gnss-sdr/src/algorithms/libs/opencl/fft_setup.cc

403 lines
11 KiB
C++

//
// File: fft_setup.cpp
//
// Version: <1.0>
//
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////////////////////////////////////////////////////////////////////////////////////////////////////
#include "fft_internal.h"
#include "fft_base_kernels.h"
#include <stdlib.h>
#include <string.h>
#include <sys/types.h>
#include <sys/stat.h>
#include <iostream>
#include <string>
#include <sstream>
#include <limits>
using namespace std;
extern void getKernelWorkDimensions(cl_fft_plan *plan, cl_fft_kernel_info *kernelInfo, cl_int *batchSize, size_t *gWorkItems, size_t *lWorkItems);
static void
getBlockConfigAndKernelString(cl_fft_plan *plan)
{
plan->temp_buffer_needed = 0;
*plan->kernel_string += baseKernels;
if(plan->format == clFFT_SplitComplexFormat)
*plan->kernel_string += twistKernelPlannar;
else
*plan->kernel_string += twistKernelInterleaved;
switch(plan->dim)
{
case clFFT_1D:
FFT1D(plan, cl_fft_kernel_x);
break;
case clFFT_2D:
FFT1D(plan, cl_fft_kernel_x);
FFT1D(plan, cl_fft_kernel_y);
break;
case clFFT_3D:
FFT1D(plan, cl_fft_kernel_x);
FFT1D(plan, cl_fft_kernel_y);
FFT1D(plan, cl_fft_kernel_z);
break;
default:
return;
}
plan->temp_buffer_needed = 0;
cl_fft_kernel_info *kInfo = plan->kernel_info;
while(kInfo)
{
plan->temp_buffer_needed |= !kInfo->in_place_possible;
kInfo = kInfo->next;
}
}
static void
deleteKernelInfo(cl_fft_kernel_info *kInfo)
{
if(kInfo)
{
if(kInfo->kernel_name)
free(kInfo->kernel_name);
if(kInfo->kernel)
clReleaseKernel(kInfo->kernel);
free(kInfo);
}
}
static void
destroy_plan(cl_fft_plan *Plan)
{
cl_fft_kernel_info *kernel_info = Plan->kernel_info;
while(kernel_info)
{
cl_fft_kernel_info *tmp = kernel_info->next;
deleteKernelInfo(kernel_info);
kernel_info = tmp;
}
Plan->kernel_info = NULL;
if(Plan->kernel_string)
{
delete Plan->kernel_string;
Plan->kernel_string = NULL;
}
if(Plan->twist_kernel)
{
clReleaseKernel(Plan->twist_kernel);
Plan->twist_kernel = NULL;
}
if(Plan->program)
{
clReleaseProgram(Plan->program);
Plan->program = NULL;
}
if(Plan->tempmemobj)
{
clReleaseMemObject(Plan->tempmemobj);
Plan->tempmemobj = NULL;
}
if(Plan->tempmemobj_real)
{
clReleaseMemObject(Plan->tempmemobj_real);
Plan->tempmemobj_real = NULL;
}
if(Plan->tempmemobj_imag)
{
clReleaseMemObject(Plan->tempmemobj_imag);
Plan->tempmemobj_imag = NULL;
}
}
static int
createKernelList(cl_fft_plan *plan)
{
cl_program program = plan->program;
cl_fft_kernel_info *kernel_info = plan->kernel_info;
cl_int err;
while(kernel_info)
{
kernel_info->kernel = clCreateKernel(program, kernel_info->kernel_name, &err);
if(!kernel_info->kernel || err != CL_SUCCESS)
return err;
kernel_info = kernel_info->next;
}
if(plan->format == clFFT_SplitComplexFormat)
plan->twist_kernel = clCreateKernel(program, "clFFT_1DTwistSplit", &err);
else
plan->twist_kernel = clCreateKernel(program, "clFFT_1DTwistInterleaved", &err);
if(!plan->twist_kernel || err)
return err;
return CL_SUCCESS;
}
int getMaxKernelWorkGroupSize(cl_fft_plan *plan, unsigned int *max_wg_size, unsigned int num_devices, cl_device_id *devices)
{
int reg_needed = 0;
*max_wg_size = std::numeric_limits<int>::max();
int err;
unsigned wg_size;
unsigned int i;
for(i = 0; i < num_devices; i++)
{
cl_fft_kernel_info *kInfo = plan->kernel_info;
while(kInfo)
{
err = clGetKernelWorkGroupInfo(kInfo->kernel, devices[i], CL_KERNEL_WORK_GROUP_SIZE, sizeof(size_t), &wg_size, NULL);
if(err != CL_SUCCESS)
return -1;
if(wg_size < kInfo->num_workitems_per_workgroup)
reg_needed |= 1;
if(*max_wg_size > wg_size)
*max_wg_size = wg_size;
kInfo = kInfo->next;
}
}
return reg_needed;
}
#define ERR_MACRO(err) { \
if( err != CL_SUCCESS) \
{ \
if(error_code) \
*error_code = err; \
clFFT_DestroyPlan((clFFT_Plan) plan); \
return (clFFT_Plan) NULL; \
} \
}
clFFT_Plan
clFFT_CreatePlan(cl_context context, clFFT_Dim3 n, clFFT_Dimension dim, clFFT_DataFormat dataFormat, cl_int *error_code )
{
int i;
cl_int err;
int isPow2 = 1;
cl_fft_plan *plan = NULL;
ostringstream kString;
int num_devices;
int gpu_found = 0;
cl_device_id devices[16];
size_t ret_size;
cl_device_type device_type;
if(!context)
ERR_MACRO(CL_INVALID_VALUE);
isPow2 |= n.x && !( (n.x - 1) & n.x );
isPow2 |= n.y && !( (n.y - 1) & n.y );
isPow2 |= n.z && !( (n.z - 1) & n.z );
if(!isPow2)
ERR_MACRO(CL_INVALID_VALUE);
if( (dim == clFFT_1D && (n.y != 1 || n.z != 1)) || (dim == clFFT_2D && n.z != 1) )
ERR_MACRO(CL_INVALID_VALUE);
plan = (cl_fft_plan *) malloc(sizeof(cl_fft_plan));
if(!plan)
ERR_MACRO(CL_OUT_OF_RESOURCES);
plan->context = context;
clRetainContext(context);
plan->n = n;
plan->dim = dim;
plan->format = dataFormat;
plan->kernel_info = 0;
plan->num_kernels = 0;
plan->twist_kernel = 0;
plan->program = 0;
plan->temp_buffer_needed = 0;
plan->last_batch_size = 0;
plan->tempmemobj = 0;
plan->tempmemobj_real = 0;
plan->tempmemobj_imag = 0;
plan->max_localmem_fft_size = 2048;
plan->max_work_item_per_workgroup = 256;
plan->max_radix = 16;
plan->min_mem_coalesce_width = 16;
plan->num_local_mem_banks = 16;
patch_kernel_source:
plan->kernel_string = new string("");
if(!plan->kernel_string)
ERR_MACRO(CL_OUT_OF_RESOURCES);
getBlockConfigAndKernelString(plan);
const char *source_str = plan->kernel_string->c_str();
plan->program = clCreateProgramWithSource(context, 1, (const char**) &source_str, NULL, &err);
ERR_MACRO(err);
err = clGetContextInfo(context, CL_CONTEXT_DEVICES, sizeof(devices), devices, &ret_size);
ERR_MACRO(err);
num_devices = (int)(ret_size / sizeof(cl_device_id));
for(i = 0; i < num_devices; i++)
{
err = clGetDeviceInfo(devices[i], CL_DEVICE_TYPE, sizeof(device_type), &device_type, NULL);
ERR_MACRO(err);
if(device_type == CL_DEVICE_TYPE_GPU)
{
gpu_found = 1;
err = clBuildProgram(plan->program, 1, &devices[i], "-cl-mad-enable", NULL, NULL);
if (err != CL_SUCCESS)
{
char *build_log;
char devicename[200];
size_t log_size;
err = clGetProgramBuildInfo(plan->program, devices[i], CL_PROGRAM_BUILD_LOG, 0, NULL, &log_size);
ERR_MACRO(err);
build_log = (char *) malloc(log_size + 1);
err = clGetProgramBuildInfo(plan->program, devices[i], CL_PROGRAM_BUILD_LOG, log_size, build_log, NULL);
ERR_MACRO(err);
err = clGetDeviceInfo(devices[i], CL_DEVICE_NAME, sizeof(devicename), devicename, NULL);
ERR_MACRO(err);
fprintf(stdout, "FFT program build log on device %s\n", devicename);
fprintf(stdout, "%s\n", build_log);
free(build_log);
ERR_MACRO(err);
}
}
}
if(!gpu_found)
ERR_MACRO(CL_INVALID_CONTEXT);
err = createKernelList(plan);
ERR_MACRO(err);
// we created program and kernels based on "some max work group size (default 256)" ... this work group size
// may be larger than what kernel may execute with ... if thats the case we need to regenerate the kernel source
// setting this as limit i.e max group size and rebuild.
unsigned int max_kernel_wg_size;
int patching_req = getMaxKernelWorkGroupSize(plan, &max_kernel_wg_size, num_devices, devices);
if(patching_req == -1)
{
ERR_MACRO(err);
}
if(patching_req)
{
destroy_plan(plan);
plan->max_work_item_per_workgroup = max_kernel_wg_size;
goto patch_kernel_source;
}
cl_fft_kernel_info *kInfo = plan->kernel_info;
while(kInfo)
{
plan->num_kernels++;
kInfo = kInfo->next;
}
if(error_code)
*error_code = CL_SUCCESS;
return (clFFT_Plan) plan;
}
void
clFFT_DestroyPlan(clFFT_Plan plan)
{
cl_fft_plan *Plan = (cl_fft_plan *) plan;
if(Plan)
{
destroy_plan(Plan);
clReleaseContext(Plan->context);
free(Plan);
}
}
void clFFT_DumpPlan( clFFT_Plan Plan, FILE *file)
{
size_t gDim, lDim;
FILE *out;
if(!file)
out = stdout;
else
out = file;
cl_fft_plan *plan = (cl_fft_plan *) Plan;
cl_fft_kernel_info *kInfo = plan->kernel_info;
while(kInfo)
{
cl_int s = 1;
getKernelWorkDimensions(plan, kInfo, &s, &gDim, &lDim);
fprintf(out, "Run kernel %s with global dim = {%zd*BatchSize}, local dim={%zd}\n", kInfo->kernel_name, gDim, lDim);
kInfo = kInfo->next;
}
fprintf(out, "%s\n", plan->kernel_string->c_str());
}