of all to prevent accidental race conditions. If you want the
/// kernel to be used on both CPU and CUDA, capture the variables by value.
///
/// Example:
///
/// \code
/// /* MyFile.cpp */
/// #ifdef BUILD_ISPC_MODULE
/// #include "MyFile_ispc.h"
/// #endif
///
/// std::vector<float> v(1000);
/// float fill_value = 42.0f;
/// core::ParallelFor(
///         core::Device("CPU:0"),
///         v.size(),
///         [&](int64_t idx) { v[idx] = fill_value; },
///         OPEN3D_VECTORIZED(MyFillKernel, v.data(), fill_value));
///
/// /* MyFile.ispc */
/// #include "open3d/core/ParallelFor.isph"
///
/// static inline void MyFillFunction(int64_t idx,
///                                   float* uniform v,
///                                   uniform float fill_value) {
///     v[idx] = fill_value;
/// }
///
/// OPEN3D_EXPORT_VECTORIZED(MyFillKernel,
///                          MyFillFunction,
///                          float* uniform,
///                          uniform float)
/// \endcode
template <typename vec_func_t, typename func_t>
void ParallelFor(const Device& device,
                 int64_t n,
                 const func_t& func,
                 const vec_func_t& vec_func) {
#ifdef BUILD_ISPC_MODULE

#ifdef __CUDACC__
    ParallelForCUDA_(device, n, func);
#else
    int num_threads = utility::EstimateMaxThreads();
    ParallelForCPU_(device, num_threads, [&](int64_t i) {
        int64_t start = n * i / num_threads;
        int64_t end = std::min<int64_t>(n * (i + 1) / num_threads, n);
        vec_func(start, end);
    });
#endif

#else

#ifdef __CUDACC__
    ParallelForCUDA_(device, n, func);
#else
    ParallelForCPU_(device, n, func);
#endif

#endif
}

#ifdef BUILD_ISPC_MODULE

// Internal helper macro.
#define OPEN3D_CALL_ISPC_KERNEL_(ISPCKernel, start, end, ...) \
    using namespace ispc;                                     \
    ISPCKernel(start, end, __VA_ARGS__);

#else

// Internal helper macro.
#define OPEN3D_CALL_ISPC_KERNEL_(ISPCKernel, start, end, ...)            \
    utility::LogError(                                                   \
            "ISPC module disabled. Unable to call vectorized kernel {}", \
            OPEN3D_STRINGIFY(ISPCKernel));

#endif

/// Internal helper macro.
#define OPEN3D_OVERLOADED_LAMBDA_(T, ISPCKernel, ...)                       \
    [&](T, int64_t start, int64_t end) {                                    \
        OPEN3D_CALL_ISPC_KERNEL_(                                           \
                OPEN3D_CONCAT(ISPCKernel, OPEN3D_CONCAT(_, T)), start, end, \
                __VA_ARGS__);                                               \
    }

/// OPEN3D_VECTORIZED(ISPCKernel, ...)
///
/// Defines a lambda function to call the provided kernel.
///
/// Use the OPEN3D_EXPORT_TEMPLATE_VECTORIZED macro to define the
/// kernel in the ISPC source file.
///
/// Note: The arguments to the kernel only have to exist if ISPC support is
/// enabled via BUILD_ISPC_MODULE=ON.
#define OPEN3D_VECTORIZED(ISPCKernel, ...)                             \
    [&](int64_t start, int64_t end) {                                  \
        OPEN3D_CALL_ISPC_KERNEL_(ISPCKernel, start, end, __VA_ARGS__); \
    }

/// OPEN3D_TEMPLATE_VECTORIZED(T, ISPCKernel, ...)
///
/// Defines a lambda function to call the provided template-like kernel.
/// Supported types:
/// - bool
/// - unsigned + signed {8,16,32,64} bit integers,
/// - float, double
///
/// Use the OPEN3D_EXPORT_TEMPLATE_VECTORIZED macro to define the
/// kernel in the ISPC source file.
///
/// Note: The arguments to the kernel only have to exist if ISPC support is
/// enabled via BUILD_ISPC_MODULE=ON.
#define OPEN3D_TEMPLATE_VECTORIZED(T, ISPCKernel, ...)                        \
    [&](int64_t start, int64_t end) {                                         \
        static_assert(std::is_arithmetic<T>::value,                           \
                      "Data type is not an arithmetic type");                 \
        utility::Overload(                                                    \
                OPEN3D_OVERLOADED_LAMBDA_(bool, ISPCKernel, __VA_ARGS__),     \
                OPEN3D_OVERLOADED_LAMBDA_(uint8_t, ISPCKernel, __VA_ARGS__),  \
                OPEN3D_OVERLOADED_LAMBDA_(int8_t, ISPCKernel, __VA_ARGS__),   \
                OPEN3D_OVERLOADED_LAMBDA_(uint16_t, ISPCKernel, __VA_ARGS__), \
                OPEN3D_OVERLOADED_LAMBDA_(int16_t, ISPCKernel, __VA_ARGS__),  \
                OPEN3D_OVERLOADED_LAMBDA_(uint32_t, ISPCKernel, __VA_ARGS__), \
                OPEN3D_OVERLOADED_LAMBDA_(int32_t, ISPCKernel, __VA_ARGS__),  \
                OPEN3D_OVERLOADED_LAMBDA_(uint64_t, ISPCKernel, __VA_ARGS__), \
                OPEN3D_OVERLOADED_LAMBDA_(int64_t, ISPCKernel, __VA_ARGS__),  \
                OPEN3D_OVERLOADED_LAMBDA_(float, ISPCKernel, __VA_ARGS__),    \
                OPEN3D_OVERLOADED_LAMBDA_(double, ISPCKernel, __VA_ARGS__),   \
                [&](auto&& generic, int64_t start, int64_t end) {             \
                    utility::LogError(                                        \
                            "Unsupported data type {} for calling "           \
                            "vectorized kernel {}",                           \
                            typeid(generic).name(),                           \
                            OPEN3D_STRINGIFY(ISPCKernel));                    \
                })(T{}, start, end);                                          \
    }

}  // namespace core
}  // namespace open3d
