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#pragma once
#include <string>
#include <SFML/Graphics.hpp>
#include <unordered_map>
#include <iostream>
#include "Vector4.hpp"
#include <string.h>
#include <memory>
#ifdef linux
#include <CL/cl.h>
#include <CL/opencl.h>
#include <GL/glx.h>
#elif defined _WIN32
#define CL_USE_DEPRECATED_OPENCL_1_2_APIS
#include <CL/cl_gl.h>
#include <CL/cl.h>
#include <CL/opencl.h>
// Note: windows.h must be included before Gl/GL.h
#include <windows.h>
#include <GL/GL.h>
#elif defined TARGET_OS_MAC
#include <OpenCL/opencl.h>
#endif
class OpenCL {
public:
OpenCL();
~OpenCL();
// command queues are associated with a device and context, so for multi-gpu applications you would need
// multiple command queues
// CONTEXTS
// - An OpenCL context is created with one or more devices. Contexts are used by the OpenCL runtime
// for managing objects such as command - queues, memory, program and kernel objects and for executing
// kernels on one or more devices specified in the context.
// - Contexts cannot be created using more than one platform!
bool init();
bool compile_kernel(std::string kernel_path, std::string kernel_name);
// Create an image buffer from an SF texture. Access Type is the read/write specifier required by OpenCL
bool create_image_buffer_from_texture(std::string buffer_name, sf::Texture* texture, cl_int access_type);
// Have CL create and manage the texture for the image buffer. Access Type is the read/write specifier required by OpenCL
bool create_image_buffer(std::string buffer_name, sf::Vector2i size, sf::Vector2f position, cl_int access_type);
bool map_buffer(std::string buffer_name, unsigned int size, void* data = nullptr);
// Create a buffer with CL_MEM_READ_ONLY and CL_MEM_COPY_HOST_PTR
int create_buffer(std::string buffer_name, cl_uint size, void* data);
// Create a buffer with user defined data access flags
int create_buffer(std::string buffer_name, cl_uint size, void* data, cl_mem_flags flags);
int set_kernel_arg(std::string kernel_name, int index, std::string buffer_name);
void run_kernel(std::string kernel_name, sf::Vector2i work_size);
void draw(sf::RenderWindow *window);
class device {
public:
#pragma pack(push, 1)
struct packed_data {
cl_device_type device_type;
cl_uint clock_frequency;
char opencl_version[64];
cl_uint compute_units;
char device_extensions[1024];
char device_name[256];
char platform_name[128];
};
#pragma pack(pop)
device(cl_device_id device_id, cl_platform_id platform_id);
device(const device& d);
void print(std::ostream& stream) const;
void print_packed_data(std::ostream& stream);
cl_device_id getDeviceId() const { return device_id; };
cl_platform_id getPlatformId() const { return platform_id; };
private:
packed_data data;
cl_device_id device_id;
cl_platform_id platform_id;
cl_bool is_little_endian = false;
bool cl_gl_sharing = false;
};
private:
int error = 0;
// The device which we have selected according to certain criteria
cl_platform_id platform_id;
cl_device_id device_id;
// The GL shared context and its subsiquently generated command queue
cl_context context;
cl_command_queue command_queue;
// Maps which contain a mapping from "name" to the host side CL memory object
std::unordered_map<std::string, cl_kernel> kernel_map;
std::unordered_map<std::string, cl_mem> buffer_map;
std::unordered_map<std::string, std::pair<sf::Sprite, std::unique_ptr<sf::Texture>>> image_map;
std::vector<device> device_list;
// Query the hardware on this machine and store the devices
bool aquire_hardware();
// After aquiring hardware, create a shared context using platform specific CL commands
bool create_shared_context();
// Command queues must be created with a valid context
bool create_command_queue();
// Store a cl_mem object in the buffer map <string:name, cl_mem:buffer>
bool store_buffer(cl_mem buffer, std::string buffer_name);
// Using CL release the memory object and remove the KVP associated with the buffer name
bool release_buffer(std::string buffer_name);
bool load_config();
void save_config();
static bool vr_assert(int error_code, std::string function_name);
};