//general parts
#include <stdio.h>
#include <vector>
#include <memory>
#include <string.h>
#include <chrono>
#include <thread>
#include <iostream>
#ifndef __STDC_FORMAT_MACROS
#define __STDC_FORMAT_MACROS
#endif
#include <inttypes.h>

#if(VKFFT_BACKEND==0)
#include "vulkan/vulkan.h"
#include "glslang_c_interface.h"
#elif(VKFFT_BACKEND==1)
#include <cuda.h>
#include <cuda_runtime.h>
#include <nvrtc.h>
#include <cuda_runtime_api.h>
#include <cuComplex.h>
#elif(VKFFT_BACKEND==2)
#ifndef __HIP_PLATFORM_HCC__
#define __HIP_PLATFORM_HCC__
#endif
#include <hip/hip_runtime.h>
#include <hip/hiprtc.h>
#include <hip/hip_runtime_api.h>
#include <hip/hip_complex.h>
#elif(VKFFT_BACKEND==3)
#ifndef CL_USE_DEPRECATED_OPENCL_1_2_APIS
#define CL_USE_DEPRECATED_OPENCL_1_2_APIS
#endif
#ifdef __APPLE__
#include <OpenCL/opencl.h>
#else
#include <CL/cl.h>
#endif 
#endif
#include "vkFFT.h"
#include "utils_VkFFT.h"

VkFFTResult sample_1003_benchmark_VkFFT_single_3d_2_512(VkGPU* vkGPU, uint64_t file_output, FILE* output, uint64_t isCompilerInitialized)
{
	VkFFTResult resFFT = VKFFT_SUCCESS;
#if(VKFFT_BACKEND==0)
	VkResult res = VK_SUCCESS;
#elif(VKFFT_BACKEND==1)
	cudaError_t res = cudaSuccess;
#elif(VKFFT_BACKEND==2)
	hipError_t res = hipSuccess;
#elif(VKFFT_BACKEND==3)
	cl_int res = CL_SUCCESS;
#endif
	if (file_output)
		fprintf(output, "1003 - VkFFT FFT + iFFT C2C multidimensional benchmark in single precision: all supported cubes from 2 to 512\n");
	printf("1003 - VkFFT FFT + iFFT C2C multidimensional benchmark in single precision: all supported cubes from 2 to 512\n");
	const int num_runs = 3;
	double benchmark_result = 0;//averaged result = sum(system_size/iteration_time)/num_benchmark_samples
	//memory allocated on the CPU once, makes benchmark completion faster + avoids performance issues connected to frequent allocation/deallocation.
	float* buffer_input = (float*)malloc((uint64_t)4 * 2 * (uint64_t)pow(2, 27));
	if (!buffer_input) return VKFFT_ERROR_MALLOC_FAILED;
	for (uint64_t i = 0; i < 2 * (uint64_t)pow(2, 27); i++) {
		buffer_input[i] = (float)(2 * ((float)rand()) / RAND_MAX - 1.0);
	}
	int num_systems = 0;
	for (int n = 1; n < 513; n++) {
		double run_time[num_runs];
		for (uint64_t r = 0; r < num_runs; r++) {
			//Configuration + FFT application .
			VkFFTConfiguration configuration = {};
			VkFFTApplication app = {};
			//FFT + iFFT sample code.
			//Setting up FFT configuration for forward and inverse FFT.
			configuration.FFTdim = 3; //FFT dimension, 1D, 2D or 3D (default 1).
			configuration.size[0] = n;// 4 * pow(2, n); //Multidimensional FFT dimensions sizes (default 1). For best performance (and stability), order dimensions in descendant size order as: x>y>z.   
			if (n == 1) configuration.size[0] = 512;
			uint64_t temp = configuration.size[0];

			/*for (uint64_t j = 2; j < 14; j++)
			{
				if (temp % j == 0) {
					temp /= j;
					j = 1;
				}
			}
			if (temp != 1) break;*/
			configuration.size[1] = configuration.size[0];
			configuration.size[2] = configuration.size[0];
			//After this, configuration file contains pointers to Vulkan objects needed to work with the GPU: VkDevice* device - created device, [uint64_t *bufferSize, VkBuffer *buffer, VkDeviceMemory* bufferDeviceMemory] - allocated GPU memory FFT is performed on. [uint64_t *kernelSize, VkBuffer *kernel, VkDeviceMemory* kernelDeviceMemory] - allocated GPU memory, where kernel for convolution is stored.
			configuration.device = &vkGPU->device;
#if(VKFFT_BACKEND==0)
			configuration.queue = &vkGPU->queue; //to allocate memory for LUT, we have to pass a queue, vkGPU->fence, commandPool and physicalDevice pointers 
			configuration.fence = &vkGPU->fence;
			configuration.commandPool = &vkGPU->commandPool;
			configuration.physicalDevice = &vkGPU->physicalDevice;
			configuration.isCompilerInitialized = isCompilerInitialized;//compiler can be initialized before VkFFT plan creation. if not, VkFFT will create and destroy one after initialization
#elif(VKFFT_BACKEND==3)
			configuration.platform = &vkGPU->platform;
			configuration.context = &vkGPU->context;
#endif
			//Allocate buffer for the input data.
			uint64_t bufferSize = (uint64_t)sizeof(float) * 2 * configuration.size[0] * configuration.size[1] * configuration.size[2];;
#if(VKFFT_BACKEND==0)
			VkBuffer buffer = {};
			VkDeviceMemory bufferDeviceMemory = {};
			resFFT = allocateBuffer(vkGPU, &buffer, &bufferDeviceMemory, VK_BUFFER_USAGE_STORAGE_BUFFER_BIT | VK_BUFFER_USAGE_TRANSFER_SRC_BIT | VK_BUFFER_USAGE_TRANSFER_DST_BIT, VK_MEMORY_HEAP_DEVICE_LOCAL_BIT, bufferSize);
			if (resFFT != VKFFT_SUCCESS) return resFFT;
			configuration.buffer = &buffer;
#elif(VKFFT_BACKEND==1)
			cuFloatComplex* buffer = 0;
			res = cudaMalloc((void**)&buffer, bufferSize);
			if (res != cudaSuccess) return VKFFT_ERROR_FAILED_TO_ALLOCATE;
			configuration.buffer = (void**)&buffer;
#elif(VKFFT_BACKEND==2)
			hipFloatComplex* buffer = 0;
			res = hipMalloc((void**)&buffer, bufferSize);
			if (res != hipSuccess) return VKFFT_ERROR_FAILED_TO_ALLOCATE;
			configuration.buffer = (void**)&buffer;
#elif(VKFFT_BACKEND==3)
			cl_mem buffer = 0;
			buffer = clCreateBuffer(vkGPU->context, CL_MEM_READ_WRITE, bufferSize, 0, &res);
			if (res != CL_SUCCESS) return VKFFT_ERROR_FAILED_TO_ALLOCATE;
			configuration.buffer = &buffer;
#endif

			configuration.bufferSize = &bufferSize;

			//Fill data on CPU. It is best to perform all operations on GPU after initial upload.
			/*float* buffer_input = (float*)malloc(bufferSize);

			for (uint64_t k = 0; k < configuration.size[2]; k++) {
				for (uint64_t j = 0; j < configuration.size[1]; j++) {
					for (uint64_t i = 0; i < configuration.size[0]; i++) {
						buffer_input[2 * (i + j * configuration.size[0] + k * (configuration.size[0]) * configuration.size[1])] = 2 * ((float)rand()) / RAND_MAX - 1.0;
						buffer_input[2 * (i + j * configuration.size[0] + k * (configuration.size[0]) * configuration.size[1]) + 1] = 2 * ((float)rand()) / RAND_MAX - 1.0;
						}
					}
				}

			*/
			//Sample buffer transfer tool. Uses staging buffer of the same size as destination buffer, which can be reduced if transfer is done sequentially in small buffers.
#if(VKFFT_BACKEND==0)
			resFFT = transferDataFromCPU(vkGPU, buffer_input, &buffer, bufferSize);
			if (resFFT != VKFFT_SUCCESS) return resFFT;
#elif(VKFFT_BACKEND==1)
			res = cudaMemcpy(buffer, buffer_input, bufferSize, cudaMemcpyHostToDevice);
			if (res != cudaSuccess) return VKFFT_ERROR_FAILED_TO_COPY;
#elif(VKFFT_BACKEND==2)
			res = hipMemcpy(buffer, buffer_input, bufferSize, hipMemcpyHostToDevice);
			if (res != hipSuccess) return VKFFT_ERROR_FAILED_TO_COPY;
#elif(VKFFT_BACKEND==3)
			res = clEnqueueWriteBuffer(vkGPU->commandQueue, buffer, CL_TRUE, 0, bufferSize, buffer_input, 0, NULL, NULL);
			if (res != CL_SUCCESS) return VKFFT_ERROR_FAILED_TO_COPY;
#endif

			//Initialize applications. This function loads shaders, creates pipeline and configures FFT based on configuration file. No buffer allocations inside VkFFT library.  
			resFFT = initializeVkFFT(&app, configuration);
			if (resFFT != VKFFT_SUCCESS) return resFFT;

			//Submit FFT+iFFT.
			uint64_t num_iter = (((uint64_t)3 * 4096 * 1024.0 * 1024.0) / bufferSize > 1000) ? 1000 : (uint64_t)((uint64_t)3 * 4096 * 1024.0 * 1024.0) / bufferSize;
#if(VKFFT_BACKEND==0)
			if (vkGPU->physicalDeviceProperties.vendorID == 0x8086) num_iter /= 4;//smaller benchmark for Intel GPUs
#elif(VKFFT_BACKEND==3)
			cl_uint vendorID;
			clGetDeviceInfo(vkGPU->device, CL_DEVICE_VENDOR_ID, sizeof(cl_int), &vendorID, 0);
			if (vendorID == 0x8086) num_iter /= 4;//smaller benchmark for Intel GPUs
#endif
			if (num_iter == 0) num_iter = 1;
			double totTime = 0;
			VkFFTLaunchParams launchParams = {};
			resFFT = performVulkanFFTiFFT(vkGPU, &app, &launchParams, num_iter, &totTime);
			if (resFFT != VKFFT_SUCCESS) return resFFT;
			run_time[r] = totTime;
			if (n > 1) {
				if (r == num_runs - 1) {
					num_systems++;
					double std_error = 0;
					double avg_time = 0;
					for (uint64_t t = 0; t < num_runs; t++) {
						avg_time += run_time[t];
					}
					avg_time /= num_runs;
					for (uint64_t t = 0; t < num_runs; t++) {
						std_error += (run_time[t] - avg_time) * (run_time[t] - avg_time);
					}
					std_error = sqrt(std_error / num_runs);
					uint64_t num_tot_transfers = 0;
					for (uint64_t i = 0; i < configuration.FFTdim; i++)
						num_tot_transfers += app.localFFTPlan->numAxisUploads[i];
					num_tot_transfers *= 4;
					if (file_output)
						fprintf(output, "VkFFT System: %" PRIu64 " Buffer: %" PRIu64 " MB avg_time_per_step: %0.3f ms std_error: %0.3f num_iter: %" PRIu64 " benchmark: %" PRIu64 " bandwidth: %0.1f\n", configuration.size[0], bufferSize / 1024 / 1024, avg_time, std_error, num_iter, (uint64_t)(((double)bufferSize / 1024) / avg_time), bufferSize / 1024.0 / 1024.0 / 1.024 * num_tot_transfers / avg_time);

					printf("VkFFT System: %" PRIu64 " Buffer: %" PRIu64 " MB avg_time_per_step: %0.3f ms std_error: %0.3f num_iter: %" PRIu64 " benchmark: %" PRIu64 " bandwidth: %0.1f\n", configuration.size[0], bufferSize / 1024 / 1024, avg_time, std_error, num_iter, (uint64_t)(((double)bufferSize / 1024) / avg_time), bufferSize / 1024.0 / 1024.0 / 1.024 * num_tot_transfers / avg_time);
					benchmark_result += ((double)bufferSize / 1024) / avg_time;
				}


			}

#if(VKFFT_BACKEND==0)
			vkDestroyBuffer(vkGPU->device, buffer, NULL);
			vkFreeMemory(vkGPU->device, bufferDeviceMemory, NULL);
#elif(VKFFT_BACKEND==1)
			cudaFree(buffer);
#elif(VKFFT_BACKEND==2)
			hipFree(buffer);
#elif(VKFFT_BACKEND==3)
			clReleaseMemObject(buffer);
#endif

			deleteVkFFT(&app);

		}
	}
	free(buffer_input);
	benchmark_result /= (num_systems);

	if (file_output) {
		fprintf(output, "Benchmark score VkFFT: %" PRIu64 "\n", (uint64_t)(benchmark_result));
#if(VKFFT_BACKEND==0)
		fprintf(output, "Device name: %s API:%d.%d.%d\n", vkGPU->physicalDeviceProperties.deviceName, (vkGPU->physicalDeviceProperties.apiVersion >> 22), ((vkGPU->physicalDeviceProperties.apiVersion >> 12) & 0x3ff), (vkGPU->physicalDeviceProperties.apiVersion & 0xfff));
#endif
	}
	printf("Benchmark score VkFFT: %" PRIu64 "\n", (uint64_t)(benchmark_result));
#if(VKFFT_BACKEND==0)
	printf("Device name: %s API:%d.%d.%d\n", vkGPU->physicalDeviceProperties.deviceName, (vkGPU->physicalDeviceProperties.apiVersion >> 22), ((vkGPU->physicalDeviceProperties.apiVersion >> 12) & 0x3ff), (vkGPU->physicalDeviceProperties.apiVersion & 0xfff));
#endif
	return resFFT;

}
