// Primitives.cpp : Defines the entry point for the console application.

#include <string>
#include <vector>
#include "Common.h"

// OpenCL C API
#include <CL/opencl.h>

// OpenCL C++ API
#include "cl.hpp"

const size_t dataSize = 4096;

void capi()
{
	// Get a platform ID
	cl_platform_id platformID;
	clGetPlatformIDs(1, &platformID, NULL);
	
	// Get a device ID
	cl_device_id deviceID;
	clGetDeviceIDs(platformID, CL_DEVICE_TYPE_GPU, 1, &deviceID, NULL);
	
	// Create a context
	cl_context context;
	cl_context_properties contextProperties[] =
	{ CL_CONTEXT_PLATFORM, (cl_context_properties)platformID, 0 };
	context = clCreateContext(contextProperties, 1, &deviceID, NULL, NULL, NULL);
	
	// Create a command queue
	cl_command_queue queue;
	queue = clCreateCommandQueue(context, deviceID, CL_QUEUE_PROFILING_ENABLE, NULL);
	
	// Create an OpenCL program
	std::string source = FileToString("../kernels/programs.cl");
	const char* csource = source.c_str();
	cl_program program = clCreateProgramWithSource(context, 1, &csource, NULL, NULL);
	cl_int err = clBuildProgram(program, 1, &deviceID, NULL, NULL, NULL);
	if (err != CL_SUCCESS)
	{
		cl_uint logLength;
		clGetProgramBuildInfo(program, deviceID, CL_PROGRAM_BUILD_LOG, 0, NULL, &logLength);
		char* log = new char[logLength];
		clGetProgramBuildInfo(program, deviceID, CL_PROGRAM_BUILD_LOG, logLength, log, 0);
		std::cout << log << std::endl;
		delete[] log;
		exit(-1);
	}

	// Get the kernel handle
	cl_kernel kernel = clCreateKernel(program, "square", &err);
	if(!CheckCLError(err)) exit(-1);

	// Allocate and upload the input data
	std::vector<float> hostBuffer;
	for (size_t index = 0; index < dataSize; ++index)
	{
		hostBuffer.push_back(static_cast<float>(index));
	}

	cl_mem inputBuffer;
	inputBuffer = clCreateBuffer(context, CL_MEM_READ_ONLY, sizeof(float) * dataSize, NULL, &err);
	if (!CheckCLError(err)) exit(-1);

	clEnqueueWriteBuffer(queue, inputBuffer, CL_TRUE, 0, sizeof(float) * dataSize, hostBuffer.data(), 0, NULL, NULL);

	// Alocate output data
	cl_mem outputBuffer;
	outputBuffer = clCreateBuffer(context, CL_MEM_WRITE_ONLY, sizeof(float) * dataSize, NULL, &err);
	if (!CheckCLError(err)) exit(-1);

	// Set the kernel paramateres
	clSetKernelArg(kernel, 0, sizeof(cl_mem), &inputBuffer);
	clSetKernelArg(kernel, 1, sizeof(cl_mem), &outputBuffer);
	// Enqueue the kernel
	clEnqueueNDRangeKernel(queue, kernel, 1, NULL, &dataSize, NULL, 0, NULL, NULL);
	// Copy the result back to the host
	clEnqueueReadBuffer(queue, outputBuffer, CL_TRUE, 0, sizeof(float) * dataSize, hostBuffer.data(), 0, NULL, NULL);

	// Validate the output
	for (size_t index = 0; index < dataSize; ++index)
	{
		if (hostBuffer[index] != index*index)
		{
			std::cout << "Wrong result at [" << index << "]: " << hostBuffer[index] << "!=" << index*index << std::endl;
			break;
		}
	}
	std::cout << "Finished" << std::endl;
}

void cppapi()
{
	cl_int err = CL_SUCCESS;

	// Get a platform ID
	std::vector<cl::Platform> platforms;
	cl::Platform::get(&platforms);
	if (platforms.size() == 0)
	{
		std::cout << "Unable to find suitable platform." << std::endl;
		exit(-1);
	}

	std::cout << platforms[0].getInfo<CL_PLATFORM_NAME>() << std::endl;

	// Create a context
	cl_context_properties properties[] =
	{ CL_CONTEXT_PLATFORM, (cl_context_properties)(platforms[0])(), 0 };
	cl::Context context(CL_DEVICE_TYPE_GPU, properties);

	// Enumerate the devices
	std::vector<cl::Device> devices = context.getInfo<CL_CONTEXT_DEVICES>();
	std::cout << devices[0].getInfo<CL_DEVICE_GLOBAL_MEM_SIZE>() << std::endl;

	// Create the command queue
	cl::Event event;
	cl::CommandQueue queue(context, devices[0], 0, &err);

	// Create the OpenCL program
	std::string programSource = FileToString("../kernels/programs.cl");
	cl::Program program = cl::Program(context, programSource);
	program.build(devices);
	
	
	// Get the kernel handle
	cl::Kernel kernel(program, "histogram_global", &err);
	CheckCLError(err);

	// Allocate and upload the input data
	std::vector<float> hostBuffer;
	for (size_t index = 0; index < dataSize; ++index)
	{
		hostBuffer.push_back(static_cast<float>(index % 32));
	}

	cl::Buffer clInputBuffer = cl::Buffer(context, CL_MEM_READ_ONLY, sizeof(float) * dataSize, NULL, &err);
	queue.enqueueWriteBuffer(clInputBuffer, 
		true, // Blocking!
		0, sizeof(float) * dataSize, hostBuffer.data());

	// Allocate the output data
	cl::Buffer clResultBuffer = cl::Buffer(context, CL_MEM_WRITE_ONLY, sizeof(float) * 32, NULL, &err);

	// Set the kernel parameters	
	kernel.setArg(0, clInputBuffer); // kernel FV paraméterei sorrendben
	kernel.setArg(1, clResultBuffer);

	// Enqueue the kernel
	queue.enqueueNDRangeKernel(kernel,
		cl::NullRange,				// Indexek nem eloffszetelve
		cl::NDRange(dataSize, 1),	// Minden elemet egy szál
		cl::NullRange,				// Workgroup méret? - ez az auto, ha nem indul, 1024-re, onnan csökkent, amig elindul
		NULL,						// 
		&event); // Ő jlezi hogy vége, lsd lent

	// Create reference values
	for (size_t index = 0; index < dataSize; ++index) {
	}
	event.wait();

	// Copy result back to host
	queue.enqueueReadBuffer(clResultBuffer, true, 0, sizeof(float) * 32, hostBuffer.data());

//	Validate the result
	for (size_t index = 0; index < 32; ++index)
	{
		if (hostBuffer[index] != index*index)
		{
			std::cout << "Wrong result at [" << index << "]: " << hostBuffer[index] << "!=" << index*index << std::endl;
			break;
		}
	}
	for (size_t index = 0; index < 32; ++index) {
		std::cout << index << ": " << hostBuffer[index] << std::endl;
	}
	std::cout << "Finished" << std::endl;
}

int main()
{
	//capi();
	cppapi();
    return 0;
}