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Grid.cpp
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Grid.cpp
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#include "Grid.h"
// for test
extern Trajectory* tradb;
extern void* baseAddrGPU;
using namespace std;
#ifdef WIN32
MyTimer timer;
#else
#endif
int getIdxFromXY(int x, int y)
{
if (x < 0 || y < 0) {
return -1; //太小超界
}
int lenx, leny;
if (x == 0)
lenx = 1;
else
{
lenx = int(log2(x)) + 1;
}
if (y == 0)
leny = 1;
else
leny = int(log2(y)) + 1;
int result = 0;
int xbit = 1, ybit = 1;
for (int i = 1; i <= 2 * max(lenx, leny); i++) // 标识向左移动多少位
{
if ((i & 1) == 1) // 二进制末尾为1 该取列号
{
result += (x >> (xbit - 1) & 1) * (1 << (i - 1)); // x >> (xbit - 1) & 1 巧妙 运用位运算 移位运算
xbit = xbit + 1;
}
else // 二进制末尾为0 该取行号
{
result += (y >> (ybit - 1) & 1) * (1 << (i - 1));
ybit = ybit + 1;
}
}
return result;
}
int Grid::GetIDfromXYTest(int x, int y) {
return getIdxFromXY(x, y);
}
//确认无误
int Grid::WhichCellPointIn(SamplePoint p)
{
//注意cell编号是从(xmin,ymax)开始的，而不是(xmin,ymin)
int row = (int)((range.ymax - p.lat) / cell_size); //从0开始
int col = (int)((p.lon - range.xmin) / cell_size); //从0开始
return getIdxFromXY(col, row);
}
Grid::Grid()
{
range = MBB(0, 0, 0, 0);
cellnum = 0;
cell_size = 0;
cellNum_axis = 0;
cellPtr = NULL;
allPoints = NULL;
allPointsPtrGPU = NULL;
}
Grid::Grid(const MBB& mbb, float val_cell_size, int VITURAL_CELL_PARAM)
{
this->nodeNum = 0;
this->VITURAL_CELL_PARAM = VITURAL_CELL_PARAM;
range = mbb;
cell_size = val_cell_size;
int divideNumOnX = (int)((mbb.xmax - mbb.xmin) / val_cell_size) + 1;
int divideNumOnY = (int)((mbb.ymax - mbb.ymin) / val_cell_size) + 1;
int maxValue = max(divideNumOnX, divideNumOnY);
cellNum_axis = maxValue >> (int(log2(maxValue))) << (int(log2(maxValue)) + 1);
cout << cellNum_axis << endl;
cellnum = cellNum_axis * cellNum_axis;
cellPtr = new Cell[cellnum];
this->testCnt = 0;
for (int i = 0; i <= cellNum_axis - 1; i++)
{
for (int j = 0; j <= cellNum_axis - 1; j++)
{
int cell_idx = getIdxFromXY(j, i);
cellPtr[cell_idx].initial(i, j, MBB(range.xmin + cell_size * j, range.ymax - cell_size * (i + 1), range.xmin + cell_size * (j + 1), range.ymax - cell_size * (i)));
}
}
}
Grid::~Grid()
{
}
int Grid::buildQuadTree(int level, int id, QuadtreeNode* pNode, QuadtreeNode* parent)
{
int totalLevel = int(log2(this->cellnum) / log2(4));
int totalPoints = 0;
for (int i = id * int(pow(4, (totalLevel - level))); i <= (id + 1) * int(pow(4, (totalLevel - level))) - 1; i++)
{
totalPoints += this->cellPtr[i].totalPointNum;
}
pNode->mbb = MBB(this->cellPtr[id * int(pow(4, (totalLevel - level)))].mbb.xmin, this->cellPtr[(id + 1) * int(pow(4, (totalLevel - level))) - 1].mbb.ymin, this->cellPtr[(id + 1) * int(pow(4, (totalLevel - level))) - 1].mbb.xmax, this->cellPtr[id * int(pow(4, (totalLevel - level)))].mbb.ymax);
pNode->numPoints = totalPoints;
pNode->NodeID = id;
pNode->parent = parent;
pNode->level = level;
if ((totalPoints < MAXPOINTINNODE) || (level == totalLevel))
{
pNode->isLeaf = true;
pNode->DL = NULL;
pNode->DR = NULL;
pNode->UL = NULL;
pNode->UR = NULL;
return 0;
}
else
{
this->nodeNum += 4;
pNode->isLeaf = false;
pNode->UL = (QuadtreeNode*)malloc(sizeof(QuadtreeNode));
this->buildQuadTree(level + 1, id << 2, pNode->UL, pNode);
pNode->UR = (QuadtreeNode*)malloc(sizeof(QuadtreeNode));
this->buildQuadTree(level + 1, (id << 2) + 1, pNode->UR, pNode);
pNode->DL = (QuadtreeNode*)malloc(sizeof(QuadtreeNode));
this->buildQuadTree(level + 1, (id << 2) + 2, pNode->DL, pNode);
pNode->DR = (QuadtreeNode*)malloc(sizeof(QuadtreeNode));
this->buildQuadTree(level + 1, (id << 2) + 3, pNode->DR, pNode);
return 0;
}
}
//把轨迹t打碎成子轨迹，添加到cell里面
//这一步仅仅是把子轨迹放进了cell里面，组成一个个item
int Grid::addTrajectoryIntoCell(Trajectory& t)
{
if (t.length == 0)
return 1;//空轨迹
SamplePoint p = t.points[0];
int lastCellNo = WhichCellPointIn(p);
int lastCellStartIdx = 0;
int nowCellNo;
//cell based traj生成，记得转换后free！
vector<int>* tempCellBasedTraj = new vector<int>;
tempCellBasedTraj->reserve(1048577);
int tempCellNum = 0;
for (int i = 0; i <= t.length - 1; i++)
{
p = t.points[i];
nowCellNo = WhichCellPointIn(p);
if (i == t.length - 1)
{
//到最后一条，发现这个cell也是上个cell就是最后一个cell了，添加之
if (lastCellNo == nowCellNo)
{
tempCellNum++;
tempCellBasedTraj->push_back(nowCellNo);
cellPtr[nowCellNo].addSubTra(t.tid, lastCellStartIdx, i, i - lastCellStartIdx + 1);
int vituralCellNo = nowCellNo >> VITURAL_CELL_PARAM; //虚格子
this->freqVectors.addPointToFVTable(t.tid, i - lastCellStartIdx + 1, vituralCellNo);
}
//否则，上一个和这个cell都要添加
else
{
tempCellNum += 2;
tempCellBasedTraj->push_back(lastCellNo);
tempCellBasedTraj->push_back(nowCellNo);
cellPtr[lastCellNo].addSubTra(t.tid, lastCellStartIdx, i - 1, i - 1 - lastCellStartIdx + 1);
int vituralCellNo = lastCellNo >> VITURAL_CELL_PARAM; //虚格子
this->freqVectors.addPointToFVTable(t.tid, i - 1 - lastCellStartIdx + 1, vituralCellNo);
cellPtr[nowCellNo].addSubTra(t.tid, i, i, 1);
vituralCellNo = nowCellNo >> VITURAL_CELL_PARAM;
this->freqVectors.addPointToFVTable(t.tid, 1, vituralCellNo);
}
}
else
{
if (lastCellNo == nowCellNo)
continue;
else
{
// 终结一条子轨迹，开始下一条子轨迹
//cellTra里面加一条
tempCellNum++;
tempCellBasedTraj->push_back(lastCellNo);
//SubTra添加
//printf("cell:%d\n", lastCellNo);
cellPtr[lastCellNo].addSubTra(t.tid, lastCellStartIdx, i - 1, i - 1 - lastCellStartIdx + 1);
int vituralCellNo = lastCellNo >> VITURAL_CELL_PARAM; //虚格子
this->freqVectors.addPointToFVTable(t.tid, i - 1 - lastCellStartIdx + 1, vituralCellNo);
lastCellNo = nowCellNo;
lastCellStartIdx = i;
}
}
}
this->cellBasedTrajectory[t.tid].length = tempCellNum;
this->cellBasedTrajectory[t.tid].cellNo = (int*)malloc(sizeof(int) * tempCellNum);
if (this->cellBasedTrajectory[t.tid].cellNo == NULL) throw("alloc error");
for (int i = 0; i <= tempCellNum - 1; i++)
{
this->cellBasedTrajectory[t.tid].cellNo[i] = tempCellBasedTraj->at(i);
}
this->cellBasedTrajectory[t.tid].trajLength = t.length;
delete tempCellBasedTraj;
return 0;
}
int Grid::addDatasetToGrid(Trajectory* db, int traNum)
{
this->trajNum = traNum;
//生成frequency vector
this->freqVectors.initFVTable(traNum, (this->cellnum)>> this->VITURAL_CELL_PARAM); //注意这里是虚格子的个数
//注意，轨迹编号从1开始
this->cellBasedTrajectory.resize(traNum + 1); //扩大cellbasedtraj的规模，加轨迹的时候可以直接用
int pointCount = 0;
for (int i = 1; i <= traNum; i++)
{
addTrajectoryIntoCell(db[i]);
}
for (int i = 0; i <= cellnum - 1; i++)
{
cellPtr[i].buildSubTraTable();
pointCount += cellPtr[i].totalPointNum;
}
this->totalPointNum = pointCount;
this->root = (QuadtreeNode*)malloc(sizeof(QuadtreeNode));
this->buildQuadTree(0, 0, this->root, NULL);
this->allPoints = (SPoint*)malloc(sizeof(SPoint) * (this->totalPointNum));
pointCount = 0;
for (int i = 0; i <= cellnum - 1; i++)
{
cellPtr[i].pointRangeStart = pointCount;
for (int j = 0; j <= cellPtr[i].subTraNum - 1; j++)
{
//for each subTra, add Points to AllPoints
cellPtr[i].subTraTable[j].idxInAllPointsArray = pointCount;
for (int k = cellPtr[i].subTraTable[j].startpID; k <= cellPtr[i].subTraTable[j].endpID; k++)
{
allPoints[pointCount].tID = cellPtr[i].subTraTable[j].traID;
allPoints[pointCount].x = tradb[allPoints[pointCount].tID].points[k].lon;
allPoints[pointCount].y = tradb[allPoints[pointCount].tID].points[k].lat;
//allPoints[pointCount].time = tradb[allPoints[pointCount].tID].points[k].time;
pointCount++;
}
}
cellPtr[i].pointRangeEnd = pointCount - 1;
if (cellPtr[i].pointRangeEnd - cellPtr[i].pointRangeStart + 1 != cellPtr[i].totalPointNum)
cerr << "Grid.cpp: something wrong in total point statistic" << endl;
}
for (int i = 1; i <= this->trajNum; i++)
{
this->cellBasedTrajectory[i].startIdx = (int*)malloc(sizeof(int) * this->cellBasedTrajectory[i].length);
this->cellBasedTrajectory[i].numOfPointInCell = (short*)malloc(sizeof(short) * this->cellBasedTrajectory[i].length);
int* tempCntForTraj = (int*)malloc(sizeof(int) * this->cellnum);
memset(tempCntForTraj, 0, sizeof(int) * this->cellnum);
for (int cellidx = 0; cellidx <= this->cellBasedTrajectory[i].length - 1; cellidx++)
{
int nowCellID = this->cellBasedTrajectory[i].cellNo[cellidx];
int j, cnt;
for (j = 0 , cnt = 0; cnt <= tempCntForTraj[nowCellID]; j++)
{
if (this->cellPtr[nowCellID].subTraTable[j].traID == i)
{
cnt++;
}
}
j--;
//choose j; //选择第j项subTra，但是这里面还是没有起始点的信息，考虑回来把point的信息加进subtraTable。。。反正最后要把subTraTable给free掉
this->cellBasedTrajectory[i].startIdx[cellidx] = this->cellPtr[nowCellID].subTraTable[j].idxInAllPointsArray;
this->cellBasedTrajectory[i].numOfPointInCell[cellidx] = this->cellPtr[nowCellID].subTraTable[j].numOfPoint;
tempCntForTraj[nowCellID]++;
}
free(tempCntForTraj);
}
// Transfer FV to GPU
//this->freqVectors.transferFVtoGPU();
////Delta Encoding的cell连续存储
//this->allPointsDeltaEncoding = (DPoint*)malloc(sizeof(DPoint)*(this->totalPointNum));
//pointCount = 0;
//for (int i = 0; i <= cellnum - 1; i++) {
// cellPtr[i].pointRangeStart = pointCount;
// for (int j = 0; j <= cellPtr[i].subTraNum - 1; j++) {
// for (int k = cellPtr[i].subTraTable[j].startpID; k <= cellPtr[i].subTraTable[j].endpID; k++) {
// allPointsDeltaEncoding[pointCount].tID = cellPtr[i].subTraTable[j].traID;
// allPointsDeltaEncoding[pointCount].x = short(int((tradb[allPointsDeltaEncoding[pointCount].tID].points[k].lon)*1000000)-cellPtr[i].anchorPointX);
// allPointsDeltaEncoding[pointCount].y = short(int((tradb[allPointsDeltaEncoding[pointCount].tID].points[k].lat)*1000000)-cellPtr[i].anchorPointY);
// pointCount++;
// }
// }
// cellPtr[i].pointRangeEnd = pointCount - 1;
// if (cellPtr[i].pointRangeEnd - cellPtr[i].pointRangeStart + 1 != cellPtr[i].totalPointNum)
// cerr << "Grid.cpp: something wrong in total point statistic" << endl;
//}
//把生成好的allpoints放到GPU内
//putCellDataSetIntoGPU(this->allPoints, this->allPointsPtrGPU, this->totalPointNum);
return 0;
}
int Grid::writeCellsToFile(int* cellNo, int cellNum, string file)
// under editing....
{
fout.open(file, ios_base::out);
for (int i = 0; i <= cellNum - 1; i++)
{
int outCellIdx = cellNo[i];
cout << outCellIdx << ": " << "[" << cellPtr[outCellIdx].mbb.xmin << "," << cellPtr[outCellIdx].mbb.xmax << "," << cellPtr[outCellIdx].mbb.ymin << "," << cellPtr[outCellIdx].mbb.ymax << "]" << endl;
for (int j = 0; j <= cellPtr[outCellIdx].subTraNum - 1; j++)
{
int tid = cellPtr[outCellIdx].subTraTable[j].traID;
int startpid = cellPtr[outCellIdx].subTraTable[j].startpID;
int endpid = cellPtr[outCellIdx].subTraTable[j].endpID;
for (int k = startpid; k <= endpid; k++)
{
cout << tradb[tid].points[k].lat << "," << tradb[tid].points[k].lon << ";";
}
cout << endl;
}
}
return 0;
}
int Grid::rangeQueryBatch(MBB* bounds, int rangeNum, CPURangeQueryResult* ResultTable, int* resultSetSize)
{
for (int i = 0; i <= rangeNum - 1; i++)
{
ResultTable[i].resize(this->trajNum + 1);
}
#ifdef CHECK_CORRECT
for (int i = 0; i <= rangeNum - 1;i++)
{
for (int j = 0; j <= this->trajNum + 1;j++)
{
ResultTable[i][j] = 0;
}
}
#endif
int totalLevel = int(log2(this->cellnum) / log2(4));
for (int i = 0; i <= rangeNum - 1; i++)
{
//int candidateNodeNum = 0;
vector<QuadtreeNode*> cells;
findMatchNodeInQuadTree(this->root, bounds[i], &cells);
//printf("%d", cells.size());
for (vector<QuadtreeNode*>::iterator iterV = cells.begin(); iterV != cells.end(); iterV++)
{
int nodeID = (*iterV)->NodeID;
int nodeLevel = (*iterV)->level;
int firstCellID = nodeID * int(pow(4, (totalLevel - nodeLevel)));
int lastCellID = (nodeID + 1) * int(pow(4, (totalLevel - nodeLevel))) - 1;
for (int cellID = firstCellID; cellID <= lastCellID; cellID++)
{
int anchorX = this->cellPtr[cellID].anchorPointX;
int anchorY = this->cellPtr[cellID].anchorPointY;
for (int idx = this->cellPtr[cellID].pointRangeStart; idx <= this->cellPtr[cellID].pointRangeEnd; idx++)
{
//compress
//float realX = float(allPointsDeltaEncoding[idx].x + anchorX) / 1000000;
//float realY = float(allPointsDeltaEncoding[idx].y + anchorY) / 1000000;
// no compress
float realX = allPoints[idx].x;
float realY = allPoints[idx].y;
int tID = allPoints[idx].tID;
if (bounds[i].pInBox(realX, realY))
{
ResultTable[i][tID] = TRUE;
}
}
}
}
}
//for (int jobID = 0; jobID <= rangeNum - 1; jobID++)
//{
// for (int traID = 1; traID <= (this->trajNum); traID++)
// {
// if (resultsReturned[jobID * (this->trajNum + 1) + traID] == 1)
// {
// out << "job " << jobID << "find" << traID << endl;
// }
// }
//}
return 0;
}
int Grid::rangeQueryBatchMultiThread(MBB* bounds, int rangeNum, CPURangeQueryResult* ResultTable, int* resultSetSize)
{
/*
// way2:
vector<thread> threads_RQ;
const int device_num = 16; // 这里用了16！！！ 说明MCPU 知道的 那20估计是弄错了 含着CPU 会满载么
int nowidx = 0;
// 整个batch平分为16份
for (int device_idx = 0; device_idx <= device_num - 1; device_idx++)
{
int boundNum = rangeNum / device_num + 1;
if (nowidx + boundNum >= rangeNum)
boundNum = rangeNum - nowidx;
threads_RQ.push_back(thread(std::mem_fn(&Grid::rangeQueryBatch), this, &bounds[nowidx], boundNum, &ResultTable[nowidx], resultSetSize));
nowidx += boundNum;
}
std::for_each(threads_RQ.begin(), threads_RQ.end(), std::mem_fn(&std::thread::join));
*/
// way1:
vector<thread> threads_RQ;
for (int qID = 0; qID <= rangeNum - 1; qID++)
{
threads_RQ.push_back(thread(std::mem_fn(&Grid::rangeQueryBatch), this, &bounds[qID], 1, &ResultTable[qID], resultSetSize));// resultSetSize 没用到
//threads_RQ.push_back(thread(std::mem_fn(&Grid::SimilarityMultiThreadHandler), this, queryQueue, qTra, 1, EDRCalculated, kValue, qID));
//threads_EDR.push_back(thread(std::mem_fn(&Grid::FDCalculateParallelHandeler), this, &queryQueue[qID], &freqVectors[qID]));
}
std::for_each(threads_RQ.begin(), threads_RQ.end(), std::mem_fn(&std::thread::join)); // threads_FD已经指明
return 0;
}
int Grid::findMatchNodeInQuadTree(QuadtreeNode* node, MBB& bound, vector<QuadtreeNode*>* cells)
{
if (node->isLeaf)
{
cells->push_back(node);
}
else
{
if (bound.intersect(node->UL->mbb))
findMatchNodeInQuadTree(node->UL, bound, cells);
if (bound.intersect(node->UR->mbb))
findMatchNodeInQuadTree(node->UR, bound, cells);
if (bound.intersect(node->DL->mbb))
findMatchNodeInQuadTree(node->DL, bound, cells);
if (bound.intersect(node->DR->mbb))
findMatchNodeInQuadTree(node->DR, bound, cells);
}
return 0;
}
int Grid::rangeQueryBatchGPU(MBB* bounds, int rangeNum, CPURangeQueryResult* ResultTable, int* resultSetSize, RangeQueryStateTable* stateTableAllocate, int device_idx)
{
#ifdef CHECK_CORRECT
for (int i = 0; i <= rangeNum - 1; i++)
{
ResultTable[i].resize(this->trajNum + 1);
}
for (int i = 0; i <= rangeNum - 1; i++)
{
for (int j = 0; j <= this->trajNum; j++)
{
ResultTable[i][j] = 0;
}
}
#endif
MyTimer timer;
// timer.start();
CUDA_CALL(cudaSetDevice(device_idx));
this->stateTableRange[device_idx] = stateTableAllocate;
this->stateTableLength[device_idx] = 0;
this->nodeAddrTableLength[device_idx] = 0;
// for each query, generate the nodes:
cudaStream_t stream;
cudaStreamCreate(&stream);
// *************************** step1: filtering ***************************
for (int i = 0; i <= rangeNum - 1; i++)
{
findMatchNodeInQuadTreeGPU(root, bounds[i], NULL, stream, i, device_idx);
}
int maxPointNum = 0;
for (int i = 0; i <= this->stateTableLength[device_idx] - 1; i++)
{
if (stateTableAllocate[i].candidatePointNum > maxPointNum)
maxPointNum = stateTableAllocate[i].candidatePointNum;
}
// timer.stop();
// cout << "Time 1:" << timer.elapse() << "ms" << endl;
// *************************** step2: verification ***************************
// timer.start();
CUDA_CALL(cudaMemcpyAsync(this->stateTableGPU[device_idx], stateTableAllocate, sizeof(RangeQueryStateTable)*this->stateTableLength[device_idx],
cudaMemcpyHostToDevice, stream));
// timer.stop();
// cout << "Time 2:" << timer.elapse() << "ms" << endl;
//传递完成，开始调用kernel查询
uint8_t* resultsReturned = (uint8_t*)malloc(sizeof(uint8_t) * (this->trajNum + 1) * rangeNum);
// timer.start();
cudaRangeQueryTestHandler((RangeQueryStateTable*)this->stateTableGPU[device_idx], this->stateTableLength[device_idx], resultsReturned, this->trajNum + 1, rangeNum, stream);
//ofstream fp("queryResult(GTS).txt", ios_base::out);
#ifdef CHECK_CORRECT
for (int jobID = 0; jobID <= rangeNum - 1; jobID++)
{
for (int traID = 0; traID <= this->trajNum; traID++)
{
if (resultsReturned[jobID * (this->trajNum + 1) + traID] == 1)
{
ResultTable[jobID][traID] = TRUE;
}
}
}
#endif
//for (vector<uint8_t>::iterator iter = resultsReturned.begin(); iter != resultsReturned.end(); iter++) {
// //cout << (*iter) << endl;
// //printf("%d\n", *iter);
//}
// timer.stop();
// cout << "Time 3:" << timer.elapse() << "ms" << endl;
//FILE *fp = fopen("resultQuery.txt", "w+");
//for (int i = 0; i <= stateTableLength - 1; i++) {
// for (int j = 0; j <= stateTableAllocate[i].candidatePointNum - 1; j++) {
// if ((resultsReturned[i*maxPointNum + j]) == (uint8_t)(1)) {
// fprintf(fp,"%d\n", stateTableAllocate[i].startIdxInAllPoints + j);
// fprintf(fp,"%f,%f\n", allPoints[stateTableAllocate[i].startIdxInAllPoints + j].x, allPoints[stateTableAllocate[i].startIdxInAllPoints + j].y);
// }
// }
//}
//查询结束，善后，清空stateTable，清空gpu等
cudaStreamDestroy(stream);
return 0;
}
int Grid::rangeQueryBatchGPUWithoutMorton(MBB * bounds, int rangeNum, CPURangeQueryResult * ResultTable, int * resultSetSize, RangeQueryStateTable * stateTableAllocate, int device_idx)
{
#ifdef CHECK_CORRECT
for (int i = 0; i <= rangeNum - 1; i++)
{
ResultTable[i].resize(this->trajNum + 1);
}
for (int i = 0; i <= rangeNum - 1; i++)
{
for (int j = 0; j <= this->trajNum; j++)
{
ResultTable[i][j] = 0;
}
}
#endif
MyTimer timer;
// timer.start();
CUDA_CALL(cudaSetDevice(device_idx));
this->stateTableRange[device_idx] = stateTableAllocate;
this->stateTableLength[device_idx] = 0;
this->nodeAddrTableLength[device_idx] = 0;
vector<int> blockOffsetInData, blockOffsetNum, blockOffsetOfOffset, blockLength;
// for each query, generate the nodes:
cudaStream_t stream;
cudaStreamCreate(&stream);
for (int i = 0; i <= rangeNum - 1; i++)
{
findMatchNodeInQuadTreeGPUWithoutMorton(root, bounds[i], NULL, stream, i, device_idx,
blockOffsetInData, blockOffsetNum, blockOffsetOfOffset, blockLength);
}
//printf("StateTableLength:%d",this->stateTableLength);
//stateTable中点的数目的最大值
// FILE* testFile = fopen("freq.txt", "w+");
int maxPointNum = 0;
for (int i = 0; i <= this->stateTableLength[device_idx] - 1; i++)
{
if (stateTableAllocate[i].candidatePointNum > maxPointNum)
maxPointNum = stateTableAllocate[i].candidatePointNum;
//fprintf(testFile, "%d ", stateTableAllocate[i].candidatePointNum);
}
//交给GPU进行并行查询
//先传递stateTable
// timer.stop();
// cout << "Time 1:" << timer.elapse() << "ms" << endl;
// timer.start();
// transfer offset of uncontinuous part
size_t allSpaceForOffsetContinuous = blockOffsetInData.size() + blockOffsetNum.size() +
blockOffsetOfOffset.size() + blockLength.size();
// printf("%zd", allSpaceForOffsetContinuous);
int* startGPUTemp = NULL;
CUDA_CALL(cudaMalloc((void**)&startGPUTemp, sizeof(int)*allSpaceForOffsetContinuous));
void* GPUTempPtr = (void*)startGPUTemp;
int* blockOffsetInDataGPU=startGPUTemp, *blockOffsetNumGPU, *blockOffsetOfOffsetGPU, *blockLengthGPU;
CUDA_CALL(cudaMemcpyAsync(startGPUTemp, &blockOffsetInData[0], sizeof(int)*blockOffsetInData.size(),cudaMemcpyHostToDevice,stream));
startGPUTemp += blockOffsetInData.size();
blockOffsetNumGPU = startGPUTemp;
CUDA_CALL(cudaMemcpyAsync(startGPUTemp, &blockOffsetNum[0], sizeof(int)*blockOffsetNum.size(), cudaMemcpyHostToDevice, stream));
startGPUTemp += blockOffsetNum.size();
blockOffsetOfOffsetGPU = startGPUTemp;
CUDA_CALL(cudaMemcpyAsync(startGPUTemp, &blockOffsetOfOffset[0], sizeof(int)*blockOffsetOfOffset.size(), cudaMemcpyHostToDevice, stream));
startGPUTemp += blockOffsetOfOffset.size();
blockLengthGPU = startGPUTemp;
CUDA_CALL(cudaMemcpyAsync(startGPUTemp, &blockLength[0], sizeof(int)*blockLength.size(), cudaMemcpyHostToDevice, stream));
CUDA_CALL(cudaMemcpyAsync(this->stateTableGPU[device_idx], stateTableAllocate, sizeof(RangeQueryStateTable)*this->stateTableLength[device_idx],
cudaMemcpyHostToDevice, stream));
//传递完成，开始调用kernel查询
uint8_t* resultsReturned = (uint8_t*)malloc(sizeof(uint8_t) * (this->trajNum + 1) * rangeNum);
// timer.stop();
// cout << "Time 2:" << timer.elapse() << "ms" << endl;
// timer.start();
//cudaRangeQueryTestHandler((RangeQueryStateTable*)this->stateTableGPU[device_idx],
// this->stateTableLength[device_idx], resultsReturned, this->trajNum + 1, rangeNum, stream);
cudaRangeQueryTestHandlerNonMorton((RangeQueryStateTable*)this->stateTableGPU[device_idx],
this->stateTableLength[device_idx], resultsReturned, this->trajNum + 1, rangeNum, stream,
blockOffsetInDataGPU, blockLengthGPU, blockOffsetNumGPU, blockOffsetOfOffsetGPU);
//ofstream fp("queryResult(GTS).txt", ios_base::out);
#ifdef CHECK_CORRECT
for (int jobID = 0; jobID <= rangeNum - 1; jobID++)
{
for (int traID = 0; traID <= this->trajNum; traID++)
{
if (resultsReturned[jobID * (this->trajNum + 1) + traID] == 1)
{
ResultTable[jobID][traID] = TRUE;
}
}
}
#endif
//for (vector<uint8_t>::iterator iter = resultsReturned.begin(); iter != resultsReturned.end(); iter++) {
// //cout << (*iter) << endl;
// //printf("%d\n", *iter);
//}
// timer.stop();
// cout << "Time 3:" << timer.elapse() << "ms" << endl;
//FILE *fp = fopen("resultQuery.txt", "w+");
//for (int i = 0; i <= stateTableLength - 1; i++) {
// for (int j = 0; j <= stateTableAllocate[i].candidatePointNum - 1; j++) {
// if ((resultsReturned[i*maxPointNum + j]) == (uint8_t)(1)) {
// fprintf(fp,"%d\n", stateTableAllocate[i].startIdxInAllPoints + j);
// fprintf(fp,"%f,%f\n", allPoints[stateTableAllocate[i].startIdxInAllPoints + j].x, allPoints[stateTableAllocate[i].startIdxInAllPoints + j].y);
// }
// }
//}
//查询结束，善后，清空stateTable，清空gpu等
cudaStreamDestroy(stream);
CUDA_CALL(cudaFree(GPUTempPtr));
return 0;
}
int Grid::rangeQueryBatchMultiGPU(MBB* bounds, int rangeNum, CPURangeQueryResult* ResultTable, int* resultSetSize)
{
MyTimer timer;
int device_num = 2;
vector<thread> threads_RQ;
int rangeNumGPU[2];
rangeNumGPU[0] = rangeNum / 2;
rangeNumGPU[1] = rangeNum - rangeNumGPU[0];
int startIdx[2];
startIdx[0] = 0;
startIdx[1] = rangeNumGPU[0];
void* allocatedGPUMem[2] = { NULL };
vector<RangeQueryStateTable> stateTableRange[2];
stateTableRange[0].resize(rangeNum * 50000);
stateTableRange[1].resize(rangeNum * 50000);
for (int device_idx=0; device_idx <= device_num - 1; device_idx++)
{
// this->freqVectors.formPriorityQueue(&queryQueue[qID], &freqVectors[qID]);
CUDA_CALL(cudaSetDevice(device_idx));
CUDA_CALL(cudaMalloc((void**)&this->baseAddrRange[device_idx], (long long int)BIG_MEM * 1024 * 1024));
CUDA_CALL(cudaMalloc((void**)&this->stateTableGPU[device_idx], (long long int)SMALL_MEM * 1024 * 1024));
allocatedGPUMem[device_idx] = this->baseAddrRange[device_idx];
threads_RQ.push_back(thread(std::mem_fn(&Grid::rangeQueryBatchGPU), this, &bounds[startIdx[device_idx
]], rangeNumGPU[device_idx], &ResultTable[startIdx[device_idx]], resultSetSize, &stateTableRange[device_idx][0], device_idx));
}
timer.start();
std::for_each(threads_RQ.begin(), threads_RQ.end(), std::mem_fn(&std::thread::join));
timer.stop();
cout << "Dual GPU Time:" << timer.elapse() << "ms" << endl;
for (int device_idx = 0; device_idx <= device_num - 1; device_idx++)
{
CUDA_CALL(cudaFree(allocatedGPUMem[device_idx]));
CUDA_CALL(cudaFree(this->stateTableGPU[device_idx]));
}
return 0;
}
int Grid::rangeQueryBatchMultiGPUWithoutMorton(MBB* bounds, int rangeNum, CPURangeQueryResult* ResultTable, int* resultSetSize)
{
MyTimer timer;
int device_num = 2;
vector<thread> threads_RQ;
int rangeNumGPU[2];
rangeNumGPU[0] = rangeNum / 2;
rangeNumGPU[1] = rangeNum - rangeNumGPU[0];
int startIdx[2];
startIdx[0] = 0;
startIdx[1] = rangeNumGPU[0];
void* allocatedGPUMem[2] = { NULL };
vector<RangeQueryStateTable> stateTableRange[2];
stateTableRange[0].resize(rangeNum * 50000);
stateTableRange[1].resize(rangeNum * 50000);
for (int device_idx = 0; device_idx <= device_num - 1; device_idx++)
{
// this->freqVectors.formPriorityQueue(&queryQueue[qID], &freqVectors[qID]);
CUDA_CALL(cudaSetDevice(device_idx));
CUDA_CALL(cudaMalloc((void**)&this->baseAddrRange[device_idx], (long long int)BIG_MEM * 1024 * 1024));
CUDA_CALL(cudaMalloc((void**)&this->stateTableGPU[device_idx], (long long int)SMALL_MEM * 1024 * 1024));
allocatedGPUMem[device_idx] = this->baseAddrRange[device_idx];
threads_RQ.push_back(thread(std::mem_fn(&Grid::rangeQueryBatchGPUWithoutMorton), this, &bounds[startIdx[device_idx
]], rangeNumGPU[device_idx], &ResultTable[startIdx[device_idx]], resultSetSize, &stateTableRange[device_idx][0], device_idx));
}
timer.start();
std::for_each(threads_RQ.begin(), threads_RQ.end(), std::mem_fn(&std::thread::join));
timer.stop();
cout << "Dual GPU Time:" << timer.elapse() << "ms" << endl;
for (int device_idx = 0; device_idx <= device_num - 1; device_idx++)
{
CUDA_CALL(cudaFree(allocatedGPUMem[device_idx]));
CUDA_CALL(cudaFree(this->stateTableGPU[device_idx]));
}
return 0;
}
int Grid::findMatchNodeInQuadTreeGPU(QuadtreeNode* node, MBB& bound, vector<QuadtreeNode*>* cells, cudaStream_t stream, int queryID, int device_idx)
{
int totalLevel = int(log2(this->cellnum) / log2(4));
if (node->isLeaf)
{
// printf("level:%d,node:%d\n", node->level, node->NodeID);
int startCellID = node->NodeID * int(pow(4, (totalLevel - node->level)));
// printf("startcellID:%d\n", startCellID);
int startIdx = this->cellPtr[startCellID].pointRangeStart;
int pointNum = node->numPoints;
SPoint* dataPtr = NULL;
//如果gpu内存中没有该node的信息
if (this->nodeAddrTable[device_idx].find(startCellID) == this->nodeAddrTable[device_idx].end())
{
CUDA_CALL(cudaMemcpyAsync(this->baseAddrRange[device_idx], &(this->allPoints[startIdx]), pointNum*sizeof(SPoint), cudaMemcpyHostToDevice, stream));
dataPtr = (SPoint*)this->baseAddrRange[device_idx];
this->nodeAddrTable[device_idx].insert(pair<int, void*>(startCellID, this->baseAddrRange[device_idx]));
this->baseAddrRange[device_idx] = (void*)((char*)this->baseAddrRange[device_idx] + pointNum * sizeof(SPoint));
}
//如果有，不再复制，直接用
else
{
//this->stateTableRange[device_idx]->ptr = this->nodeAddrTable[device_idx].find(startCellID)->second;
dataPtr = (SPoint*)this->nodeAddrTable[device_idx].find(startCellID)->second;
}
int pointsInState = 0;
for (int idx = 0; idx < pointNum; idx+=MAXPOINTINNODE) {
this->stateTableRange[device_idx]->ptr = dataPtr;
this->stateTableRange[device_idx]->xmin = bound.xmin;
this->stateTableRange[device_idx]->xmax = bound.xmax;
this->stateTableRange[device_idx]->ymin = bound.ymin;
this->stateTableRange[device_idx]->ymax = bound.ymax;
if (idx + MAXPOINTINNODE >= pointNum)
pointsInState = pointNum - idx;
else
pointsInState = MAXPOINTINNODE;
this->stateTableRange[device_idx]->candidatePointNum = pointsInState;
this->stateTableRange[device_idx]->startIdxInAllPoints = startIdx + idx;
this->stateTableRange[device_idx]->queryID = queryID;
this->stateTableRange[device_idx] = this->stateTableRange[device_idx] + 1;
this->stateTableLength[device_idx] = this->stateTableLength[device_idx] + 1;
this->testCnt++;
//printf("%d ", this->testCnt);
dataPtr += pointsInState;
}
}
else
{
if (bound.intersect(node->UL->mbb))
findMatchNodeInQuadTreeGPU(node->UL, bound, cells, stream, queryID, device_idx);
if (bound.intersect(node->UR->mbb))
findMatchNodeInQuadTreeGPU(node->UR, bound, cells, stream, queryID, device_idx);
if (bound.intersect(node->DL->mbb))
findMatchNodeInQuadTreeGPU(node->DL, bound, cells, stream, queryID, device_idx);
if (bound.intersect(node->DR->mbb))
findMatchNodeInQuadTreeGPU(node->DR, bound, cells, stream, queryID, device_idx);
}
return 0;
}
int Grid::findMatchNodeInQuadTreeGPUWithoutMorton(QuadtreeNode * node, MBB & bound,
std::vector<QuadtreeNode*>* cells, cudaStream_t stream, int queryID, int device_idx,
vector<int>& blockOffsetInData, vector<int>& blockOffsetNum, vector<int>& blockOffsetOfOffset,
vector<int>& blockLength)
{
int totalLevel = int(log2(this->cellnum) / log2(4));
if (node->isLeaf)
{
// printf("level:%d,node:%d\n", node->level, node->NodeID);
int startCellID = node->NodeID * int(pow(4, (totalLevel - node->level)));
// printf("startcellID:%d\n", startCellID);
int startIdx = this->cellPtr[startCellID].pointRangeStart;
int pointNum = node->numPoints;
SPoint* dataPtr = NULL;
// simulate no morton encoding
int colsOfCells = int(pow(2, (totalLevel - node->level)));
//如果gpu内存中没有该node的信息
if (this->nodeAddrTable[device_idx].find(startCellID) == this->nodeAddrTable[device_idx].end())
{
CUDA_CALL(cudaMemcpyAsync(this->baseAddrRange[device_idx], &(this->allPoints[startIdx]), pointNum * sizeof(SPoint), cudaMemcpyHostToDevice, stream));
dataPtr = (SPoint*)this->baseAddrRange[device_idx];
this->nodeAddrTable[device_idx].insert(pair<int, void*>(startCellID, this->baseAddrRange[device_idx]));
this->baseAddrRange[device_idx] = (void*)((char*)this->baseAddrRange[device_idx] + pointNum * sizeof(SPoint));
}
//如果有，不再复制，直接用
else
{
//this->stateTableRange[device_idx]->ptr = this->nodeAddrTable[device_idx].find(startCellID)->second;
dataPtr = (SPoint*)this->nodeAddrTable[device_idx].find(startCellID)->second;
}
int pointsInState = 0;
for (int idx = 0; idx < pointNum; idx += MAXPOINTINNODE) {
this->stateTableRange[device_idx]->ptr = dataPtr;
this->stateTableRange[device_idx]->xmin = bound.xmin;
this->stateTableRange[device_idx]->xmax = bound.xmax;
this->stateTableRange[device_idx]->ymin = bound.ymin;
this->stateTableRange[device_idx]->ymax = bound.ymax;
if (idx + MAXPOINTINNODE >= pointNum)
pointsInState = pointNum - idx;
else
pointsInState = MAXPOINTINNODE;
this->stateTableRange[device_idx]->candidatePointNum = pointsInState;
this->stateTableRange[device_idx]->startIdxInAllPoints = startIdx + idx;
this->stateTableRange[device_idx]->queryID = queryID;
this->stateTableRange[device_idx] = this->stateTableRange[device_idx] + 1;
this->stateTableLength[device_idx] = this->stateTableLength[device_idx] + 1;
this->testCnt++;
// simulate no morton encoding
// each block for a cuda block
blockOffsetNum.push_back(colsOfCells);
blockOffsetOfOffset.push_back((int)blockOffsetInData.size());
int added = 0;
for (int i = 0; i < colsOfCells; i++) {
blockOffsetInData.push_back(added);
if (added + pointsInState / colsOfCells <= pointsInState)
blockLength.push_back(pointsInState / colsOfCells);
else
blockLength.push_back(pointsInState - added);
}
//printf("%d ", this->testCnt);
dataPtr += pointsInState;
}
}
else
{
if (bound.intersect(node->UL->mbb))
findMatchNodeInQuadTreeGPUWithoutMorton(node->UL, bound, cells, stream, queryID, device_idx,
blockOffsetInData, blockOffsetNum, blockOffsetOfOffset, blockLength);
if (bound.intersect(node->UR->mbb))
findMatchNodeInQuadTreeGPUWithoutMorton(node->UR, bound, cells, stream, queryID, device_idx,
blockOffsetInData, blockOffsetNum, blockOffsetOfOffset, blockLength);
if (bound.intersect(node->DL->mbb))
findMatchNodeInQuadTreeGPUWithoutMorton(node->DL, bound, cells, stream, queryID, device_idx,
blockOffsetInData, blockOffsetNum, blockOffsetOfOffset, blockLength);
if (bound.intersect(node->DR->mbb))
findMatchNodeInQuadTreeGPUWithoutMorton(node->DR, bound, cells, stream, queryID, device_idx,
blockOffsetInData, blockOffsetNum, blockOffsetOfOffset, blockLength);
}
return 0;
}
int Grid::FDCalculateParallelHandeler(priority_queue<FDwithID, vector<FDwithID>, cmp>* queue, map<int, int>* freqVectorQ)
{
this->freqVectors.formPriorityQueue(queue, freqVectorQ);// 关键变量 std::vector<std::map<int, int>> FreqVector; //每个map代表一个轨迹 trajDB中的轨迹
return 0;
}
// 负责找到top-k的EDR
// thread(std::mem_fn(&Grid::SimilarityMultiThreadHandler), this, queryQueue, qTra, 1, EDRCalculated, kValue, qIDnow)
int Grid::SimilarityMultiThreadHandler(priority_queue<FDwithID, vector<FDwithID>, cmp>* queryQueue, Trajectory* qTra, int queryTrajNum, priority_queue<FDwithID, vector<FDwithID>, cmpBig>* EDRCalculated, int kValue, int startQueryIdx)
{
const int k = KSIMILARITY;
int* numElemInCalculatedQueue = new int[queryTrajNum];
for (int i = 0; i <= queryTrajNum - 1; i++)
numElemInCalculatedQueue[i] = 0;
for (int qID = startQueryIdx; qID <= startQueryIdx + queryTrajNum - 1; qID++)
{
SPoint* queryTra = (SPoint*)malloc(sizeof(SPoint) * qTra[qID].length);
for (int i = 0; i <= qTra[qID].length - 1; i++)
{
queryTra[i].x = qTra[qID].points[i].lon;
queryTra[i].y = qTra[qID].points[i].lat;
queryTra[i].tID = qTra[qID].tid; // 888888
}
int worstNow = 9999999;
//timer.start();
//printf("qID:%d", qID);
/*MyTimer tt;*/
while (worstNow > queryQueue[qID].top().FD)// worst now 代表最大EDR
{
/*tt.start();*/
int candidateTrajID[k];// m 保存ID
//printf("%d", worstNow);
// 第0步：提取topk(topm)FD
for (int i = 0; i <= k - 1; i++)
{
candidateTrajID[i] = queryQueue[qID].top().traID;// FD小顶堆的ID依次pop到candidateTrajID[]中
queryQueue[qID].pop();
}
//EDR calculate
//第一步：从AllPoints里提取出来轨迹(m条)
SPoint** candidateTra = (SPoint**)malloc(sizeof(SPoint*) * k);
int* candidateTraLength = (int*)malloc(sizeof(int) * k);
for (int i = 0; i <= k - 1; i++)
{
candidateTra[i] = (SPoint*)malloc(sizeof(SPoint) * this->cellBasedTrajectory[candidateTrajID[i]].trajLength);
SPoint* tempPtr = candidateTra[i];
// 遍历每条轨迹 借助Lt
for (int subID = 0; subID <= this->cellBasedTrajectory[candidateTrajID[i]].length - 1; subID++)
{
int idxInAllPoints = this->cellBasedTrajectory[candidateTrajID[i]].startIdx[subID];
memcpy(tempPtr, &this->allPoints[idxInAllPoints], sizeof(SPoint) * this->cellBasedTrajectory[candidateTrajID[i]].numOfPointInCell[subID]);
//for (int cnt = 0; cnt <= this->cellBasedTrajectory[candidateTrajID[i]].numOfPointInCell[subID] - 1; cnt++) {
// candidateTra[i][cnt] = this->allPoints[idxInAllPoints+cnt];
//}
//printf("%d ", this->cellBasedTrajectory[candidateTrajID[i]].numOfPointInCell[subID]);
tempPtr += this->cellBasedTrajectory[candidateTrajID[i]].numOfPointInCell[subID];
}
candidateTraLength[i] = this->cellBasedTrajectory[candidateTrajID[i]].trajLength;
}
//tt.stop();
//cout << "Part3.1 time:" << tt.elapse() << endl;
//tt.start();
//第二步：计算EDR
//printf("%d", qID);
int resultReturned[k];
this->SimilarityExecuter(queryTra, candidateTra, qTra[qID].length, candidateTraLength, k, resultReturned);
//tt.stop();
//cout << "Part3.3 time:" << tt.elapse() << endl;
for (int i = 0; i <= k - 1; i++)
{
if (numElemInCalculatedQueue[qID - startQueryIdx] < kValue)// qID - startQueryIdxm = 0 比较头元素 第一次计算
{
//直接往PQ里加
FDwithID fd;
fd.traID = candidateTrajID[i];
fd.FD = resultReturned[i];