#include <iostream>
#include <iomanip>
#include "Common.h"
#include "PrimitiveTests.h"
#include <random>
#include <stdlib.h>

ReduceAdd::ReduceAdd(size_t max_size)
{
	data_size = max_size;
	cpuResult = 0.0f;
	const float vmax = 1000.0f;
	std::random_device rd;
	std::mt19937 gen(rd());
	std::uniform_real_distribution<float> distr(0.0f, vmax);

	for (size_t index = 0; index < data_size; ++index)
	{
		float val = distr(gen);
		gpuResult.push_back(val);
		sourceData.push_back(val);
	}
}

void ReduceAdd::gpu_compute(cl::Context* context, cl::CommandQueue* queue, cl::Program* program, cl::Event* Event)
{
	cl_int err = CL_SUCCESS;
	cl::Kernel kernel = cl::Kernel(*program, "reduce_global", &err);
	CheckCLError(err);

	clInputBuffer = cl::Buffer(*context, CL_MEM_READ_ONLY, sizeof(int) * data_size, NULL, &err);
	CheckCLError(err);
	queue->enqueueWriteBuffer(clInputBuffer, true, 0, sizeof(int) * data_size, gpuResult.data());

	kernel.setArg(0, clInputBuffer);

	queue->enqueueNDRangeKernel(kernel,
		cl::NullRange,				// Indexek nem eloffszetelve
		cl::NDRange(data_size, 1),	// Minden elemet egy szál
		cl::NDRange(1024, 1),				// Workgroup méret? - ez az auto, ha nem indul, 1024-re, onnan csökkent, amig elindul
		NULL,						// 
		Event);
}

void ReduceAdd::cpu_compute()
{
	cpuResult = 0;
	for (size_t index = 0; index < data_size; ++index) {
		cpuResult += sourceData[index];
	}
}

void ReduceAdd::collect_results(cl::CommandQueue* queue)
{
	queue->enqueueReadBuffer(clInputBuffer, true, 0, sizeof(int) * data_size, gpuResult.data());
}

bool ReduceAdd::validate_results()
{
	float diff = abs(cpuResult - gpuResult[0]);
	if (diff < 0.3f) {
		return true;
	}
	else
	{
		std::cout << "Wrong result: " << cpuResult << "!=" << gpuResult[0] << ", diff is " <<diff << std::endl;
		return false;
	}
}

std::string ReduceAdd::description()
{
	return std::string("ReduceAdd (data_size=" + std::to_string(data_size) + ")");
}