/**
 * 2DConvolution.c: This file is part of the PolyBench/GPU 1.0 test suite.
 *
 *
 * Contact: Scott Grauer-Gray <sgrauerg@gmail.com>
 * Louis-Noel Pouchet <pouchet@cse.ohio-state.edu>
 * Web address: http://www.cse.ohio-state.edu/~pouchet/software/polybench/GPU
 */

#include <stdio.h>
#include <stdlib.h>
#include <time.h>
#include <sys/time.h>
#include <math.h>

#ifdef __APPLE__
#include <OpenCL/opencl.h>
#else
#include <CL/cl.h>
#endif

#include "../../common/polybenchUtilFuncts.h"

//define the error threshold for the results "not matching"
#define PERCENT_DIFF_ERROR_THRESHOLD 1.05

#define MAX_SOURCE_SIZE (0x100000)

/* Problem size */
#define NI 4096
#define NJ 4096

/* Thread block dimensions */
#define DIM_LOCAL_WORK_GROUP_X 32
#define DIM_LOCAL_WORK_GROUP_Y 8

#if defined(cl_khr_fp64)  // Khronos extension available?
#pragma OPENCL EXTENSION cl_khr_fp64 : enable
#elif defined(cl_amd_fp64)  // AMD extension available?
#pragma OPENCL EXTENSION cl_amd_fp64 : enable
#endif

/* Can switch DATA_TYPE between float and double */
typedef float DATA_TYPE;


char str_temp[1024];

cl_platform_id platform_id;
cl_device_id device_id;   
cl_uint num_devices;
cl_uint num_platforms;
cl_int errcode;
cl_context clGPUContext;
cl_kernel clKernel;
cl_command_queue clCommandQue;
cl_program clProgram;
cl_mem a_mem_obj;
cl_mem b_mem_obj;
cl_mem c_mem_obj;
FILE *fp;
char *source_str;
size_t source_size;



void compareResults(DATA_TYPE* B, DATA_TYPE* B_outputFromGpu)
{
	int i, j, fail;
	fail = 0;
	
	// Compare a and b
	for (i=1; i < (NI-1); i++) 
	{
		for (j=1; j < (NJ-1); j++) 
		{
			if (percentDiff(B[i*NJ + j], B_outputFromGpu[i*NJ + j]) > PERCENT_DIFF_ERROR_THRESHOLD) 
			{
				fail++;
			}
		}
	}
	
	// Print results
	printf("Non-Matching CPU-GPU Outputs Beyond Error Threshold of %4.2f Percent: %d\n", PERCENT_DIFF_ERROR_THRESHOLD, fail);
	
}


void read_cl_file()
{
	// Load the kernel source code into the array source_str
	fp = fopen("2DConvolution.cl", "r");
	if (!fp) {
		fprintf(stdout, "Failed to load kernel.\n");
		exit(1);
	}
	source_str = (char*)malloc(MAX_SOURCE_SIZE);
	source_size = fread( source_str, 1, MAX_SOURCE_SIZE, fp);
	fclose( fp );
}


void init(DATA_TYPE* A)
{
	int i, j;

	for (i = 0; i < NI; ++i)
    	{
		for (j = 0; j < NJ; ++j)
		{
			A[i*NJ + j] = (float)rand()/RAND_MAX;
        	}
    	}
}


void cl_initialization()
{
	
	// Get platform and device information
	errcode = clGetPlatformIDs(1, &platform_id, &num_platforms);
	if(errcode == CL_SUCCESS) printf("number of platforms is %d\n",num_platforms);
	else printf("Error getting platform IDs\n");

	errcode = clGetPlatformInfo(platform_id,CL_PLATFORM_NAME, sizeof(str_temp), str_temp,NULL);
	if(errcode == CL_SUCCESS) printf("platform name is %s\n",str_temp);
	else printf("Error getting platform name\n");

	errcode = clGetPlatformInfo(platform_id, CL_PLATFORM_VERSION, sizeof(str_temp), str_temp,NULL);
	if(errcode == CL_SUCCESS) printf("platform version is %s\n",str_temp);
	else printf("Error getting platform version\n");

	errcode = clGetDeviceIDs( platform_id, CL_DEVICE_TYPE_GPU, 1, &device_id, &num_devices);
	if(errcode == CL_SUCCESS) printf("number of devices is %d\n", num_devices);
	else printf("Error getting device IDs\n");

	errcode = clGetDeviceInfo(device_id,CL_DEVICE_NAME, sizeof(str_temp), str_temp,NULL);
	if(errcode == CL_SUCCESS) printf("device name is %s\n",str_temp);
	else printf("Error getting device name\n");
	
	// Create an OpenCL context
	clGPUContext = clCreateContext( NULL, 1, &device_id, NULL, NULL, &errcode);
	if(errcode != CL_SUCCESS) printf("Error in creating context\n");
 
	//Create a command-queue
	clCommandQue = clCreateCommandQueue(clGPUContext, device_id, 0, &errcode);
	if(errcode != CL_SUCCESS) printf("Error in creating command queue\n");
}


void cl_mem_init(DATA_TYPE* A)
{
	a_mem_obj = clCreateBuffer(clGPUContext, CL_MEM_READ_ONLY, sizeof(DATA_TYPE) * NI * NJ, NULL, &errcode);
	b_mem_obj = clCreateBuffer(clGPUContext, CL_MEM_READ_WRITE, sizeof(DATA_TYPE) * NI * NJ, NULL, &errcode);
	
	if(errcode != CL_SUCCESS) printf("Error in creating buffers\n");

	errcode = clEnqueueWriteBuffer(clCommandQue, a_mem_obj, CL_TRUE, 0, sizeof(DATA_TYPE) * NI * NJ, A, 0, NULL, NULL);
	if(errcode != CL_SUCCESS)printf("Error in writing buffers\n");
 }


void cl_load_prog()
{
	// Create a program from the kernel source
	clProgram = clCreateProgramWithSource(clGPUContext, 1, (const char **)&source_str, (const size_t *)&source_size, &errcode);

	if(errcode != CL_SUCCESS) printf("Error in creating program\n");

	// Build the program
	errcode = clBuildProgram(clProgram, 1, &device_id, NULL, NULL, NULL);
	if(errcode != CL_SUCCESS) printf("Error in building program\n");
		
	// Create the OpenCL kernel
	clKernel = clCreateKernel(clProgram, "Convolution2D_kernel", &errcode);
	if(errcode != CL_SUCCESS) printf("Error in creating kernel\n");
	clFinish(clCommandQue);
}


void cl_launch_kernel()
{
	double t_start, t_end;
	int ni = NI;
	int nj = NJ;

	size_t localWorkSize[2], globalWorkSize[2];
	localWorkSize[0] = DIM_LOCAL_WORK_GROUP_X;
	localWorkSize[1] = DIM_LOCAL_WORK_GROUP_Y;
	globalWorkSize[0] = (size_t)ceil(((float)NI) / ((float)DIM_LOCAL_WORK_GROUP_X)) * DIM_LOCAL_WORK_GROUP_X;
	globalWorkSize[1] = (size_t)ceil(((float)NJ) / ((float)DIM_LOCAL_WORK_GROUP_Y)) * DIM_LOCAL_WORK_GROUP_Y;

	t_start = rtclock();
	
	// Set the arguments of the kernel
	errcode =  clSetKernelArg(clKernel, 0, sizeof(cl_mem), (void *)&a_mem_obj);
	errcode |= clSetKernelArg(clKernel, 1, sizeof(cl_mem), (void *)&b_mem_obj);
	errcode =  clSetKernelArg(clKernel, 2, sizeof(int), &ni);
	errcode |= clSetKernelArg(clKernel, 3, sizeof(int), &nj);

	if(errcode != CL_SUCCESS) printf("Error in seting arguments\n");
	// Execute the OpenCL kernel
	errcode = clEnqueueNDRangeKernel(clCommandQue, clKernel, 2, NULL, globalWorkSize, localWorkSize, 0, NULL, NULL);

	if(errcode != CL_SUCCESS) printf("Error in launching kernel\n");
	clFinish(clCommandQue);
	t_end = rtclock();
	fprintf(stdout, "GPU Runtime: %0.6lfs\n", t_end - t_start);
}

void cl_clean_up()
{
	// Clean up
	errcode = clFlush(clCommandQue);
	errcode = clFinish(clCommandQue);
	errcode = clReleaseKernel(clKernel);
	errcode = clReleaseProgram(clProgram);
	errcode = clReleaseMemObject(a_mem_obj);
	errcode = clReleaseMemObject(b_mem_obj);
	errcode = clReleaseCommandQueue(clCommandQue);
	errcode = clReleaseContext(clGPUContext);
	if(errcode != CL_SUCCESS) printf("Error in cleanup\n");
}

void conv2D(DATA_TYPE* A, DATA_TYPE* B)
{
	int i, j;
	DATA_TYPE c11, c12, c13, c21, c22, c23, c31, c32, c33;

	c11 = +0.2;  c21 = +0.5;  c31 = -0.8;
	c12 = -0.3;  c22 = +0.6;  c32 = -0.9;
	c13 = +0.4;  c23 = +0.7;  c33 = +0.10;


	for (i = 1; i < NI - 1; ++i) // 0
	{
		for (j = 1; j < NJ - 1; ++j) // 1
		{
			B[i*NJ + j] = c11 * A[(i - 1)*NJ + (j - 1)]  +  c12 * A[(i + 0)*NJ + (j - 1)]  +  c13 * A[(i + 1)*NJ + (j - 1)]
				+ c21 * A[(i - 1)*NJ + (j + 0)]  +  c22 * A[(i + 0)*NJ + (j + 0)]  +  c23 * A[(i + 1)*NJ + (j + 0)] 
				+ c31 * A[(i - 1)*NJ + (j + 1)]  +  c32 * A[(i + 0)*NJ + (j + 1)]  +  c33 * A[(i + 1)*NJ + (j + 1)];
		}
	}
}


int main(int argc, char *argv[])
{
	double t_start, t_end;
	int i;

	DATA_TYPE* A;
	DATA_TYPE* B;  
	DATA_TYPE* B_outputFromGpu;
	
	A = (DATA_TYPE*)malloc(NI*NJ*sizeof(DATA_TYPE));
	B = (DATA_TYPE*)malloc(NI*NJ*sizeof(DATA_TYPE));
	B_outputFromGpu = (DATA_TYPE*)malloc(NI*NJ*sizeof(DATA_TYPE));

	init(A);

	read_cl_file();
	cl_initialization();
	cl_mem_init(A);
	cl_load_prog();

	cl_launch_kernel();

	errcode = clEnqueueReadBuffer(clCommandQue, b_mem_obj, CL_TRUE, 0, NI*NJ*sizeof(DATA_TYPE), B_outputFromGpu, 0, NULL, NULL);
	if(errcode != CL_SUCCESS) printf("Error in reading GPU mem\n");

	t_start = rtclock();
	conv2D(A, B);
	t_end = rtclock(); 
	fprintf(stdout, "CPU Runtime: %0.6lfs\n", t_end - t_start);   
	compareResults(B, B_outputFromGpu);

	free(A);
	free(B);
	free(B_outputFromGpu);

	cl_clean_up();
    	return 0;
}

