#include "TaskManager.h"
#include "CudaScheduler.h"
#include "ReferencedDmaManager.h"
#include "PreRefDmaManager.h"
#include "SchedTask.h"
#include "CudaError.h"
#include "ListData.h"
#include "SysFunc.h"
#include "gettime.h"
#include "error.h"
#include <stdio.h>
#include <fcntl.h>
#include <sys/stat.h>
#include <string.h>
#include <cuda.h>
#include <map>

using namespace std;

TaskObject cuda_task_list[MAX_TASK_OBJECT];

CudaScheduler::CudaScheduler() {
}

void
CudaScheduler::init_gpu() {
    cuInit(0);
    cuDeviceGetCount(&ret_num_devices);
    if (ret_num_devices == 0) {
        error("no cuda device.");
        exit(EXIT_FAILURE);
    }
    cuDeviceGet(&device, 0);
    /*
      context flog
      CU_CTX_SCHED_AUTO
      CU_CTX_SCHED_SPIN
      CU_CTX_SCHED_YIELD
    */ 
    ret = cuCtxCreate(&context, CU_CTX_SCHED_SPIN, device);
    if (ret!=0) {
        error(convert_error_status(ret));
    }
}

CudaScheduler::~CudaScheduler()
{
    cuCtxDestroy(context);
}

void
CudaScheduler::initCudaBuffer(CudaBufferPtr m) {
    m->allcate_size = 64;
    m->in_size = 0;
    m->out_size = 0;
    m->memin = (CUdeviceptr*)malloc(m->allcate_size*sizeof(CUdeviceptr*));
    m->memout = (CUdeviceptr*)malloc(m->allcate_size*sizeof(CUdeviceptr*));
    ret = cuStreamCreate(&(m->stream), 0);
    if (ret!=0)
        error(convert_error_status(ret));
    m->kernelParams = (void**)malloc(m->allcate_size*2*sizeof(void*));
}

void
CudaScheduler::destroyCudaBuffer(CudaBufferPtr m) {
    free(m->memin);
    free(m->memout);
    free(m->kernelParams);
    ret = cuStreamDestroy(m->stream);
    if (ret!=0)
        error(convert_error_status(ret));
    m->memin = 0;
    m->memout = 0;
    m->in_size = 0;
    m->out_size = 0;
    m->allcate_size = 0;
    m->stream = 0;
    m->kernelParams = 0;
}

void
CudaScheduler::createBuffer(CudaBufferPtr cudabuffer, CUdeviceptr* mem, int param, size_t size) {
    if (param > cudabuffer->allcate_size) {
        cudabuffer->allcate_size *= 2;
        cudabuffer->memin = (CUdeviceptr*)realloc(cudabuffer->memin, cudabuffer->allcate_size*sizeof(CUdeviceptr*));
        cudabuffer->memout = (CUdeviceptr*)realloc(cudabuffer->memout, cudabuffer->allcate_size*sizeof(CUdeviceptr*));
        cudabuffer->kernelParams = (void**)realloc(cudabuffer->kernelParams, cudabuffer->allcate_size*2*sizeof(void*));
    }

    ret = cuMemAlloc(&mem[param], size);
}

#define NOP_REPLY NULL

int
CudaScheduler::read(TaskPtr nextTask, TaskListPtr tasklist) {
    int cur = 0;
    for (;nextTask < tasklist->last(); nextTask = nextTask->next(), cur++) {
        if (STAGE <= cur) return cur;

        /*
         * get flip flag
         * flip : When caluculate on input data, to treat this as a output data
         */
        if (tasklist->self) {
            flag[cur] = tasklist->self->flag;
        } else {
            memset(&flag[cur], 0, sizeof(HTask::htask_flag)); // unnecessary ?
        }

        if(nextTask->command==ShowTime) {
            connector->show_profile(); continue;
        }
        if(nextTask->command==StartProfile) {
            connector->start_profile(); continue;
        }
        if (load_kernel(nextTask->command) == 0) { CudaTaskError(cudabuffer, cur, tasklist, ret); continue; }
        
        ret = cuModuleGetFunction(&kernel[cur], *cuda_task_list[nextTask->command].cudatask->module, cuda_task_list[nextTask->command].name);
        if (ret!=0) { CudaTaskError(cudabuffer, cur, tasklist, ret); continue; }
        
        int param = 0;
        
        // set arg count
        createBuffer(&cudabuffer[cur], cudabuffer[cur].memin, param, sizeof(memaddr)*nextTask->param_count);
        if (ret!=0) { CudaTaskError(cudabuffer, cur, tasklist, ret); continue; }
        
        // parameter is passed as first kernel arg 
        ret = cuMemcpyHtoDAsync(cudabuffer[cur].memin[param], nextTask->param(0), sizeof(memaddr)*nextTask->param_count, cudabuffer[cur].stream);
        if (ret!=0) { CudaTaskError(cudabuffer, cur, tasklist, ret); continue; }
        cudabuffer[cur].kernelParams[param] = &cudabuffer[cur].memin[param];
        param++;
        
        for(int i=0;i<nextTask->inData_count;i++) {
            ListElement *input_buf = nextTask->inData(i);
            if (input_buf->size==0) break;
            if (!transmitted.count(input_buf)) {
                createBuffer(&cudabuffer[cur], cudabuffer[cur].memin, param, input_buf->size);
                if (ret!=0) { CudaTaskError(cudabuffer, cur, tasklist, ret); continue; }
                ret = cuMemcpyHtoDAsync(cudabuffer[cur].memin[param], input_buf->addr, input_buf->size, cudabuffer[cur].stream);
                if (ret!=0) { CudaTaskError(cudabuffer, cur, tasklist, ret); continue; }
                transmitted.insert(make_pair(input_buf, &cudabuffer[cur].memin[param]));
                reverse_map.insert(make_pair(&cudabuffer[cur].memin[param], input_buf));
            }
            cudabuffer[cur].kernelParams[param] = transmitted[input_buf];
            param++;
        }

        cudabuffer[cur].in_size = param; // +1 means param
        
        for(int i = 0; i<nextTask->outData_count;i++) { // set output data
            ListElement *output_buf = nextTask->outData(i);
            if (output_buf->size==0) break;
            if (!transmitted.count(output_buf)) {
                createBuffer(&cudabuffer[cur], cudabuffer[cur].memout, i, output_buf->size);
                if (ret!=0) { CudaTaskError(cudabuffer, cur, tasklist, ret); continue; }
                transmitted.insert(make_pair(output_buf, &cudabuffer[cur].memout[i]));
                reverse_map.insert(make_pair(&cudabuffer[cur].memout[i], output_buf));
            }
            cudabuffer[cur].kernelParams[param] = transmitted[output_buf];
            param++;
        }
        cudabuffer[cur].out_size = param - cudabuffer[cur].in_size; // no buffer on flip, but flip use memout event
    }
    return cur;
}
    
void
CudaScheduler::exec(TaskListPtr tasklist, int cur) {
    for (int i=0;i<cur;i++) {
        if (tasklist->dim > 0) {
            ret = cuLaunchKernel(kernel[i],
                                 tasklist->x, tasklist->y, tasklist->z,
                                 1, 1, 1,
                                 0, cudabuffer[i].stream, cudabuffer[i].kernelParams, NULL);
        } else {
            ret = cuLaunchKernel(kernel[i],
                                 1, 1, 1,
                                 1, 1, 1,
                                 0, cudabuffer[i].stream, cudabuffer[i].kernelParams, NULL);
        }
        if (ret!=0) { CudaTaskError(cudabuffer , i, tasklist, ret); continue; }
    }
}

TaskPtr
CudaScheduler::write(TaskPtr nextTask, TaskListPtr tasklist) {
    int cur = 0;
    for (;nextTask < tasklist->last(); nextTask = nextTask->next(), cur++) {
        if (STAGE <= cur) break;
        // enable flip : not data transfer device to host
        if (flag[cur].flip) continue;
        for(int i=0;i<nextTask->outData_count;i++) { // read output data
            ListElement *output_buf = nextTask->outData(i);
            if (output_buf->size==0) break;
            if (transmitted.count(output_buf)) {
                ret = cuMemcpyDtoHAsync(output_buf->addr, *transmitted[output_buf], output_buf->size, cudabuffer[cur].stream);
                if (ret!=0) { CudaTaskError(cudabuffer, cur, tasklist, ret); continue; }
                reverse_map.erase(transmitted[output_buf]);
                transmitted.erase(output_buf);
            }
        }
    }
    return nextTask;
}

static void
release_buf_event(int cur, CudaScheduler::CudaBufferPtr mem, map<CUdeviceptr*, ListElement*> map) {
    for (int i=0; i<mem[cur].in_size; i++) {
        if (!map.count(&mem[cur].memin[i])) {
            cuMemFree(mem[cur].memin[i]);
            mem[cur].memin[i] = 0;
        }
    }
    for (int i=0; i<mem[cur].out_size; i++) {
        if (!map.count(&mem[cur].memout[i])) {
            cuMemFree(mem[cur].memout[i]);
            mem[cur].memout[i] = 0;
        }
    }
}

void
CudaScheduler::wait_for_event(CudaBufferPtr cudabuffer, TaskListPtr taskList, int cur) {
    for (int i=0;i<cur;i++) {
        if (cuStreamQuery(cudabuffer[i].stream) == CUDA_SUCCESS) continue;
        // all operation is not executed in the stream
        else if (cuStreamQuery(cudabuffer[i].stream) == CUDA_ERROR_NOT_READY){
            // wait for finish
            ret = cuStreamSynchronize(cudabuffer[i].stream);
            if (ret!=0) {
                error(convert_error_status(ret));
            }
        }
    }
    
    if (taskList!=NULL) {
        // unsigned long start = 0;
        // unsigned long end = 0;
        // timestamp 取る方法がない?
    }
    
    for (int i=0;i<cur;i++) {
        if (cudabuffer[i].in_size > 0 || cudabuffer[i].out_size > 0)
            release_buf_event(i, cudabuffer, reverse_map);
    }

    if(reply) {
        connector->mail_write(reply);
        __debug(this, "CUDA %d %s\t%lld\n", taskList->self->cpu_type, (char*)(cuda_task_list[taskList->tasks[0].command].name), taskList->task_end_time-taskList->task_start_time);
        reply = 0;
    }
}

void
CudaScheduler::CudaTaskError(CudaBufferPtr cudabuffer, int cur, TaskListPtr taskList, int ret) {
    error(convert_error_status(ret));
    kernel[cur] = 0;

    wait_for_event(cudabuffer, taskList, cur);
}

void
CudaScheduler::run() {
    init_gpu();
    int cur = 0; // current pipeline index.
    TaskListPtr tasklist = NULL;
    reply = 0;
    
    for (int i = 0; i<STAGE; i++) {
        initCudaBuffer(&cudabuffer[i]);
    }

    memset(&flag, 0, sizeof(HTask::htask_flag)*STAGE);

    for (;;) {
        memaddr param_addr = connector->task_list_mail_read();

        if ((memaddr)param_addr == (memaddr)MY_SPE_COMMAND_EXIT) {
            for (int i = 0; i<STAGE; i++) {
                destroyCudaBuffer(&cudabuffer[i]);
            }
            return;
        }

        (*connector->start_dmawait_profile)(&(connector->start_time));
        while (param_addr) {
            // since we are on the same memory space, we don't has to use dma_load here
            tasklist = (TaskListPtr)connector->dma_load(this, param_addr,
                                                        sizeof(TaskList), DMA_READ_TASKLIST);
            tasklist->task_start_time = 0;
            for (TaskPtr nextTask = tasklist->tasks; nextTask < tasklist->last();) {
                cur = read(nextTask, tasklist);
                exec(tasklist, cur);
                nextTask = write(nextTask, tasklist);
                wait_for_event(cudabuffer, tasklist, cur);
            }
            reply = (memaddr)tasklist->waiter;
            param_addr = (memaddr)tasklist->next;
        }
        wait_for_event(cudabuffer, tasklist, 0);
        
        unsigned long long wait = 0;
        (*connector->end_dmawait_profile)(&wait, &(connector->start_time), &(connector->stop_time));
        connector->mail_write((memaddr)MY_SPE_STATUS_READY);
    }
    /* NOT REACHED */
}

int
not_ready(SchedTask* smanager, void* r, void *w)
{
    smanager->printf("GPU task not ready %d\n", smanager->atask->command);
    return 0;
}

/*
 * kernel file open and build program
 */
int
CudaScheduler::load_kernel(int cmd)
{
    if (cuda_task_list[cmd].run == null_run) {
        return 1;
    }

    if (cuda_task_list[cmd].cudatask == 0 || cuda_task_list[cmd].cudatask->filename == 0) {
        fprintf(stderr, "CUDA module %d not defined.\n",cmd);
        return 0;
    }

    CUmodule* module = new CUmodule;
    ret = cuModuleLoad(module, cuda_task_list[cmd].cudatask->filename);
    
    if(ret!=0) {
        error(convert_error_status(ret));
    }
    cuda_task_list[cmd].cudatask->module = module;
    cuda_task_list[cmd].run = null_run; // kernel is ready
    return 1;
}

// regist kernel file name
void
cuda_register_task(int cmd, const char* filename, const char* functionname)
{
    cuda_task_list[cmd].run = not_ready;  // not yet ready
    cuda_task_list[cmd].load = null_loader;
    cuda_task_list[cmd].wait = null_loader;
    cuda_task_list[cmd].name = functionname;
    cuda_task_list[cmd].cudatask->filename = (const char*)filename;
}

/* end */